UNIVERSIDAD DE GRANADA

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SaraMarañónJi ménez Granada,201 1 TESI SDOCTORAL

UNIVERSIDAD DE GRANADA DEPARTAMENTO DE ECOLOGÍA

EFECTO DEL MANEJO DE LA MADERA QUEMADA DESPUÉS DE UN INCENDIO SOBRE EL CICLO DEL CARBONO Y NUTRIENTES EN UN ECOSISTEMA DE MONTAÑA MEDITERRÁNEA.

TESIS DOCTORAL Sara Marañón Jiménez Granada, 2011

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EFECTO DEL MANEJO DE LA MADERA QUEMADA DESPUÉS DE UN INCENDIO SOBRE EL CICLO DEL CARBONO Y NUTRIENTES EN UN ECOSISTEMA DE MONTAÑA MEDITERRÁNEA.

Memoria que la Licenciada Sara Marañón presenta para aspirar al Grado de Doctor por la Universidad de Granada

Esta memoria ha sido realizada bajo la dirección de: Dr. Jorge Castro Gutiérrez, Dr. Regino Zamora Rodríguez y Dr. Andrew S. Kowalski

Lda. Sara Marañón Jiménez Aspirante al Grado de Doctor

Granada, septiembre de 2011

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Dr. Jorge Castro Gutiérrez, Profesor Titular de Ecología de la Universidad de Granada, Dr. Regino Zamora Rodríguez, Catedrático de Ecología de la Universidad de Granada y Dr. Andrew S. Kowalski Profesor Titular de Física Aplicada de la Universidad de Granada

CERTIFICAN Que los trabajos de investigación desarrollados en la Memoria de Tesis Doctoral: ”Efecto del manejo de la madera quemada después de un incendio sobre el ciclo del carbono y nutrientes en un ecosistema de montaña mediterránea”, son aptos para ser presentados por la Lda. Sara Marañón Jiménez ante el Tribunal que en su día se designe, para aspirar al Grado de Doctor por la Universidad de Granada. Y para que así conste, en cumplimiento de las disposiciones vigentes, extendemos el presente certificado a 2 de septiembre de 2010

Dr. Jorge Castro Gutiérrez

Dr. Regino Zamora Rodríguez

Dr. Andrew S. Kowalski

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Durante el tiempo de realización de esta Tesis Doctoral he disfrutado de una Beca del Programa Nacional de Formación de Personal Universitario del Ministerio de Educación y Ciencia Ref. (AP2006-00387).

Este trabajo estuvo financiado por los proyectos (SUM2006-0001000-00) del INIA, (10/2005) del Organismo Autónomo de Parques Nacionales (MMA), Consolider-Ingenio Montes (CSD2008-00040) del MICINN, GESBOME (P06-RNM-1890) de la Junta de Andalucía, COILEX (CGL2008-01671) del MICINN, Red Nacional Española de torres de flujo de CO2 (Carbored-II; CGL2010-22193-C04-02) y por el 7th 9 proyecto del programa marco GHG-Europe de la Comunidad Europea (FP7/2007-2013; concesión de ayuda 244122).

La investigación presentada en esta Tesis Doctoral se ha realizado en los Departamentos de Ecología y de Física Aplicada de la Universidad de Granada.

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A ti, Óscar, porque llegaste justo cuando más te necesitaba, y te quedaste! porque fuiste mi sol, mi luz, mi aliento y mi energía...

Y a mi padre, a quien debo tantísimo…

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“Los que están siempre de vuelta de todo son los que nunca han ido a ninguna parte”

Antonio Machado.

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__________________________________________________________________________Indice

INDICE

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AGRADECIMIENTOS

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RESUMEN / ABSTRACT

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INTRODUCCIÓN GENERAL

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CAPITULO 1: Macro and micronutrient content in burnt wood after a wildfire in a Mediterranean pine forest

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CAPITULO 2: Effect of decomposing burnt wood on soil fertility and nutrient availability in a Mediterranean ecosystem

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CAPITULO 3: Post-fire salvage logging increases water stress and reduces seedling growth and performance of Pinus pinaster in the Sierra Nevada (SE Spain)

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CAPITULO 4: Post-fire soil respiration in relation to burnt wood management in a Mediterranean mountain ecosystem

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CAPITULO 5: Post-fire salvage logging reduces carbon sequestration in Mediterranean coniferous forest

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DISCUSIÓN GENERAL

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CONCLUSIONES / CONCLUSIONS

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AGRADECIMIENTOS

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Agradecimientos_________________________________________________________________

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_________________________________________________________________Agradecimientos

AGRADECIMIENTOS

A ver… ¿por dónde empiezo? Sé que suele ocurrir esto ante una página en blanco, pero en este caso se trata de expresar con palabras todo eso que se apelotona y arremolina en la garganta y pelea por salir cuando echo la vista atrás y recuerdo… y que es tanta esa gratitud… ¡que necesitaría otra tesis para daros las gracias! Gracias por haberme enseñado y ayudado, cada uno a su modo, de la mejor manera en que cada uno supisteis. Por haber estado ahí cuando os necesité, aún sin haberos llamado. Perdón y gracias por haber capeado esas “tormentas”, y haber sabido salir ilesos del temporal. Y es ahora que esto llega a su fin…y miro atrás…cuando empiezo a comprender de verdad que tal fin no existe, y que lo realmente importante es ese camino que me habéis ayudado a recorrer, aún a veces sin saberlo. Ese aliento, valentía y ánimos que me habéis prestado cuando se hacía taaaan pedregoso, y esas ganas, esa fé en mí que nunca perdisteis, aún cuando yo sí que lo hiciese, y ese cariño, los abrazos, los consejos y las risas! Porque esta tesis, al igual que yo, está hecha de pequeñas piezas que he ido recogiendo en ese camino, ¡¡y que al fin conseguí encajar!! Paciencia y templanza,…¡gracias, Papá! Y por jugar conmigo “a explorar”, ¡ahí empezó todo! Y gracias, mamá, por la perseverancia que transmitiste y algo de esa creatividad, por enseñarme a ser exigente conmigo misma y… por ese temperamento! que de vez en cuando no viene mal…Gloria, gracias por creer en mí, ¡tú también te mereces lo mejor! Perdonadme por haberme perdido tantos momentos irrepetibles, yo también os he echado mucho de menos. Abuela Paquita, que has sabido cuidarme y escucharme como nadie en tu casa, sobre todo ese primer año en Granada, ¡y qué comidas más ricas esperaban al volver del campo, cuando volvía tan cansada! Y abuelo Pepe, tenías razón, no merece la pena preocuparse tanto por “ná”, sino que hay que ser valiente y luchar hasta el final. A mi también me hubiese gustado que te quedases para ver como se

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Agradecimientos_________________________________________________________________

doctora la segunda de la familia…¡también vá por ti!. Titos Goyo, May, Paco, Pura, Merche y Conchi y Laurent muchas gracias por hacerme sentir de nuevo en familia, por vuestros consejos, por esos “tápers” y conservas, mmm. Abuelo Andrés, gracias por tu bondad, tu fortaleza y tu alegría. ¿Has visto qué mayor se hace este “troncho”? Y a ti abuela Pepita, que también te quedaste en el camino. A los amigos de Málaga, a Loli y Antonia, mi “oráculo sentimental” y mis amigas de “tó la vía”, a Javi Blasco, ese sabio que te hace reír y con el que los problemas se esfuman a si los miras “entre los dedos” y a Laura y Adela. Gracias a todos por hacerme recordar siempre quién soy y por no cambiar nunca. Y a vosotros, ¡mi “familia del día a día”! Inma, gracias, por no haber bajado la guardia en ningún momento, acudiendo “rauda y veloz” a la señal del “SOS”, por saber escuchar de verdad, qué suerte la mía por haberte conocido… Anita, hermanita pequeña de tesis, ¡gracias por tu energía, campeona!, por ese entusiasmo, por saber ver siempre el vaso medio lleno, por recordarme por qué nos metimos en estos “fregaos”, ¡y por tus bizcochos, que alegraban mis mañanas! Y a todos vosotros, “personajes”, ya sabeis… Nieves, Marta “la Gunti”, Nacho, Pablo, Indra, Kárim, y a Martika, David y Manu de Bellas Artes, ¡qué hubiese sido de mi todos vosotros! Sin esas excursiones, esas “cenitas-atracón”, esos abrazos que dan la vida y vuestras bromas…cuántos buenos raticos, ¡y cuántas razones que celebrar! Gracias por hacerme olvidar mis agobios, por hacer que me encante vivir en esta ciudad y por recordarme lo que realmente hace que la vida merezca la pena. Y si alguien ha conseguido que “en esos días más chungos” el sonreír al llegar “al curro” no fuese tan difícil y que no me sintiese la única “pringailla” sois vosotros, mis hermanitos de tesis. Mati, el hermano mayor al que admirar, siempre dando ánimos y con respuestas para todo… ¿cuántas “birras” te deberé ya? y Asier, ese “tío duro” con un corazón que no le cabe en el pecho, ahí, codo a codo hasta en los momentos más intempestivos…hey, vasco…al final va a ser que te has “refinao

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un pelín y tó”! Juande, Ayub, Manu, Fran… Pero tampoco me olvido esos dos “supermastuerzos”, Raymon y Enrique, ¿qué habría sido de una “tirillas” como yo si no hubiese tenido vuestra ayuda para pegar barrenazos en la Sierra y recoger troncos quemados a pleno sol? Y todo ello sin perder el buen humor, ¡sois unos cracks! ¿Y sin la mama Susanita?, esa superquímica siempre dispuesta a remangarse y nadar entre muestras a mi rescate… ¡la hubiese “liao parda” más de una vez entre tanto reactivo! Ángela, Belencilla, esas “serias” trabajadoras, gracias por esas risas, sé cuánto os costaba hacer chistes para hacerme reír de vez en cuando…gracias por todo vuestro apoyo y por esa fuerza…Y muchísimas gracias a Eulogio el técnico más “apañao” de la facultad, y a Gustavo, un “ingenieromecánico” de excepción capaz de sacarle serrín a las piedras. Tampoco me olvido de vosotros los físicos, a los que estáis en el CEAMA, por aguantar mis seminarios, y adoptarme en vuestros eventos sociales, y a Borja, Luismi, Cecile, Juan Antonio, y claro! Penélope, ¡qué paciencia has tenido! mil gracias por tu ayuda, por tu ejemplo de profesionalidad y de eficiencia, por tus consejos en lo profesional y lo personal, por tu amistad…¡ah!, ¡y por hacer esos viajecillos de trabajo más divertidos! Y a mis “compis” del CEAMA durante aquellas largas horas en “el zulo”, por aquellas veces en que no os olvidasteis de que aún seguía dentro y, ¡también por aquellas en las que os disteis cuenta de que lo habíais olvidado! Gracias de verdad a todos, y en especial a “los curros” que mejor hacen honor a su nombre, a Pablillo “el matri”, porque… quién sabe si estaría aquí si no hubiese sido por ti? las vueltas que da la vida…, y a Isa Sánchez. A Peter Fulé e Ivan Janssens, mis tutores de estancia debo agradeceros esas ideas frescas y sugerencias, ese ejemplo de pasión por la investigación, ese tiempo tan preciado que me dedicasteis, vuestra hospitalidad, y vuestro trato tan humano y familiar, que tantísimo se agradecen cuando se está lejos de casa. Kristina, Amy, Manú, Sara y Marylin fuisteis los responsables de que el tiempo belga o la “morriña” no acabasen conmigo y de que recuerde estancias de forma tan 19

Agradecimientos_________________________________________________________________

entrañable. Gracias también a Robert Jandl por la confianza prestada y las oportunidades de colaboración que tan necesarias son cuando se está empezando, y a Mirco Rodeghiero por tu ejemplo, tus preciados consejos sobre “cómo ser investigador y poder disfrutar de la vida en el intento”, por tu amistad y por tu sentido del humor. Quiero también agradecer especialmente al departamento de edafología el permitirme usar sus laboratorios y, en especial, a Paco Martín Peinado por su tiempo y su ayuda desinteresada y a Emilia Fernández Ondoño por su inestimable colaboración, su amabilidad y sus palabras de ánimo. Y ahora, la parte más…“de-li-ca-da”. ¿Cómo iba a olvidar a mis directores?, a quienes hicieron posible una tesis en “tres dimensiones”. Regino, gracias por tu confianza, por haber tenido siempre palabras de ánimo, por tus consejos desde la experiencia y gracias por esa valiosa perspectiva global. A Andy, por tu franqueza, por tu modestia, tus brillantes ideas, tu paciencia con mi inglés, por tu ayuda siempre que la he necesitado y por preguntar siempre, de verdad, y antes de nada “¿cómo estás?”. Y gracias Jorge, por toda esa dedicación, por tu entusiasmo y tu carácter positivo en “aquellas veces”, y por no haberme hecho perder la paciencia más de lo que la perdí “esas otras veces”… (en fin, podía haber sido peor…¿no?). Gracias por tu espíritu crítico, y por haber sabido desarrollar como nadie el mío, por enfrascarte hasta las cejas en esto como nadie y por hacer esta tesis tan “tuya”. Y Óscar, vida…, millones de gracias a ti. Porque con lo cabezona que soy, puede que quizás también lo hubiese conseguido sin tí, pero sólo tú has sabido transformar los momentos más amargos en los más dulces. Conseguiste hacer que recuerde este “veranito” y este último año con mucho cariño y le diste a todo esto su verdadero sentido. ¡Ole por esta dichosa tesis que me permitió conocerte! Sólo por ti… ¡haría otra!

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RESUMEN / ABSTRACT

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Resumen________________________________________________________________________

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________________________________________________________________________Resumen

RESUMEN

Tras un incendio forestal, una práctica forestal muy extendida en relación a la madera quemada consiste en su extracción rápida e intensa (saca de la madera). Sin embargo, la retirada de la madera quemada supone una perturbación adicional sobre el ecosistema que puede suponer un impacto negativo y sinérgico sobre su funcionamiento. Por otro lado, la madera quemada puede contener aún una importante cantidad de nutrientes que podrían ser incorporados progresivamente al suelo, favoreciendo así la regeneración natural del ecosistema. En la presente tesis doctoral se pretende analizar el efecto de diferentes grados de manejo de la madera quemada tras un incendio forestal sobre el reciclaje de carbono (C) y nutrientes, así como su implicación sobre la regeneración y el funcionamiento general del ecosistema. Para ello, se establecieron en diversas parcelas a lo largo de un gradiente altitudinal (de ca. 1.500 a 2.300 m) tres tratamientos que difieren en su grado de intervención de la madera quemada: 1) “No Intervención” (NI), en la que los árboles se dejaron en pie (sin intervención). 2) “Extracción” (E), consistente en el corte de todos los árboles, retirada de los troncos, y el triturado de los restos no aprovechables y ramas finas (procedimiento habitual). 3) “Intervención Intermedia” (Ii), consistente en el corte, desramado y tronzado en 2-3 trozas del 90% de los árboles, dejando toda la biomasa in situ sobre el suelo. El Capítulo 1 de esta tesis se dedica a determinar el contenido inicial o capital de nutrientes existente en la madera quemada tras el incendio y a la valoración de su potencial para amortiguar las pérdidas de nutrientes. Esta potencialidad será interpretada en función de la magnitud del reservorio de

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Resumen________________________________________________________________________

nutrientes en la madera en relación con el existente en la capa superior del suelo. En el Capítulo 2 se evalúa el efecto de la madera quemada sobre la fertilidad del suelo. Para ello se determina la tasa de liberación de nutrientes esenciales mayoritarios que sufre la madera a medida que se descompone. Por otro lado, se analiza el efecto de la presencia de la madera sobre la disponibilidad de nutrientes en el suelo y otros parámetros edáficos. El efecto que ejerce el manejo de la madera quemada sobre el desarrollo de la vegetación a través de la modificación de la fertilidad y del microclima del suelo es objeto de estudio en el Capítulo 3. Concretamente, se estudian diversos parámetros fisiológicos y fisiognómicos que permitirán determinar aspectos relacionados con el estrés hídrico, el crecimiento y el estado nutritivo de plántulas de Pinus pinaster de regeneración natural tras el incendio. En el Capítulo 4 se aborda el efecto del manejo de la madera quemada sobre la respiración del suelo. Para ello, se determinará el flujo de CO2 del suelo existente bajo distintos tratamientos de la madera quemada a diferentes escalas temporales (horaria y estacional), y mediante varias aproximaciones (medidas de campo en condiciones naturales y bajo simulación de eventos lluvia). Por último, en el Capítulo 5 se pretende determinar el balance del C en el ecosistema resultante de la modulación de las distintas componentes del ciclo del C por el manejo post-incendio de la madera. Con este fin, se comparan los flujos netos de CO2 a escala de ecosistema de los dos tratamientos más contrapuestos en cuanto al grado de manejo (E, con máxima intensidad de intervención versus NI, en ausencia de intervención). En conjunto, los resultados de esta tesis muestran que la presencia de la madera quemada amortigua las pérdidas de nutrientes que se producen después de un incendio, contribuyendo a la recuperación de la fertilidad, el reciclaje de nutrientes y la dinámica biogeoquímica del ecosistema. Por tanto, la aplicación de técnicas de manejo post-incendio asociadas a la madera quemada de menor intensidad puede mejorar la sostenibilidad y resiliencia ecosistémicas. La mejora en

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el funcionamiento del ecosistema puede facilitar, por tanto, el proceso de regeneración natural y contribuir, en último término, a la recuperación de la capacidad de secuestro de C.

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Abstract________________________________________________________________________

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_________________________________________________________________________Abstract

ABSTRACT

After a wildfire, a widely extended forest practise is the fast and intensive removal of the burnt wood (salvage logging). However, the burnt wood withdrawal represents an additional perturbation for the ecosystem that can have a synergic negative impact on its functioning. On the other hand, the burnt wood can still contain an important amount of nutrients that could be progressively incorporated into the soil and therefore, enhance the natural regeneration of the ecosystem. In this doctoral thesis, we intend to analyze the effect of different degrees of burnt wood management after a wildfire on the carbon (C) and nutrient cycling, as well as the implications for the regeneration and general ecosystem functioning. For this, we established in several sites along an altitudinal gradient (from ca. 1500 to 2300 m a.s.l.) three treatments that differed in the intensity of the intervention of the burnt wood: 1) “Non Intervention” (NI), in which the burnt trees were left standing (without intervention). 2) “Salvage Logging” (SL), consisting of cutting all the burnt trees, removing the trunks and chipping the remaining non profitable fine woody residues (the traditional procedure). 3) “Cut plus Lopping” (CL), consisting of felling the 90% of the burnt trees, lopping off the branches and cutting the logs in 2-3 pieces, leaving all the biomass in situ over the ground. Chapter 1 of this thesis is devoted to determine the initial nutrient content or capital existing in the burnt wood after the wildfire, and to the evaluation of its potential to ameliorate nutrient losses. This potential will be assessed according to the relative magnitude of the nutrient reservoir in the burnt wood compared to the existing nutrients in the upper soil layer. In Chapter 2, we assess the effect of the

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Abstract________________________________________________________________________

burnt wood on the soil fertility. For this, we determine the release rate of essential macronutrients from the burnt wood as it decomposes. Additionally, we analyse the effect of the presence of burnt wood on the soil nutrient availability and other edaphic parameters. The effect of the burnt wood management on the vegetation performance through the alteration of the soil fertility and microclimate is tackled in Chapter 3. Concretely, several physiognomic and physiological variables are measured in naturally regenerating seedlings of Pinus pinaster after the wildfire, in order to determine aspects related to their water stress, growth and nutritional status. In Chapter 4, we investigate the effect of the burnt wood management on soil respiration. For this, the soil CO2 flux will be determined in the different treatments at different temporal scales (hourly and seasonal), and by means of different approaches (field measurements, both under natural conditions and under simulated rain events). Finally, Chapter 5 is aimed to determine the ecosystem C balance as a result of the modulation of several components of the C cycle by the post-fire burnt wood management. With this objective, the net CO2 fluxes of the two most extreme treatments according to the degree of management are compared at the ecosystem level (SL, subjected to the highest intensity of intervention versus NI, in absence of intervention). Overall, the results of this thesis show that the presence of burnt wood ameliorates post-fire nutrient losses, contributing to the recovery of fertility, nutrient cycling and the biochemical dynamic of the ecosystem. Therefore, the implementation of less intensive post-fire management techniques regarding the burnt wood can improve ecosystem sustainability and resilience. Improved ecosystem functioning can enhance, as a result, the process of natural regeneration and ultimately contribute to the recovery of the C sequestration capacity.

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INTRODUCCIÓN GENERAL

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Introducción general _____________________________________________________________

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_____________________________________________________________Introducción general

INTRODUCCIÓN GENERAL 1. LOS INCENDIOS FORESTALES COMO PERTURBACIÓN Y SU PROBLEMÁTICA

El fuego es una de las principales perturbaciones de los ecosistemas terrestres y motor de cambio global, ya que produce una profunda alteración en los patrones de uso del suelo, en los ciclos de nutrientes, así como en el papel del ecosistema como fuente o sumidero de carbono (Lloret et al., 2002; Viedma et al., 2006). En el caso de muchos ecosistemas mediterráneos, el fuego constituye, no obstante, una perturbación natural implícita en su dinámica ecológica (Duguy et al., 2007; Moreno et al., 1998). De este modo, el fuego entendido como proceso natural no conlleva necesariamente la degradación irreversible del ecosistema. Cuando su intensidad, magnitud y frecuencia es baja, el fuego puede contribuir a la movilización y reciclaje de nutrientes y a generar una heterogeneidad de hábitats que fomente la diversidad específica y estructural en el ecosistema (Covington et al., 1997; Kaye y Hart, 1998; Lindenmayer et al., 2008; Selmants et al., 2008; Swanson et al., 2010). Sin embargo, en las últimas décadas el fuego se ha convertido probablemente en la perturbación más importante en España en términos de magnitud e intensidad, presentando además una elevada frecuencia (Moreno et al., 1998). Esto ha venido condicionado fundamentalmente por factores humanos: plantaciones monoespecíficas de alta densidad en abandono o ausencia de manejo, cambios de usos y aprovechamientos forestales, conflictos económicos y sociales, etc. (Cerdá y Mataix-Solera et al., 2009; Conard et al., 2002). Más aún, algunos escenarios de cambio climático predicen un incremento de las temperaturas y veranos más secos en el área Mediterránea así como en otros muchos ecosistemas del mundo (Giorgi y Lionello, 2008; IPCC, 2007). Esto causaría una desecación más prolongada, un incremento en la inflamabilidad de los restos forestales y, por consiguiente, un mayor riesgo de incendios (Duguy et al., 2007; FAO, 2007). De 31

Introducción general _____________________________________________________________

hecho, esta tendencia se ha constatado en las últimas décadas para algunas regiones (Mouillot et al., 2002; Piñol et al., 1998). Como muestra de ello, sólo en España se producen unos 20.000 incendios forestales al año, quemando en promedio una superficie de 118.000 hectáreas. Bajo la tendencia actual, se calcula que toda la superficie forestal de España se habrá visto afectada por incendios en los próximos dos siglos (datos obtenidos del Ministerio de Medio Ambiente, Medio Rural y Marino, Cerdá y Mataix-Solera et al., 2009). Los incendios forestales reiterativos y de gran intensidad repercuten negativamente sobre procesos y funciones claves del ecosistema, como la capacidad de secuestro de carbono, y sobre la disponibilidad y el reciclaje de nutrientes (Bond-Lamberty et al., 2004; Certini, 2005; Rutigliano et al., 2002; Trabaud, 1994; Wan et al., 2001). Durante un incendio de alta intensidad se produce la combustión de gran cantidad de materia orgánica y de la biomasa existente, lo que se traduce en una liberación repentina de gran cantidad de carbono y nutrientes en forma de gases a la atmósfera (Trabaud, 1994). El fuego provoca además, la reducción o incluso la eliminación de la capacidad de retención de carbono por parte de la vegetación. Esto supone la transformación del balance de carbono en el ecosistema, que pasa de ser de sumidero a fuente neta de carbono (Amiro, 2001, Amiro et al., 2003, 2006; Mkhabela et al., 2009). Parte de los nutrientes liberados por el fuego serán depositados en el suelo con las cenizas (Neary et al., 1999, Raison, 1979; Yang et al., 2003). Sin embargo, el fuego también puede alterar las propiedades físicas y químicas de los suelos, pudiendo sufrir estos una pérdida o transformación de la materia orgánica que contienen en sustancias hidrofóbicas y recalcitrantes (Certini, 2005; DeBano et al., 1998; Gonzalez-Pérez et al., 2004). Esto, junto con la disrupción de los agregados y cementantes orgánicos del suelo, conlleva la alteración de parámetros como la textura y estructura, el aumento de la densidad aparente y la disminución de la capacidad de intercambio catiónico y de retención de agua (DeBano et al., 1998; 32

_____________________________________________________________Introducción general

Certini, 2005). Como resultado, los suelos afectados por incendios forestales son mucho menos estables y especialmente susceptibles a la erosión, especialmente en suelos arenosos y zonas de alta pendiente. Por ello, buena parte de los nutrientes depositados con las cenizas pueden perderse por erosión, arrastre y lixiviado durante los primeros eventos de lluvia (DeBano y Conrand, 1978; Fernández et al., 2007; Shakesby, 2011; Thomas et al., 1999). De este modo, el aumento en la disponibilidad de nutrientes en el suelo que se suele producir tras un incendio es a menudo efímero y no persiste más de varios meses (Certini, 2005, Iglesias et al., 1997; Wan et al., 2001, Yang et al., 2003). Las condiciones microclimáticas del suelo se verán asimismo alteradas tras un incendio. Así, por ejemplo, la oscilación térmica en el suelo se verá ampliada al perderse la protección proporcionada por la cubierta de la vegetación, hojarasca y otros restos vegetales. La incidencia de la radiación también será mayor, lo que se traduce en un mayor calentamiento del suelo durante las horas centrales del día (Castro et al., 2011) y en una mayor desecación (Alauzis et al., 2004; Castro et al., 2011; Certini, 2005; Sullivan et al., 2011). En resumen, los incendios de alta intensidad originan como resultado pérdidas netas en el capital o reservorios de nutrientes y carbono existentes en el ecosistema, y pueden dar lugar a condiciones microclimáticas más desfavorables para el desarrollo de la vegetación y la actividad microbiana. Esto supone la intensificación de los factores ecológicos que típicamente limitan la actividad y desarrollo biológico en ecosistemas mediterráneos (Costa-Tenorio et al., 1998; Sardans et al., 2005). La fertilidad y disponibilidad de nutrientes en el suelo es, sin embargo, crucial para la regeneración de la vegetación después de un incendio. Durante las primeras etapas de la regeneración, la vegetación depende especialmente de los aportes externos de nutrientes (Imbert et al., 2004; Landsberg y Gower, 1997). De hecho, la viabilidad del ecosistema y el mantenimiento de su estabilidad no sería posible sin la existencia del suficiente reservorio de nutrientes que asegure la 33

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productividad de la comunidad vegetal (Augusto et al. 2000; Blanco et al., 2005; Imbert et al., 2004; Miller, 1986). El impacto del fuego sobre las condiciones edáficas y la disponibilidad de nutrientes también determina la abundancia y actividad de los microorganismos (De Marco et al., 2005; Dumontet et al., 1996; Fierro et al., 2007; Fioretto et al., 2005; Hernández et al., 1997; Kara y Bolat, 2009; Saa et al., 1993). Estos parámetros microbianos son de gran importancia para la calidad del suelo, ya que intervienen en la mineralización de la materia orgánica y su transformación en formas asimilables para la vegetación y, en definitiva, en el balance del carbono y reciclaje de nutrientes (Staddon et al., 1999).

2. EL MANEJO FORESTAL POST-INCENDIO DE LA MADERA QUEMADA: PROS Y CONTRAS DE LA EXTRACCIÓN INTENSIVA

Tras un incendio forestal es común que el hombre actúe sobre la masa afectada. Una práctica forestal muy extendida tras los incendios forestales en relación a la madera quemada consiste en una extracción rápida e intensa (saca de la madera), generalmente en cuestión de meses, en la que se cortan los árboles quemados y en algunos casos los parcialmente dañados, se extraen los troncos, y se eliminan las ramas y otros restos mediante astillado o quema (Bautista et al., 2004; Castro et al., 2009, 2010a,b; Martínez-Sánchez et al., 1999). Ésta es, de hecho, la actuación habitual en España, pero es igualmente común en otros países y regiones como Norteamérica, Australia, regiones tropicales, o en el ámbito de la cuenca mediterránea (Bautista et al., 2004; Lindenmayer et al., 2004, 2008; McIver y Starr, 2000; Van Nieuwstadt et al., 2001). Esto origina un paisaje en el que se cambia de una masa en pie con predominio de árboles calcinados a una superficie despejada de la que se ha eliminado la mayor parte de la biomasa. Las razones para acometer esta actuación son múltiples y dependen de las particularidades de cada región y los objetivos de restauración del área afectada

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(Bautista et al., 2004; Lindenmayer et al., 2008; McIver y Starr, 2000). Muchas masas arboladas están sujetas a explotación forestal y constituyen un sector clave para la economía de muchos países. En tales circunstancias, la corta urgente de la madera permite compensar las pérdidas económicas sufridas por el incendio mediante su comercialización (Harrington, 1996; Lindenmayer y Noss, 2006; McIver y Starr, 2000; Purdon et al., 2004). Sin embargo, la extracción de la madera no resulta siempre económicamente beneficiosa, como queda ejemplificado por los bosques del área Mediterránea, donde con frecuencia la retirada de los troncos quemados implica un coste neto dada la baja calidad y valor económico de la madera (Bautista et al. 2004). Además, en este caso existe una normativa legal que regula y limita su posible comercialización (para el caso de Sierra Nevada: BOJA nº 155 de 2011, Decreto 238/2011, de 12 de Julio por el que se establece la ordenación y gestión de Sierra Nevada). La extracción de la madera ofrece ventajas para el manejo posterior de la zona afectada ya que facilita el acceso y las labores de repoblación y reduce el riesgo de accidentes por el colapso de los árboles quemados durante los trabajos de manejo (Bautista et al., 2004; Martínez-Sánchez et al., 1999; McIver y Starr, 2000; Ne´eman et al., 1995; Spanos et al., 2005). No obstante, la necesidad de acceder al área para su futura restauración dependerá también de la capacidad de regeneración natural y los objetivos de manejo del área. Así, por ejemplo, si el objetivo principal se centra en la preservación de la función del ecosistema y su estructura (como ocurre en el lugar donde se realiza este estudio, el cual se localiza en un Parque Nacional y Natural), puede ser aconsejable dejar la madera quemada in situ como un componente esencial para la estructura del hábitat y el reciclaje de nutrientes (Brown et al., 2003). Más aún, si lo que se pretende es potenciar los procesos de regeneración natural puede ser incluso deseable reducir el acceso del ganado doméstico o las personas durante cierto tiempo. En cuanto al riesgo de accidentes, éstos deben ser valorados en cada caso teniendo en cuenta el uso social, recreativo

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o el tránsito en la zona y pueden ser mitigados cortando los árboles en las zonas más frecuentadas. Otra de las principales razones que se argumentan para retirar la madera quemada es la de eliminar la carga de combustible muerto con objeto de aminorar el riesgo de nuevos incendios. Los restos de madera gruesos pueden ser, no obstante, menos determinantes para el riesgo de incendios y su severidad de lo que se ha asumido tradicionalmente (Passovoy y Fulé, 2006), en particular en paisajes antropizados (Mortiz et al., 2004; Salvador et al., 2005), mientras que otros factores como la topografía, el microclima, o la densidad de población en la zona pueden ser factores de mayor peso. Otros estudios también argumentan que la extracción intensiva puede incrementar en lugar de reducir el riesgo de incendios a corto plazo, ya que puede conllevar una mayor abundancia de restos de madera de fracción fina de fácil ignición (Donato et al., 2006; Odion et al., 2004; Thompson et al., 2007). Por otro lado, los restos gruesos de madera tienen un menor poder de ignición, y dejados sobre el suelo pueden actuar reteniendo la humedad en su interior (Harmon et al., 1986). Bajo estas condiciones, éstos pueden incluso actuar ralentizando y dificultando la progresión del fuego (Andrew et al., 2000; Campbell y Tanton, 1981). De forma indirecta, la alta densidad de árboles con la que se repueblan con frecuencia las zonas previamente sometidas a la extracción intensiva de la madera, se considera una de las principales causas de riesgo de incendios recurrentes (Thompson et al., 2007). La reducción del riesgo de plagas (en particular de insectos barrenadores) hacia las masas forestales no afectadas por el incendio es otro de los argumentos para la extracción de la madera quemada. Sin embargo, las larvas de insectos barrenadores se alimentan de floema vivo (Jenkins et al., 2008; Martikainen et al., 2006), por lo que el riesgo se centraría en aquellos árboles parcialmente quemados y debilitados o en aquellos casos en los que la madera quemada mantiene aun floema activo (en incendios de baja intensidad). Por ello, la prevención de este 36

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riesgo no siempre requiere una actuación extensiva y generalizada sobre toda la biomasa afectada. Por otro lado, la madera representa la única fuente de alimento para gran cantidad de especies de hongos e insectos, los cuales son de gran importancia para la descomposición de la madera, la liberación de los nutrientes contenidos en ella y constituyen una parte fundamental de muchas cadenas tróficas (Grove y Meggs, 2003; Harmon et al., 1986; Hutto, 2006; McCay y Komoroski, 2004; Reynolds et al., 1992; Torgersen y Bull, 1995). Por último, y a pesar de su carácter eminentemente subjetivo, cabe mencionar los argumentos de índole psicológica, emotiva y estética. Con frecuencia, el impacto visual que provoca un paisaje arrasado por un incendio con los árboles calcinados es mayor que si estos árboles son retirados. Este factor no es trivial, a pesar de lo que en principio pueda parecer, sobre todo en aquellos casos en los que la población se encuentra vinculada al bosque ya sea económicamente mediante su aprovechamiento y su uso recreativo, o simplemente emocionalmente. En este contexto sociocultural, la administración puede incluso verse presionada por la población a intervenir de forma apresurada sobre las zonas afectadas, a menudo sin previa planificación o valoración de costes y beneficios, tanto económicos como ecológicos. No valorar adecuadamente la actuación forestal más apropiada en cada caso concreto puede repercutir de forma negativa y directa sobre los vecinos de la zona. Por ello, son esenciales la educación ambiental y la información sobre las actuaciones a realizar y sus implicaciones. Involucrar a la población en estas decisiones puede suponer incluso la participación activa y la movilización en las tareas de restauración, e incrementar, por otra parte, el grado de concienciación ambiental, lo que resulta primordial para reducir el riesgo de nuevos incendios provocados. En definitiva, existen razones de diversa índole para la retirada de la madera, pero igualmente existen razones ecológicas (e igualmente selvícolas) para mantener la madera quemada in situ. Esto ha llevado en la última década a una 37

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intensa y enriquecedora polémica en torno al manejo post-incendio de la madera quemada (e.g.: Beschta et al., 2004; Castro et al., 2009, 2010a, 2011; DellaSala et al., 2006; Donato et al., 2006; Lindenmayer et al., 2008; McIver y Starr, 2000), y cada vez son más numerosas las voces que abogan por un manejo que considere caso por caso con objeto de optimizar el potencial de regeneración natural de la masa y minimizar el impacto sobre el área que se pretende restaurar.

3. LA EXTRACCIÓN INTENSIVA DE LA MADERA COMO PERTURBACIÓN Y EL PAPEL DE LA MADERA QUEMADA COMO ELEMENTO ESTRUCTURAL Y FUNCIONAL DEL ECOSISTEMA

La extracción de la madera supone una perturbación adicional a la producida por el fuego, ya que implica un cambio sustancial en el paisaje, un manejo intenso sobre el área afectada y una retirada de nutrientes del sistema. Si bien, como se decía arriba, un incendio forestal es un proceso natural cuya perturbación no tiene necesariamente consecuencias ecológicas negativas o irreversibles (en una frecuencia e intensidad moderada o baja), la reincidencia de varias perturbaciones sobre una misma zona en un corto lapso de tiempo, como es el caso de la extracción intensiva de la madera tras un incendio, puede provocar un impacto sinérgico y magnificado (Lindenmayer et al., 2008; Lindenmayer y Ough, 2006). Este impacto sobre aspectos estructurales y funcionales clave del ecosistema puede exceder el grado de adaptación que muchas especies presentan a las perturbaciones que ocurren de manera natural (Paine et al., 1998), lo que puede mermar la capacidad de regeneración de las comunidades, con el potencial de provocar impactos negativos acumulados sobre los procesos ecosistémicos (Attiwil, 1994; Lindenmayer et al., 2008). La perturbación asociada a la saca de la madera puede incrementar la escorrentía y erosión del suelo (Bautista et al., 2004; Beschta et al., 2004; Fernández et al., 2007; Lindenmayer y Noss, 2006; McIver y Starr, 2000;

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Wondzell, 2001). Por otro lado, la utilización de maquinaria pesada puede incrementar la compactación del suelo, lo cual, unido al arrastre de los troncos que conllevan algunas técnicas de extracción de la madera, lleva a una reducción de la supervivencia de plántulas y rebrotes que a menudo se encuentran emergiendo al comienzo de los trabajos de extracción, afectando negativamente a la regeneración (DellaSala et al., 2006; Donato et al., 2006; Fernández et al., 2007; Greene et al., 2006; Lindenmayer et al., 2004; Lindenmayer y Ough, 2006; Martínez-Sánchez et al., 1999; McIver y Starr, 2000). Los estudios disponibles apuntan, además, a que la retirada de la madera puede tener un efecto negativo muy importante sobre la biodiversidad de la comunidad de plantas (Ne´eman et al., 1997; Stark et al., 2006), hongos e insectos (Grove y Meggs, 2003), otros invertebrados (Bros et al., 2011), vertebrados (Castro et al., 2010b; Harrington, 1996; Hutto, 2006; Lindenmayer y Ough, 2006; McCay y Komoroski, 2004), así como en los ecosistemas acuáticos y de ribera (Beschta et al., 2004; Karr et al., 2004). Dejar los restos de madera quemada puede tener también efectos positivos directos sobre la regeneración forestal. La presencia de ramas y troncos caídos o en pie reduce la radiación incidente, la temperatura del suelo y aumenta la humedad, lo que puede reducir el estrés hídrico y mejora el establecimiento de la vegetación en ecosistemas mediterráneos (Bautista et al., 2004; Castro et al., 2011). Además, los restos de ramas y troncos esparcidos por el suelo pueden suponer una defensa para plántulas y rebrotes contra la herbivoría por ungulados (Castro et al., 2010a; Ripple y Larsen, 2001; ver Harmon et al., 1986; Relva et al., 2009 para efecto similar de restos de ramas y troncos no quemados). Como resultado, en los últimos años se han incrementado las demandas para implementar actuaciones forestales postincendio de baja intensidad o ausencia de intervención, basadas en la evidencia de que los restos de madera quemada en descomposición son componentes naturales que promueven la recuperación de los ecosistemas (Beschta et al., 2004; DellaSala et al., 2006; Hutto, 2006; Lindenmayer et al., 2004).

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4. EFECTO DEL MANEJO DE LA MADERA QUEMADA SOBRE LOS CICLOS BIOGEOQUÍMICOS: ESTADO DE LA CUESTIÓN E HIPÓTESIS DE TRABAJO

A pesar de los numerosos estudios emergentes sobre el efecto contraproducente de la saca de la madera para la estructura y funcionamiento del ecosistema, el papel clave sobre los ciclos biogeoquímicos permanece aún poco estudiado. Esta tesis se centra en el efecto que la madera quemada puede tener en el ecosistema tras un incendio sobre los ciclos de carbono (C) y nutrientes, desde el punto de vista biogeoquímico, y sobre la regeneración, desde el punto de vista ecológico. Durante un incendio forestal se volatilizan grandes cantidades de carbono y nutrientes (Johnson et al., 2005; Neary et al., 1999; Trabaud, 1994; Wei et al. 1997), procedentes fundamentalmente de los restos vegetales de menor tamaño (hojas, hojarasca, corteza, ramas finas y parte exterior del tronco y de las ramas). Sin embargo, incluso tras incendios de alta intensidad, frecuentemente solo la corteza y partes externas del tronco se ven sustancialmente afectadas por el fuego, mientras que aproximadamente un 60% de los restos gruesos de madera previamente muerta y casi todos los troncos de los árboles superiores a 3 cm de diámetro permanecen sin ser quemados (Stocks et al., 2004). Esto se explica ya que las temperaturas que se alcanzan a unos pocos centímetros dentro de la matriz de la madera durante la onda de calor no son lo suficientemente elevadas como para producir la volatilización de sus componentes (Czimczik et al., 2002). De este modo, la mayor parte del material leñoso, que constituye un 75-90% de la biomasa aérea total del árbol (Merino et al., 2003, 2005; Ouro et al., 2001), permanece en el ecosistema (Johnson et al., 2005; Tinker y Knight, 2000; Wei et al., 1997) y, a pesar de la ausencia de datos en la literatura sobre las concentraciones de nutrientes en la madera de árboles quemados tras un incendio, cabría esperar por tanto que buena parte de su composición química permaneciese inalterada. La importancia de

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la madera muerta como reservorio y potencial fuente de nutrientes se ha puesto de manifiesto en diferentes estudios (e.g.: Clark et al., 2002; Harmon et al., 1986; Idol et al., 2001; Wilcke et al., 2005; Zimmerman et al., 1995), pero el reservorio de nutrientes existente en la madera quemada tras un incendio no ha sido evaluado hasta la fecha. Por tanto, nuestra hipótesis de partida se basa en que la madera quemada representa un reservorio de nutrientes de gran magnitud para el ecosistema, debido a la gran biomasa que aún persiste tras un incendio y a la relativamente elevada concentración de nutrientes que se prevé que aún contenga. La madera quemada, en el caso de no ser extraída, irá liberando el carbono y los nutrientes que contiene de forma progresiva a medida que se descompone. Las tasas de descomposición de la madera que yace sobre el suelo han sido ampliamente estudiadas en numerosos ecosistemas, así como la dinámica y liberación de nutrientes a lo largo de este proceso (Brown et al., 1996; Ganjegunte et al., 2004; Laiho y Prescott, 2004; Lambert et al., 1980; Palviainen et al., 2010a, b). No obstante, apenas existe información publicada al respecto para ecosistemas mediterráneos (Rock et al. 2008; pero ver Brown et al., 1996), y esta es también muy limitada para el caso de madera quemada (Grove et al., 2009; Shorohova et al., 2008; Wei et al., 1997). Con todo, cabe esperar que la tasa de descomposición de la madera quemada sea mayor en el caso de encontrarse en contacto con el suelo, dada la mayor retención de humedad y accesibilidad a ella de los descomponedores (Mackensen y Bauhus, 2003; Naesset, 1999; Rice et al., 1997). De la misma manera, los árboles quemados que quedan en pie tras un incendio también estarán sometidos a la descomposición más rápida de su base y sus raíces. Una vez que la resistencia de la madera no es suficiente para soportar el peso del árbol muerto, este caerá al suelo (Aakala et al., 2008; Harrington, 1996; Morrison y Raphael, 1993; Passovoy y Fulé, 2006; Vanderwell et al., 2006) y su descomposición se irá produciendo a una tasa comparable a las registradas para madera en contacto con el suelo. A pesar de todo, la información científica relativa

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a las tasas de caída de árboles muertos o calcinados por un incendio y los factores que las determinan es extremadamente escasa, y ausente para el caso de bosques mediterráneos. La liberación de nutrientes y materia orgánica por parte de la madera quemada puede contribuir a la fertilidad del suelo y a la mejora de la disponibilidad de nutrientes y de otros parámetros edáficos como el contenido en materia orgánica, la densidad aparente y la presencia y actividad de los microorganismos. Al igual que antes, algunos estudios abordan el papel de los restos gruesos de madera muerta sobre diferentes parámetros de calidad y fertilidad de los suelos en bosques maduros poco perturbados (Brais et al., 2005; Graham et al., 1994; Grove y Meggs, 2003; Hafner et al., 2005; Hafner y Groffman, 2005; Jurgensen et al., 1997; Kuehne et al., 2008), aunque esto no ha sido específicamente estudiado aún para el caso de la madera quemada en suelos afectados por un incendio. La extracción de la madera supone, sin embargo, una retirada adicional de nutrientes del ecosistema que se añade a la ya producida por el incendio (Brais et al., 2005; Johnson et al., 2005; Lindenmayer y Noss, 2006) con la consiguiente reducción de los potenciales aportes y de la capacidad de restitución de nutrientes al suelo a medida que la madera se descompone. Además, si los troncos y ramas quemados se dejan sobre el terreno, pueden frenar el arrastre y erosión del suelo que se produce sobre todo durante las primeras lluvias tras un incendio, contribuyendo con ello a minimizar la pérdida de nutrientes existentes en el suelo y en las cenizas depositadas (Fox, 2011; Kim et al., 2008; Shakesby et al., 1996; Thomas et al., 2000). A esto se une la mencionada mejora de las condiciones microclimáticas cuando el suelo se encuentra protegido por restos de madera quemada (Castro et al., 2011; ver Smaill et al., 2008; Stoddard et al., 2008 para madera no quemada). Todo esto también puede contribuir a acentuar el efecto cascada sobre la fertilidad del suelo, la actividad de los microorganismos descomponedores, las tasas de reciclaje de nutrientes y, en definitiva, en la 42

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disponibilidad de nutrientes para el conjunto de la comunidad (Brown et al., 2003; McIver y Starr, 2000). La recuperación de las funciones y procesos ecológicas del suelo por la presencia de la madera quemada puede tener importantes consecuencias para la regeneración de la vegetación tras el incendio, ya que la reducción de la sequía y el aporte de nutrientes (factores que con más frecuencia limitan el desarrollo de la vegetación en ecosistemas mediterráneos; Costa-Tenorio et al.,1998; Sardans et al., 2005) suelen traducirse en una mayor supervivencia, crecimiento y productividad (Castro et al., 2011; Jiménez et al., 2007; Querejeta et al., 2008; Matías et al., 2011; Mendoza et al., 2009; Siles et al., 2010; Trichet al., 2008). Por tanto, la mayor disponibilidad de nutrientes y mejores condiciones microclimáticas no sólo pueden llevar a un incremento en la capacidad de establecimiento de las plántulas (Castro et al., 2011; Fernández et al., 2008; Greene et al., 2006; Martínez-Sánchez et al., 1999; McIver y Starr, 2000, 2001), sino que también estas podrían desarrollarse mejor y tomar ventaja de las condiciones más favorables proporcionadas por la presencia de la madera quemada en años posteriores. A pesar del potencial efecto del manejo post-incendio de la madera quemada sobre el capacidad de regeneración de la vegetación (ya sea natural o repoblada), existen pocos trabajos que estudien este aspecto bajo condiciones experimentales controladas. Además, la mayor parte de estos estudios experimentales sólo tratan el efecto de los tratamientos más contrapuestos (la extracción intensiva de la madera frente a la ausencia de intervención; Martínez-Sánchez et al., 1999; Pérez y Moreno, 1998; Spanos et al., 2005), a pesar del gran abanico de posibilidades de manejo intermedio existentes. A raíz del incremento de la fertilidad, la actividad microbiana del suelo también podría verse incrementada, al disponer, como se hipotetiza, de mayor cantidad de nutrientes (Hamman et al., 2008; Mabuhay et al., 2006; Trumbore et al., 1996), sustratos orgánicos (Coleman et al., 2004; Franzluebbers et al., 2001) y 43

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humedad en el suelo (Almagro et al., 2009; Carlyle y Bathan, 1988; Davidson et al., 1998; Kirschbaum, 2000; Lloyd y Taylor, 1994) en presencia de madera quemada. Además, la mayor productividad de la vegetación y presencia de raíces contribuirá a un incremento de la actividad metabólica, ya sea a través de su propia respiración o mediante la liberación de exudados orgánicos utilizables por los microorganismos (Craine et al., 1998; Irvine et al., 2007; Janssens et al., 2001; Knapp et al., 1998; Litton et al., 2003; Mkhabela et al., 2009; Yanai et al., 2000). El resultado de esta actividad respiratoria puede ser inferido a través de los flujos de CO2 del suelo, que serán interpretados como un indicativo más de la calidad del suelo en respuesta al manejo forestal post-incendio de la madera (Staddon et al., 2009; Weber, 1990). Existen numerosos trabajos sobre el efecto del fuego sobre los flujos de CO2 del suelo (e.g.: Dore et al., 2010; Gough et al., 2007; Hamman et al., 2008; Hubbard et al., 2004; Kobziar, 2007; McCarthy and Brown, 2006; O’Neill et al., 2006; Yermakov y Rothstein, 2006). Sin embargo, a pesar de la importancia de conocer el efecto que las diferentes prácticas de manejo forestal post-incendio tienen sobre el balance del carbono, la literatura existente sobre la respiración del suelo en función del manejo de la madera quemada es muy escasa (ver Irvine et al., 2007; Mkhabela et al., 2009) y, en todo caso, el impacto de la extracción intensiva de la madera quemada en los flujos de CO2 del suelo aún no ha sido abordado. Por último, el manejo de la madera quemada no sólo puede afectar al reciclaje de nutrientes y a las tasas de actividad biológica, sino que también puede repercutir en el ciclo del carbono de forma decisiva. Como se ha mencionado, las emisiones de carbono del suelo pueden verse alteradas por el tratamiento de la madera aplicado tras el incendio. Además, la descomposición de la madera también contribuye al total de emisiones de CO2 que se producen en el ecosistema (Jomura et al. 2008; Progar et al., 2000). Sin embargo, esto no implica necesariamente que la madera quemada provoque un aumento neto de las emisiones de CO2 a la atmósfera a escala de ecosistema. De hecho, puesto que la presencia de la madera

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quemada puede fomentar la capacidad de regeneración y productividad de la vegetación (Castro et al., 2011; Donato et al., 2006; Martínez-Sánchez et al., 1999), la retención de carbono también puede verse incrementada. El balance entre las emisiones (fuentes) y el secuestro (sumideros) de carbono en el ecosistema como resultado del manejo forestal post-incendio tiene implicaciones globales de gran relevancia para las políticas dirigidas a la optimización del secuestro de carbono (Lindenmayer et al., 2008; Stark et al., 2006). A pesar de esto, no existen estudios hasta la fecha que evalúen el efecto del manejo post-incendio de la madera sobre el intercambio neto de carbono a nivel de ecosistema. La determinación del balance de carbono resultante de la extracción de la madera quemada frente a su persistencia cobra en esta tesis una dimensión global, ya que integra desde la perspectiva biogeoquímica los diferentes efectos que el manejo post-incendio de la madera puede tener sobre los diferentes componentes del ecosistema.

5. ÁREA DE ESTUDIO Y DISEÑO EXPERIMENTAL GENERAL Los estudios que se desarrollan en los sucesivos capítulos de la presente tesis fueron realizados en el Parque Natural y Nacional de Sierra Nevada, en un área afectada por un incendio ocurrido en Septiembre de 2005 (“incendio de Lanjarón”, UTM: 462673, 4094115). Dicho incendio afectó a 3.425 ha en total, de las cuales unas 1.300 ha aproximadamente eran bosques de pinos de reforestación de 35-50 años de edad, de manera que la madera de los árboles quedó carbonizada en los primeros centímetros de su superficie. En esta zona se seleccionaron cuatro parcelas localizadas a diferente altitud (Parcelas 1-4 en adelante, ver cuadro 1). Las especies de pino presentes en cada parcela son diferentes según su distribución altitudinal. El clima de la zona es Mediterráneo, con precipitaciones concentradas en primavera y otoño, alternando con veranos cálidos y secos. La precipitación media anual a 1465 m de altitud es de 470±50 mm, con una precipitación estival (Junio, Julio y Agosto conjuntamente) de 17±4 mm (datos climáticos procedentes 45

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de una estación meteorológica cercana a la zona de estudio, periodo 1988-2008). Hay nieve durante los meses más fríos de invierno, a menudo persistente desde Noviembre a Marzo a partir de los 2000 m de altitud. La temperatura media anual es de 12.3±0.4 ºC a 1652 m de altitud, mientras que la media de las temperaturas máximas es de 16.2±0.6 ºC y la media de las mínimas es de 7.6±0.5 ºC (Agencia Estatal de Meteorología, periodo 1994–2008). La temperatura media anual a 2300 m de altitud es de 7.8±0.7 ºC (dato procedente de un sensor instalado en una torre de flujo turbulento en la parcela 4, periodo 2008–10). La vegetación actual está compuesta mayoritariamente por herbáceas y arbustos con una cobertura de un 75% aprox. (Castro et al., 2010a). Todas las parcelas son homogéneas en cuanto a intensidad del fuego (alta intensidad), exposición (suroeste) y roca madre (micaesquistos) (Cuadro 1).

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Cuadro 1: Características principales de las parcelas de estudio.

PARCELA 1

Altitud1: 1.477 m Tipo de suelo2: Phaeozems háplicos, inclusiones de Cambisoles eútricos Pendiente: 25-30% Especie Forestal Dominante: Pinus pinaster Especies herbáceas y arbustos dominantes: Ulex parviflorus, Adenocarpus decorticans, Festuca scariosa, Dactylis glomerata, Euphorbia flavicoma Densidad de árboles previa al incendio: 1.480±50 Diámetro de los árboles a la altura del pecho: 13,3±0,2 cm Altura media de los árboles: 6,3±0,1 m

PARCELA 2

Altitud1: 1.698 m Tipo de suelo2: Phaeozems háplicos, inclusiones de Cambisoles eútricos y húmicos Pendiente: 25-35% Especie Forestal Dominante: Pinus nigra Especies herbáceas y arbustos dominantes: Ulex parviflorus, Adenocarpus decorticans, Festuca scariosa, Sangisorba minor, Euphorbia flavicoma Densidad de árboles previa al incendio: 1.060±70 Diámetro de los árboles a la altura del pecho: 14,5±0,2 cm Altura media de los árboles: 6,6±0,1 m

PARCELA 3

Altitud1: 2.053 m Tipo de suelo2: Phaeozems háplicos, inclusiones de Cambisoles eútricos y húmicos Pendiente: 35% Especie Forestal Dominante: Pinus sylvestris Especies herbáceas y arbustos dominantes: Vaccaria hispanica, Sesamoides prostrata, Senecio nebrodensis, Helianthemum apenninum Densidad de árboles previa al incendio: 1.050±40 Diámetro de los árboles a la altura del pecho: 10,8±0,2 cm Altura media de los árboles: 6,2±0,1 m

PARCELA 4

Altitud1: 2.317 m Tipo de suelo2: Cambisoles húmicos y Phaeozems háplicos Pendiente: 20% Especie Forestal Dominante: Pinus sylvestris Especies herbáceas y arbustos dominantes: Genista versicolor, Festuca spp., Sesamoides prostrata Densidad de árboles previa al incendio: 1.060±50 Diámetro de los árboles a la altura del pecho: 13,4±0,3 cm Altura media de los árboles: 6,6±0,2 m

1

Altitud medida en el centro de la parcela.2 Según Mapa de Suelos. Hoja Lanjarón 1:100.000. Proyecto LUCDEME. Ministerio de Agricultura Pesca y Alimentación. (1993)

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Entre Enero y Mayo de 2006, (4-8 meses después del incendio), se establecieron tres tratamientos de manejo post-incendio de los árboles quemados, en tres réplicas o subparcelas por cada tratamiento para las parcelas 1, 2 y 3 (3 réplicas x 3 tratamientos = 9 réplicas por parcela). Las réplicas, de al menos 2 ha de extensión cada una, se dispusieron contiguas entre sí, distribuidas de forma aleatoria dentro de cada parcela siguiendo un diseño de bloques (Fig. 1). En el caso de la parcela 4, no se subdividió en réplicas o subparcelas y cada tratamiento fue aplicado a un área de unas 35 ha aprox. (Fig. 1), debido a que en esta parcela fueron instaladas torres para la medida del flujo turbulento de CO2 mediante la técnica de eddy covarianza, para lo cual se requiere una mayor extensión con objeto de asegurar que los flujos medidos proceden del tratamiento en cuestión (“área fuente”) (Baldocchi, 2003; Schmid, 1994, 1997, 2002).

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Parcela 4 (2.317 m)

Parcela 3 (1.698 m) No Intervención (NI)

Intervención Intermedia (Ii)

Parcela 2 (2.053 m)

Parcela 1 (1.477 m)

NI

NI

Ii

E

NI

E

Ii

E

Ii

NI

Ii

NI

E

NI

E

Ii

E

Ii

NI

Ii

NI

E

E

Ii

E

Ii

NI

Ii

NI

E

Extracción (E)

Figura 1: Esquema del diseño experimental general utilizado en los diferentes estudios de la tesis y fotografías de diferentes tratamientos de la madera quemada aplicados. En el caso de la parcela 4, cada tratamiento fue aplicado a una sola área más extensa que en el resto de las parcelas, debido a que la medida del flujo turbulento de CO2 mediante la técnica de eddy covarianza realizada en esta parcela requiere una mayor extensión de cada tratamiento.

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Los tratamientos de la madera quemada que se aplicaron fueron: 1) “No Intervención” o “Non Intervention” (NI), en el que se dejaron en pie todos los árboles quemados (sin intervención) (Fig. 1). No obstante, los árboles se fueron cayendo de forma natural y progresiva a lo largo de los años, lo cual ha sido monitorizado como parte complementaria a los estudios de los que consta esta tesis. Así, ningún árbol se había caído aún en la zona de estudio tras el invierno de 2006-2007, un 13% de los árboles se cayeron tras el invierno de 2007-2008, un 83% se habían caído tras el invierno de 2008-2009 y un 98% tras el invierno de 2009-2010 (Fig. 2).

Figura 2: Porcentaje acumulado de árboles caídos a lo largo del tiempo. Los valores representan el promedio en las parcelas de estudio 1, 2 y 3. Por cada parcela y réplica fueron inicialmente marcados 100 árboles en los tratamientos NI e Ii (1.800 árboles en total), y fueron monitorizados en años sucesivos para determinar la tasa de caída.

2) “Intervención Intermedia” (Ii) ó “Cut plus Lopping” (CL), consistente en el corte y desramado de los árboles quemados, y el troceado de los troncos con una sierra mecánica con objeto de facilitar su contacto con el suelo. La biomasa dejada in situ con este tratamiento es igual a la del tratamiento “Control”, pero con las ramas y restos de madera cubriendo el 45% aprox. de la superficie del suelo (Castro et al., 2011) (Fig. 1). 3) “Extracción” (E) ó “Salvage Logging” (SL), en el que se talaron los árboles quemados, se desramaron, y el tronco se cortó en 2-3 trozas de unos 3 m que se apilaron en grupos de 10-12 para su posterior retirada con un autocargador. Las ramas finas y otros restos no aprovechables se trituraron con una desbrozadora

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de cadenas (Fig. 1). En las parcelas de más difícil acceso, la retirada de los troncos no fue posible, por lo que los troncos se dejaron apilados sobre el terreno. Este tratamiento es el más frecuentemente utilizado por la administración tras los incendios forestales y es, de hecho, el tratamiento que se aplicó al resto del área afectada por el incendio que rodea a cada una de las parcelas experimentales (Castro et al., 2010a). Los tratamientos se diferencian por tanto en su intensidad de manejo de la madera quemada, siendo por orden: E > Ii > NI.

6. OBJETIVOS Y ESTRUCTURA EN CAPÍTULOS Partiendo de las hipótesis mencionadas, esta tesis se enfocará de manera general en el análisis de los posibles efectos del manejo post-incendio de la madera sobre la dinámica de nutrientes y sus implicaciones sobre la regeneración y balance de C en el ecosistema. Este objetivo general supone el reto de abordar una cuestión de aplicabilidad directa para la gestión forestal recurriendo a diversas disciplinas tradicionalmente disociadas en la ciencia. De este modo, diversos aspectos químicos y edafológicos, fisiológicos, ecológicos y de física atmosférica serán estudiados y considerados de manera aplicada. Para ello, se han utilizado técnicas e instrumentación innovadoras como son el análisis de isótopos estables

13

Cy

15

N,

los sistemas de cámaras IRGA portátiles para la medida de flujos de CO2 del suelo o las torres de flujo turbulento para la medida de flujos netos de CO2 con la técnica “eddy-covarianza”. Finalmente, los resultados obtenidos se interpretan y discuten desde una perspectiva transversal para obtener un panorama global e integrador de la cuestión que se plantea. Con este objeto, la pregunta general será desgranada en diferentes objetivos que serán abordados, según su temática, en forma de capítulos (Fig. 3):

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Figura 3: Esquema conceptual simplificado de los posibles procesos entre los diferentes compartimentos y flujos del ciclo del C y nutrientes en el ecosistema afectados por la presencia de madera quemada tras el incendio. Los flujos de C se indican mediante flechas con llamada, los flujos de nutrientes se indican mediante flechas discontinuas. En cada uno de los capítulos de esta tesis (representados mediante rectángulos redondeados y sus etiquetas) se abordan uno o varios de los procesos considerados, y en el último capítulo se aborda el balance neto del C, lo que permite determinar el efecto global sobre el ecosistema.

El primer objetivo, abordado en el Capítulo 1 de esta tesis, será el de determinar el contenido o capital de nutrientes existente en la madera quemada que se deja en el ecosistema tras el incendio. Se valorará la utilidad potencial de la madera quemada como elemento natural para amortiguar las pérdidas de nutrientes. Esta potencialidad será función de la magnitud del reservorio de nutrientes en la madera en relación con el disponible en los primeros centímetros del suelo. En el Capítulo 2 se determinará el efecto que tiene la madera quemada sobre la fertilidad del suelo. Para ello se estudiará, por un lado, la tasa de liberación de nutrientes mayoritarios que experimenta la madera a medida que se

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descompone. Por otro lado, se analiza el efecto de la presencia de la madera sobre la disponibilidad de nutrientes en el suelo y otros parámetros edáficos. El efecto que ejerce el manejo de la madera quemada sobre el desarrollo de la vegetación a través de la modificación de la fertilidad y del microclima del suelo será objeto de estudio en el Capítulo 3. En concreto, se estudiarán diversos parámetros fisiológicos, fisiognómicos y bioquímicos que permitirán determinar aspectos relacionados con el estrés hídrico, el crecimiento y el estado nutritivo de plántulas de Pinus pinaster de regeneración natural tras el incendio. En el Capítulo 4 se aborda la modificación de las tasas respiratorias de los microorganismos y raíces del suelo en respuesta a la alteración de los parámetros edáficos y, de forma indirecta, de la vegetación. Para ello, se determinará el flujo de CO2 del suelo existente bajo distintos tratamientos de la madera quemada a diferentes escalas temporales (horaria y estacional) y mediante varias aproximaciones (medidas de campo en condiciones naturales y en condiciones controladas de humedad). Por último, en el Capítulo 5 se pretende determinar el balance del C en el ecosistema resultante de la modulación de las distintas componentes del ciclo del C por el manejo post-incendio de la madera. Con este fin, se comparan los flujos netos de CO2 a escala de ecosistema de los dos tratamientos más contrapuestos en cuanto al grado de manejo (E, con máxima intensidad de intervención versus NI, en ausencia de intervención). Las conclusiones que se extraigan de esta tesis permitirán poner de manifiesto la relevancia que el manejo de la madera quemada puede tener sobre el funcionamiento y dinámica del ecosistema desde el punto de vista biogeoquímico. Más aún, posibilitan vislumbrar las implicaciones a escala global que las estrategias de manejo post-incendio de los bosques mediterráneos pueden tener sobre las emisiones de C. Por todo ello, representan también una llamada de 53

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atención sobre la importancia de considerar el aspecto biogeoquímico para asegurar la estabilidad y sostenibilidad de los ecosistemas forestales. Los resultados de esta tesis podrán servir, por tanto, como instrumento de apoyo en la toma de decisiones para la gestión forestal post-incendio.

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CHAPTER 1: MACRO AND MICRONUTRIENT CONTENT IN BURNT WOOD AFTER A WILDFIRE IN A MEDITERRANEAN PINE FOREST

Sara Marañón-Jiménez, Emilia Fernández-Ondoño, Jorge Castro, Regino Zamora.

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________________________Macro- and micronutrient capital in burnt wood after a wildfire

ABSTRACT Even after a high-intensity wildfire, large amounts of logs and coarse woody debris remain in the ecosystem. In this study, we analyze the initial C and nutrient concentrations (N, P, Ca, Mg, K, Na, Fe, Mn, Zn, Cu) in burnt pine logs just after a wildfire in four sites along an altitudinal gradient, and the available nutrients in the upper 10 cm of soil in absence of woody residues two years after the fire. To evaluate its relative relevance, nutrient pools in the burnt wood are compared to those available in the soil. Overall, soil characteristics of the experimental sites were mainly driven by differences in pH and CIC, likely as a result of differences in mineralogy and microclimatic conditions of the sites. Soils were poorly developed and nutrients limiting for the vegetation requirements. Burnt wood still contained a relative high concentration of nutrients compared to those reported for unburnt, dead pine wood, and in general, decreased with altitude. In particular, Cu, Zn and Mn in burnt wood reflected the availability of these micronutrients in soil, as a response of their limitation. Burnt wood represented a considerable pool of nutrients, both due to the relatively high concentrations and to the great amount of biomass still present after the fire. Potential contributions of the burnt wood were particularly relevant for N, K and micronutrients Na, Mn, Fe, Zn, Cu, as they represented approx. a 93%, 62% and 72-87% respectively of the amount of nutrients existing in soil and wood pools. Burnt wood remaining after a wildfire therefore constitutes a valuable natural element as a reservoir and potential source of nutrients, which would be lost from ecosystems in the case of being removed. Keywords: Forest management, silvicultural treatments, woody debris, wildfire, wood nutrients, soil nutrients, Mediterranean mountain, post-fire salvage logging

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1. INTRODUCTION Wildfires exert a radical perturbation to the ecosystem nutrient cycle, leading to an immediate nutrient mobilization from organic pools (Page-Dumroese and Jurgensen, 2006; Trabaud, 1994; Whelan, 1995). Vegetation, litter and soil organic layers are susceptible to be consumed in greater or lesser degrees by fire, and their nutrients either released to the atmosphere as smoke or deposited to the soil as ash (DeBano and Conrand, 1978; Iglesias et al., 1997; Johnson et al., 2005; Neary et al., 1999; Raison, 1979; Yang et al., 2003). As a consequence, increases in soil nutrients can appear on the short term (Gray and Dighton, 2009; Johnson and Curtis, 2001; Marcos et al., 2009). Nonetheless, the nutrient enrichment is most often ephemeral, and does not usually persist more than several months after the fire (Certini, 2005; Iglesias et al., 1997; Wan et al., 2001; Yang et al., 2003), as deposited nutrients can be lost by leaching and erosion especially in steep areas or sandy soils (DeBano and Conrand, 1978; Fernández et al., 2007; Shakesby, 2011; Thomas et al., 1999). In addition, the loss of soil organic matter and disruption of organic cements in severe wildfires contribute to nutrient impoverishment by minimizing soil exchangeable capacity and stability (Certini, 2005; DeBano et al., 1998). Soil nutrient availability is however crucial for the recovery of vegetation after a wildfire. Furthermore, the existence of a nutrient reservoir in the ecosystem is key to ensure the sustainability of the plant community, especially during the first stages of succession (Augusto et al., 2000, 2008; Jurgensen et al., 1997; Merino et al., 2005, 2003). Coarse woody debris may have an important role in both biochemical cycling and ecosystem functioning. During growth, trees incorporate and accumulate nutrients from the soil in the proportions needed to constitute biomass, even where soils are poor (Chapin et al., 2002; Clarkson and Hanson, 1980; Ingestad, 1979). On the other hand, woody material usually represents the largest

74

________________________Macro- and micronutrient capital in burnt wood after a wildfire

proportion of biomass in the forest, although this varies according to the characteristics of the stand (tree density, forest species, climate, etc.). Overall, it is estimated that coarse woody tree fractions (stem wood excluding bark and thick branches) represent about 75-90% of the total aboveground biomass of a pine forests (Merino et al., 2003, 2005; Ouro et al., 2001). Moreover, this estimation ascends to about 95% of the total tree biomass if stumps and roots are also included (Alriksson and Eriksson, 1998; Rademacher, 2005), while the rest is accounted for by needles, thin branches, twigs, cones and stem bark. Therefore, although the nutrient concentrations in the woody tissues are usually the lowest compared to the rest of the tree fractions, they can contain a high proportion of the nutrients. As an example, the contents of nutrients in the woody fractions are estimated to represent ca. 25-60% of N, 50-70% of P, 65-75% of K, Mg and Zn, respectively, 75-80% of Ca, Mn and Cu, and 75-80% of Fe contained in the aboveground pine biomass (Alriksson and Eriksson, 1998; Merino et al., 2003, 2005; Ouro et al., 2001; Rademacher, 2005). Thus, woody tissues can store the largest amounts of nutrients in the tree, thus acting as an ecosystem sink and reservoir. Wildfires provoke a sudden mobilization and loss of nutrients from the system, although they are restricted mostly to the leaves and fine fractions of vegetation (Johnson et al., 2005; Trabaud, 1994). However, most of the nutrients contained in the large woody material (trunks and thick branches) and in the roots will likely remain in the ecosystem (Johnson et al., 2005; Tinker and Knight, 2000; Wei et al., 1997), as the temperatures reached inside the first centimeters of the matrix of coarse woody fractions during the heat wave are not high enough to volatilize its components (Czimczik et al., 2002). In fact, charring is usually limited to the bark or the outer superficial wood layer, and even after intense, stand-replacing crown fires, more than approx. 60% of the pre-existing coarse woody debris and almost all standing tree boles greater than 3 cm of diameter remain unburned (Stocks et al., 2004). The nutrients contained in the coarse burnt

75

Chapter 1_______________________________________________________________________

woody debris will be progressively released later during the decay process (Brown et al., 1996; Ganjegunte et al., 2004; Palviainen et al., 2010a, 2010b; Wei et al., 1997), allowing their retention by the soil and their availability for microorganisms and developing vegetation (Brais et al., 2005; Grove and Meggs, 2003; Jurgensen et al., 1997). Ecosystem nutrient losses associated with wildfires have been estimated in several studies (Brais et al., 2000; DeBano and Conrad, 1978; Johnson et al., 2005; Wan et al., 2001; Wei et al. 1997). In this respect, Wei et al. (1997) suggested that the nutrients (N and P) contained in pine unburnt stemwood are comparable to the nutrient losses associated with low severity wildfires. However, to our knowledge, there are no data about elemental concentrations in burnt wood to date, and what is more, the magnitude of the nutrient pools of burnt wood after a wildfire and their potential role in the ecosystem nutrient reserves has not been assessed yet. The estimation of the nutrient reservoir in the burnt wood is however a key first step to assess ecosystem sustainability towards its regeneration. In this work we intend to evaluate the nutrient concentration and reservoir in burnt wood after a standreplacing fire. We analyze the initial macro and micronutrient concentrations in burnt pine logs just after the wildfire, and the available nutrients in the soil where burnt wood is absent. This is done across an altitudinal gradient that varies in climatic conditions and pine species, with the potential to affect soil and wood nutritional status. Nutrients pools in the burnt wood are further estimated and compared to the nutrients in the soil pools to evaluate their relative relevance. The main objectives of this study are to: 1) determine the nutrient concentrations in the burnt wood left after a wildfire along the altitudinal gradient, and 2) assess the relative magnitude of the nutrient reservoir in the burnt wood in relation to the available nutrient stocks in the soil.

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________________________Macro- and micronutrient capital in burnt wood after a wildfire

2. MATERIAL AND METHODS

2.1. STUDY AREA The study site is located in the Sierra Nevada Natural and National Parks (SE Spain; UTM: 456070; 4089811), where in September 2005 the Lanjarón wildfire burned ca. 1,300 ha of reforested pine forest between 35 and 45 years old. The climate is Mediterranean, with rainfall concentrated in spring and autumn, alternating with hot, dry summers. Mean annual precipitation is 470±50 mm, with summer precipitation (June, July and August pooled) of 17±4 mm (1988-2008; climatic data from a meteorological station at 1465 m a.s.l.). Snow falls during winter, usually persisting from November to March above 2000 m a.s.l. The mean annual temperature is 12.3±0.4ºC at 1652 m a.s.l. (State Meteorological Agency, period 1994-2008. Ministry of Environment) and 7.8±0.7ºC at 2300 m a.s.l. (data from meteorological station, period 2008-10). The burnt pine stands occupy an altitudinal gradient from ca. 1300 to 2300 m a.s.l. Across this gradient, we established 4 study sites of ca. 3 ha (sites 1 to 4, respectively) that were similar in terms of fire intensity (high), situation (southwest exposure), bedrock (micaschists), tree density and tree size (Table 1). The dominant pine species at each site varied according to climatic conditions (Table 1). Between January and March 2006 (4-6 months after the wildfire), the Forest Service felled the trees with the use of manually operated chainsaws, the main branches were lopped off, and all wood was left in situ on the ground. Logs and branches diffusely covered approximately 45% of the surface at ground level (Castro et al., 2011). Post-fire vegetation was composed mainly of grasses and forbs with a cover of approximately 70% (Castro et al., 2010). Dominant species were Ulex parviflorus, Adenocarpus decorticans, Festuca scariosa, Dactylis glomerata and Euphorbia flavicoma in site 1; Ulex parviflorus, Adenocarpus

77

Chapter 1_______________________________________________________________________

decorticans, Festuca scariosa, Sangisorba minor and Euphorbia flavicoma in site 2; Vaccaria hispanica, Sesamoides prostrata, Senecio nebrodensis and Helianthemum apenninum in site 3; and Genista versicolor, Festuca spp., and Sesamoides prostrata in site 4. Table 1: Main pre-fire stand characteristics and dasometric variables of the trees in the study sites.

Element UTM position Altitude1 (m a.s.l.) Slope (%) Prefire dominant species: Tree density (invividuals ha-1) Diameter at 1.30 m (cm) Tree height (m)

Site 1

2

3

4

456070; 4089811

455449; 4091728

457244; 4091551

457719; 4091518

1477

1698

2053

2317

25-30% Pinus pinaster Aiton

25-35% Pinus nigra Arnold

35% Pinus sylvestris Linneo

20% Pinus sylvestris Linneo

1477±46

1064±67

1051±42

1058±52

13.3±0.2

14.5±0.2

10.7±0.2

13.4±0.3

6.3±0.1

6.6±0.1

6.2±0.1

6.6±0.2

1

Altitude in the centre of the delimited area of each site.

2.2. SOIL SAMPLING In June 2008 (2 years after the wildfire), 12 soil samples were collected from bare areas without woody debris at each site, characterizing soil conditions excluding the short term effects of ash deposition, once ash runoff and the lixiviation of its nutrients had occurred. For each soil sample, 3-4 soil pits were extracted using a gouge auger (2.5 cm diameter) to 10 cm depth, and homogenized to compound a single soil sample. Samples were immediately sieved at 2 mm and stored to 4ºC. Within 24 h of soil sampling, two subsamples of 15 and 7.5 g of soil were extracted for 1 h in agitation with 75 mL of 2M KCl and 0.5M NaHCO3, respectively, and filtered through a Whatman GF-D filter. Extracts were frozen at 20ºC until analyzed (Schinner et al., 1995). A 30 g subsample was oven-dried at 105ºC for 48 h for gravimetric determination of water content by the difference 78

________________________Macro- and micronutrient capital in burnt wood after a wildfire

between fresh and dry weight, and stored for further analyses. The bulk density of the upper 10 cm of the soil layer was calculated from the dry weight of the soil fraction <2 mm and the volume occupied by this fraction. For each soil pit, this volume was calculated as the difference between the volume of the gouge auger to a depth of 10 cm and the volume of the water displaced by the fraction >2 mm.

2.3. SOIL CHEMICAL ANALYSES From the dried subsample, soil organic matter (SOM) content was determined by incineration at 550ºC with a thermobalance (Leco TGA 701, St. Joseph, MI, USA) to constant weight (Sparks, 1996), whereas total C (Ctot) and N (Ntot) were determined by combustion at 850ºC (Leco TruSpec autoanalyzer). Total inorganic C (TIC) was measured by acidification with HClO4 in a coulometer (UIC CM-5014, Joliet, IL, USA). The TIC showed mere trace concentrations for these acidic soils (0.0034±0.0012% at site 1 and non detectible at sites 2, 3 and 4), so that Ctot can be considered as organic C. The soil pH was determined in 2008 samples by stirring and settling in distilled water with a pHmeter (Crison micropH-2001, Barcelona, Spain), according to the international standard ISO 10390 (1994) (Pansu and Gautheyrou, 2006). Ammonium (NH4+) and nitrate (NO3-) were determined from KCl extracts by the Kjeldahl method (Bremner and Keeney, 1965) with a Buchi distillation unit B-324 and a Metrohm SM Titrino 702 titrator. Inorganic P (Pinorg) was determined in NaHCO3 extracts by the Olsen method (Watanabe and Olsen, 1965) with a Perkin Elmer 2400 spectrophotometer (Waltham, MA, USA). Meso and micronutrients (Ca, Mg, K, Na, Fe, Mn, Zn and Cu) were determined by cation displacement with ammonium acetate and later analysis by atomic absorption with a Perkin Elmer 5100 spectrometer. The cation exchange capacity (CEC) was obtained after saturation of the soil exchange complex with Na+ cations by adding sodium acetate, and later determination of the

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Chapter 1_______________________________________________________________________

displaced Na+ cations with ammonium acetate by atomic absorption. The soil texture was determined by the standard pipette method after Robinson-Köhn or Andreasen (Pansu and Gautheyrou, 2006). Soil mineralogy was determined by Xray diffraction (XRD) after milling a soil subsample to powder (Whittig and Allardice, 1986) with an X-ray diffractometer (Bruker D8 Advance, Madrid, Spain). All nutrient fractions were referred to the corresponding dry weight of the soil.

2.4. WOOD SAMPLING During tree felling by the Forest Service (March 2006), discs of 6-8 cm thick were sawed (with a chainsaw) from 50 logs randomly chosen per site and taken to the laboratory. These discs are considered a representative sample of the initial characteristics of the burnt wood, since they were collected ca. 6 months (mostly winter) after the fire and showed no signs of decomposition. The disc diameter did not differ among sites and was 12.7±0.3 cm of average. The remaining bark was removed and wood discs were oven-dried at 70ºC to constant weight to determine the dry weight. Sawdust samples were taken from the whole section of the disc to maintain proportions of hardwood and softwood in the log, the composition being considered representative of the whole. For this, we used an adapted mechanical saw with no lubricant to avoid contamination. The extracted sawdust (<1 mm) from each disc was collected in paper envelopes and stored in a dry place for later chemical analysis.

80

________________________Macro- and micronutrient capital in burnt wood after a wildfire

2.5. WOOD CHEMICAL ANALYSES

The carbon and nitrogen concentrations of sawdust samples were determined using the combustion furnace technique at 850ºC (Leco TruSpec autoanalyzer), and phosphorus was analysed using the molybdovanadate method [Association of Official Analytical Chemists (AOAC), 1975]. Meso and micronutrients (Ca, Mg, K, Na, Fe, Mn, Zn and Cu) were determined by atomic absorption of the vegetal ash solution (Métodos Oficiales de Análisis de Plantas, 1981) with a Perkin Elmer 5100 spectrometer. The sawdust was dried at 105ºC by a thermogravimetric analyser (Leco TGA 701), and nutrient concentrations referred to the corresponding dry weight.

2.6. NUTRIENT POOLS ESTIMATION The biogeochemical relevance of the remaining burnt wood was assessed by comparing both the soil and wood pools of nutrients as a result of the wildfire. In order to estimate the nutrient content of the burnt wood, we calculated the dry wood biomass using specific equations developed by Montero et al. (2006) and implemented by the INIA in the calculation tool cubiFOR (CeseFor, url: http://cubifor.cesefor.com/). For each experimental site, the means of dasometric variables (tree density, d.b.h and tree height; table 1) were introduced to specific equations according to the dominant pine species. The fraction of needles and twigs <2 cm were not considered, since these fractions were consumed during the wildfire. The resultant values of biomass per area allowed the estimation of the nutrient content per area of the wood pool for each site. The nutrient content in the upper 10 cm soil layer was calculated using the nutrient concentrations in the soil and the bulk density for each site (Table 2). The N in the soil pool was referred to the extractable inorganic fraction (NH4+ + NO3-), 81

Chapter 1_______________________________________________________________________

since it is broadly accepted that this is the most relevant direct N source for plant nutrition in most of the cases (Killham, 1994), whereas direct evidence that organic N contributes significantly to plant N nutrition is still lacking (Näsholm et al., 2009).

2.7. DATA ANALYSIS The differences in nutrient concentrations in wood and soil were analyzed with one-way analysis of variances (ANOVAs), with site as the independent factor. The comparison of mean nutrient concentrations between sites was further analyzed with Tukey HSD post-hoc tests. Differences in textures and mineralogy between sites were similarly analyzed using a non-parametric Kruskal-Wallis test, and, in cases of significant differences, Nemenyi post-hoc tests of multiple comparisons of means among sites were performed. Additionally, correlations between all nutrients were explored separately for the wood and for the soil using Pearson correlations. The correlation between the mean concentration per site of each nutrient in the soil and in the wood was also explored by the same method. A principal component analysis (PCA) was also performed for nutrients in wood and soil. For this, a correlation matrix with standardization of variables was used. Further, differences between experimental sites according to the first component scores obtained in the PCA were tested with a one-way ANOVA and Tukey HSD post-hoc tests (Jolliffe, 2002; Quinn and Keough, 2009). Data were log- or square-root-transformed when required to improve normality and homocedasticity (Quinn and Keough, 2009). Statistical analyses and models were made with JMP 7.0 software (SAS Institute). In the results that follow, mean values are followed by ±1SE.

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________________________Macro- and micronutrient capital in burnt wood after a wildfire

3. RESULTS:

3.1. SOIL PARAMETERS AND NUTRIENT CONCENTRATIONS Experimental sites had lower pH values with increasing altitude, whereas SOM and CEC were the highest at the most elevated site (Table 2). Soil nutrient concentrations differed significantly between experimental sites in the case of Ctot, Ntot, Pinorg, Ca, Mg and Mn (Table 3). Ctot and Ntot showed the same pattern as SOM, being highest at the most elevated site, with the same tendency for NO3(Tables 2 and 3). The C/N ratio in soil was higher in sites 1 and 2 and lowest in site 3 (Table 3). Most of the N in the soil was organic and only ca. 0.54% was inorganic. The extractable Pinorg was lower in site 2 and higher in site 4 (Table 3). The exchangeable Ca and Mg had similar patterns between experimental sites, being higher in sites 1 and 2 (Table 3). Despite the absence of significant differences, Fe, Cu and Zn tended to be lowest at the most elevated site. Mn had an opposite pattern, increasing with the elevation (Table 3).

83

Chapter 1_______________________________________________________________________ Table 2: Main soil parameters of the study sites. Values represent means ± standard errors. CEC: cationic exchange capacity; SOM: soil organic matter; ρ: bulk density. Different letters above means indicate significant differences among sites (Tukey post-hoc test or after one-ways ANOVAs or Nemenyi test after Kruskal-Wallis tests). F / H: Value of the statistics, P: Critical probability.

Site

Soil Parameter 1

Soil type

ρ (g cm-3) Texture (%) Sand Coarse loam Fine loam

2.15

0.1006

69.1±0.7

8.44

0.0378

b

8.44

0.0378

13.6±0.5

8.95

0.0300

8.74

0.0329

Humic cambisols and haplic phaeozems

1.25±0.06 Sandy loam

Sandy loam

Sandy loam

Sandy loam

59.4±2.4

58.9±3.2

69.0±0.1

a

a,b

a,b

10.6±0.8

11.9±0.7

15.2±0.7

Clay

P

3 Haplic phaeozems, with eutric and humic cambisols 1.15±0.06

Haplic phaeozems, with eutric cambisols

1

F/H

2 Haplic phaeozems, with eutric and humic cambisols 1.34±0.07

14.8±0.9

9.7±0.4

16.7±1.3

a

12.5±1.5

8.8±0.3

1.18±0.04

7.3±0.2

12.5±0.4

a,b

4

b

10.0±0.3

a,b

Mineralogy (%) Quartz

17±3

20±3

17±2

19±2

1.31

0.7273

Clinoclore

4±0.2

3±1

16±3

19±2

8.43

0.0378

Muscovite

51±2

43±4

44±2

50±1

4.53

0.2089

b

9.15

0.0273

a,b

Paragonite

15±1

SOM (%) -1

CEC (cmol+ kg )

12±2

a

13±2

pH

a,b

18±2

a,b

Albite

1

a

15±2

7.270±0.040

a

3.339±0.186

a

5.592±0.256

a

7±1

a,b

b

10±1

7.282±0.049

a

3.317±0.180

a

5.313±0.306

a

6.713±0.084

5±0.5 b

3.573±0.179

a

4.633±0.313

a

8.08

0.0444

c

83.66

≤0.0001

6.037±0.174

b

48.79

≤0.0001

8.191±0.272

b

29.71

≤0.0001

5.581±0.101

Soil types according to the soil map Lanjarón 1:100.000 LUCDEME Project, Ministry of Agriculture, Fisheries and Foods (1993).

84

______________________________________________________________ Macro- and micronutrient capital in burnt wood after a wildfire Table 3: Soil nutrient concentrations in the four study sites. Values represent means±standard errors. V: Percentage of bases saturation; Ctot and Ntot: soil C and N referred to total concentrations, respectively. Different letters above means indicate significant differences among sites (Tukey post-hoc test after one-ways ANOVAs). F: Value of the statistic, P: Critical probability.

Soil Variable

F

P

2.981±0.088b

44.632

≤0.0001

c

1

2

3

4

Ctot (%)

1.047±0.115a

1.168±0.105a

1.304±0.130a

Ntot (%)

a

a

b

C/N

0.062±0.007

0.068±0.006

a

a

16.36±0.72

17.42±0.68

0.094±0.006 13.32±0.68

b

0.204±0.006 14,65±0.68

73.488

≤0.0001

a,b

6.774

0.0004

+

1

2.516±0.801

3.101±0.822

3.664±0.852

2.621±0.880

0.392

0.7591

-

1

0.809±0.243

1.170±0.352

1.471±0.279

2.138±0.439

2.695

0.0521

0.626±0.182

0.804±0.249

0.540±0.122

0.233±0.061

2.117

0.1054

10.123 9.130

≤0.0001 ≤0.0001

0.720±0.064b

20.970

≤0.0001

NH4 (ppm) NO3 (ppm)

Ninorg/Ntot (%) Pinog (ppm)

1

4.960±1,253 -1 2

Ca (cmol+ kg )

-1 2

Mg (cmol+ kg ) -1 2

K (cmol+ kg )

Na(cmol+ kg-1) 2 V (%)

a,b

3.238±0.244

a

1.311±0.067

a

1.874±0.149

c

3.144±0.231

a

1.044±0.064

a

2.645±0.383

b,c

1.705±0.231

b

0.653±0.064

b

5.396±0.589 2.399±0.231

a

a,b

0.0188±0.0016

0.0219±0.0015

0.0184±0.0015

0.0226±0.0015

2.051

0.1141

0.00213±0.00071

0.00217±0.00067

0.00116±0.00067

0.00168±0.00067

0.490

0.6900

81.811±5.398

a

a

b

b

82.596±5.121

55.622±5.121

38.886±5.121

16.932

≤0.0001

0.059±0.029

0.089±0.034

0.091±0.034

0.025±0.015

1.181

0.3227

a

0.356±0.052

a

b

6.254

0.0008

Zn (ppm)

2

0.026±0.010

0.025±0.008

0.032±0.009

0.009±0.005

1.461

0.2321

Cu (ppm)

2

0.015±0.007

0.017±0.008

0.014±0.007

0.005±0.005

0.552

0.6484

Fe (ppm)

2

Mn (ppm)

1

Site

2

0.369±0.080

0.651±0.088

a,b

0.953±0.167

Extractable concentrations; 2 exchangeable concentrations.

85

Chapter 1_______________________________________________________________________

The pH, SOM, CEC, Ctot and Ntot, Pinorg and Mn were strongly correlated (Appendix A). For the pH, these correlations are negative (R2>0.35, P<0.001 in all cases, Appendix A). Ca, Mg and pH presented also very high correlations, although for these nutrients the relationship with pH was positive (R2>0.40, P<0.001 in all cases, Appendix A). Also meaningful are the correlations between NO3- and NH4+ (R2=0.75, P<0.0001), Fe and Cu (R2=0.59, P<0.0001), and between K and Ctot or Pinorg (R2>0.39, P<0.001 in all cases, Appendix A). The study sites can be differentiated by their soil nutrients and edaphic parameters according to the principal components obtained in the PCA (Fig.1B and D). The first and second principal components explain a 30.9% and 16.9% of the total variance (Fig. 1A and B). The concentrations of N, C, SOM and pH contributed more to the first component, whereas Ca and Mg were the variables that contributed more to the second component (Fig. 1A). According to the first component, the site 4 had the highest scores, followed by the site 3, and then sites 1 and 2, without significant differences between these latter two (P<0.0001; one-way ANOVA; Fig. 1B).

3.2. WOOD NUTRIENT CONCENTRATIONS All nutrient concentrations in wood differed between sites, except Zn and C (Table 4). N was more concentrated in sites 2 and 3, so that the ratio C/N in the wood was lower in these sites (Table 4). The concentrations of P, Ca and Mg resulted the lowest in site 4. The patterns of K, Na and Fe were similar, becoming also lower as altitude increased (Table 4). However, the Mn concentration had again the opposite pattern, increasing at higher elevations (Table 4). Cu was lower in sites 1 and 4, and highest in site 2 (Table 4).

86

________________________ Macro- and micronutrient capital in burnt wood after a wildfire Table 4: Nutrient concentrations in the burnt wood in the four study sites. Values represent means ± standard errors. Different letters above means indicate significant differences among sites (Tukey post-hoc test after one-ways ANOVAs). F: Value of the statistic, P: Critical probability.

Wood Nutrient

Site 1

2

F 3

P

4

C (%)

50.49±0.08

50.60±0.08

50.63±0.07

50.37±0.07

2.456

0.0645

N (%)

0.163±0.004a

0.187±0.006b

0.189±0.005b

0.155±0.005a

11.841

≤0.0001

C/N

320.45±8.75ª

284.77±10.29b

278.65±9.29b

342.8±12.99a

10.029

≤0.0001

14.019

≤0.0001

25.946

≤0.0001

10.114

≤0.0001

13.36

≤0.0001

54.678

≤0.0001

19.672

≤0.0001

3.9120

0.0097

N/P P (ppm) Ca (ppm) Mg (ppm) K (ppm) Na (ppm) Fe (ppm)

18.90±1.58

a

99.74±5.17

a

20.04±1.33

105.42±5.82 a

622.48±43.54

a

264.56±11.57 575.00±36.75

a,b

a

a

69.39±4.58

12.562±2.035 a

91.49±3.55

28.89±1.60

a

58.74±2.48

627.32±35.37

438.16±19.61

a

b

264.98±10.12

a

a

233.69±9.49

b

504.31±27.15

359.33±18.47

a,b

b,c

7.816±1.263ª

,b

a

Mn (ppm)

29.79±2

30.00±1.58

4.629±0.519

4.618±0.496

Cu (ppm)

a

b

1.556±0.094

b

a

Zn (ppm)

1.167±0.071

22.54±1.42

c

a

710.05±48.27

50.83±2.46 a

a

b

40.32±2.56

7.136±1.212 43.39±2.36

a,b

b

5.302±0.562 1.353±0.086

a,b

b

186.98±9.47

c

203.19±13.51 31.03±2.38

c

4.853±1.025 67.04±3.25

b

c

43.646

≤0.0001

3.870±0.515

0.517

0.6711

a

5.670

0.001

1.145±0.072

Strong correlations were found between the N, P and the majoritycomponents of the burnt wood Ca, Mg and K being positive in all cases (Appendix B). These were especially important between K and P, Na or Mg (R2=0.75, 0.59 and 0.54 respectively, P<0.0001 in all cases) and between P and Na (R2=0.51, P<0.0001, Appendix B). High positive correlations were also found between Mg and Ca, Na or P (R2>0.36, P<0.0001), and between Fe and Cu or Zn (R2>0.33, P<0.0001). Additionally, Mn was inversely correlated to K (R2=0.39, P<0.0001, Appendix B). The study sites were also different according to the principal components of the wood composition, although in this case the sites can not be distinguished as clearly as according to their soil nutrients. The first and second principal components obtained in the PCA explained the 29.6% and 16.1% of the total

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variance, respectively (Fig. 1C and D). K, P and Mg contributed more to the first component and Zn, C and N to the second (Fig. 1C). According to the first component, the site 4 had the lowest scores, followed by site 3 and then sites 1 and 2 (one-way ANOVA; P<0.0001; Fig. 1D).

6

Component 2 (16.9%)

Mg 0.5

0.0

Cu

4 K

Fe

Mn

Na pH

P Zn

C SOM N

-0.3

B

5

NH4+ NO3-

-0.5

Component 2 (16.9%)

0.8

0.3

A

Ca

3 2 1 0 -1 -2 -3 -4

-0.8

-5

Site 1 2 3 4

-6 -0.8 -0.5 -0.3 0.0 0.3 0.5 Component 1 (30.9%)

0.8

-6 -5 -4 -3 -2 -1 0 1 2 3 Component 1 (30.9%)

4

5

6

6

C

0.8

4

0.3

Mn

C Cu Fe N Ca

0.0

Mg P

-0.3

K

Na -0.5

Component 2 (16.1%)

Component 2 (16.1%)

Zn 0.5

D

5 3 2 1 0 -1 -2 -3 -4

-0.8

-5 -6 -0.8 -0.5 -0.3 0.0 0.3 0.5 Component 1 (29.6%)

0.8

-6 -5 -4 -3 -2 -1 0 1 2 3 Component 1 (29.6%)

4

5

6

Figure 1: Principal component analysis (PCA) of soil nutrient concentrations (A and B), and wood nutrient concentrations (C and D) in the four different study sites. For an easier visualization, only the two first principal components are represented. The percentage of contribution to the total variability is between parentheses. A and C refer to the relative contribution of each individual variable to the first two principal components, B and D refer to the value assigned to each wood sample according to these two components.

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________________________ Macro- and micronutrient capital in burnt wood after a wildfire

In addition, correlations between the concentration of each nutrient obtained in the soil and in the wood were significant in the case of the Mn (R2=0.98, P=0.0078) and the Zn (R2=0.77, P=0.0787).

4. DISCUSSION: The results of this study highlight the potential of burnt wood as a nutrient source for natural forest regeneration. Two years after the wildfire, soils in the study area showed very low nutrient availability, although they varied among the study sites likely due to differences of mineralogy and microclimate. On the other hand, the relative potential contributions of the wood pool were very relevant, due to the low soil nutrient availability, the concentrations of these elements still present in the wood after the fire, and the high biomass of burnt wood still present. Moreover, the relative relevance of the burnt wood as a reservoir of nutrients for the ecosystem was quite consistent across study sites, regardless of the differences in soil and wood nutrient concentrations, soil characteristics and wood biomass remaining after the wildfire. 4.1. SOIL NUTRIENT CONCENTRATIONS Overall, soil nutrient concentrations in this study were lower than those reported for other soils in the area (Sánchez-Marañón et al., 1996) and in other Mediterranean pine forests (Blanco et al., 2008; De Marco et al., 2005; Fierro et al., 2007; Yilziz et al. 2010). This is likely due to the combination of the young and poorly developed soils, especially at the highest elevations (Sánchez-Marañón et al., 1996); the nutrient losses associated to the organic layer combustion by the wildfire (Certini, 2005; DeBano and Conrand, 1978; Raison, 1979); and the high slopes, which increase ash runoff and erosion (Fernández et al., 2007; Shakesby,

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2011; Thomas et al., 1999). It is also worth mentioning the recurrent history of degradative land use (deforestation for agricultural uses, consequent nutrient depletion and vulnerability to soil erosion and further soil perturbation for reforestation; Padilla et al., 2010). The pre-fire existence of a pine forest with a litter input of high C/N ratio and difficult mineralization could also have contributed to soil acidification and low nutrient availability (Moro and Domingo, 2000; Oyonarte et al., 2008; van Wesemael, 1993), particularly in the case of the inorganic forms of N for plant assimilation. The low pool of nutrients found in the soil are insufficient to meet the annual requirements of available inorganic N (ca. 40 kg ha-1year-1), K (ca. 25 kg ha-1year-1), Zn (ca. 0.14 kg ha-1year-1), Fe (ca. 0.18 kg ha-1year-1), and to a lesser degree, of P (ca. 4 kg ha-1year-1) and Mn (ca. 0.85 kg ha-1year-1) of a mature coniferous forest (Cole and Rapp, 1981; Helmisaari, 1995; Johnson and Lindberg, 1992; Merino et al., 2005; Miller, 1986). However, despite their low concentrations in this siliceous soil, Ca and Mg were not limiting. Among sites, available or changeable soil nutrients were modulated by differences in pH and SOM, as a result of the different lithology and microclimate, and to a lesser degree by weathering of the parent material and soil development. As altitude increase, temperatures are lower and the lithology becomes more acidic. These factors explain the lower pH found at highest altitudes and the highest SOM, provided the slower mineralization and prevalence of humification processes (Bohn et al., 1993; Silver, 1998). The higher SOM determined, in turn, a higher CEC, total C and N at the highest site. Furthermore, the Ninorg/Ntotal ratio was also consistent with the greater predominance of humification. The pattern of available Pinorg was determined by the CEC and presence of Ca, Mg and Fe in soil, which can form insoluble phosphates and lead to their precipitation (Porta et al., 2003). Similarly, the contrasting effects of the decrease in pH and the highest CEC at the most elevated site explain the decreasing pattern of the base saturation with altitude (Porta et al. 2003). By contrast, the acidity increases the Mn solubility and

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________________________ Macro- and micronutrient capital in burnt wood after a wildfire

availability (Godo and Reisenauer, 1980), and reinforces the retention of NO3anions by the protoned surfaces of colloids (Ashman and Puri, 2002). In addition, the tendencies of lower Cu, Fe and Zn availability at the highest site are likely due to lesser release from a not very weathered parent material. The young nature of these soils is in fact evidenced by the greater presence of easily weatherable clorite minerals at this site (Thompson and Troeh, 2005).

4.2. WOOD NUTRIENT CONCENTRATIONS The essential nutrients found in burnt stemwood are within the range of the concentrations reported in other studies for unburnt pine wood for most of the nutrients analized. Nonetheless, the mean concentrations of N in pine wood found in this study (0.17%, all sites pooled) exceed the range of values reported in the literature for the same species (0.05-0.15%). The P concentrations here averaged 89.2 ppm versus the values of 45-180 ppm in other studies. Similarly, Ca, Mg and K averaged here 605.47 ppm, 238.35 ppm and 413.36 ppm, respectively, versus the ranges of 500-1100 ppm, 100-300 ppm and 250-1000 ppm found for the same elements in the literature (Alriksson and Eriksson, 1998; Augusto et al., 2008; Merino et al., 2005; Palviainen et al., 2010a, 2010b). This suggests that nutrient losses suffered by the large wood fractions were not relevant, since the effects of fire are usually limited to the bark and small fractions of the tree, even in intense stand-replacing fires (Stocks et al., 2004; Wei et al., 1997). However, the concentrations of Fe, Mn, Zn, Cu and Na were very low compared to those found in unburnt wood (Alriksson and Eriksson, 1998; Harju et al., 1997; Merino et al., 2005; Saarela et al., 2002). This could be likely due to their limited availability in soil (see above). This is also supported by the similar patterns of Mn, Zn and Cu both in the burnt wood and in the soil across sites, and by the correlations found between the concentrations in wood and soil in the case

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of Mn and Zn. The same thing occurred between the N in wood and NH4+ in soil, suggesting a limitation of a source of available N in the soil. Thus, nutrients in wood tended to reflect their availability in the soil, being therefore lower at the most elevated sites, although others factors like the differences in composition among the dominant pine species could be also influencing (Alriksson and Eriksson, 1998; Augusto et al., 2008, 2000; Baumann et al. 2006).

4.3. RELATIVE MAGNITUDE OF THE NUTRIENT RESERVOIR IN BURNT WOOD During a high-intensity wildfire, nutrients contained in fine nutrient-rich vegetal fractions, such as leaves and twigs, are mostly volatilized (Johnson et al., 2005; Trabaud, 1994). However, our results show that a relatively high nutrient concentration was still present in burnt wood and that great amounts of biomass remained after the wildfire, both over and underground. Therefore, the magnitude of the nutrient pools in the remaining burnt wood was very relevant from a biochemical perspective. As an example, the N and P reservoirs represented by burnt wood (75.3 kg ha-1 and 3.9 kg ha-1, Fig. 2) would be comparable to the inputs of atmospheric deposition for this area during 12 and 20 years, respectively (6.3 kg ha-1year

-1

of N and 0.2 kg ha-1year

-1

of P; Morales-Baquero et al., 2006).

Similarly, the N in the wood pool would be the equivalent to the estimated N input by fixation of ca. 1800 Adenocarpus decorticans per ha in a similar Mediterranean ecosystem during at least 75 years (1 kg ha-1year

-1

of N; Moro et al., 1996).

Moreover, the magnitude of the nutrient reservoir in wood is likely even greater than that estimated, as the nutrient concentrations of roots (34% of the total biomass) and branches (11%) are usually higher than those of stemwood (Alriksson and Eriksson, 1998, Montero et al., 1999).

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________________________ Macro- and micronutrient capital in burnt wood after a wildfire

Figure 2: Nutrient reservoir in the burnt wood and soil pools. A. Nutrient content in the burnt wood left after the wildfire and in the upper 10 cm soil layer. B. Nutrient percentage relative to the total content in the wood and soil pools. Nitrogen in the soil pool is referred to the extractable inorganic fraction (NH4+ + NO3-). Roots and bark are included in the biomass estimations, but needles and branches <2 cm were excluded due to their total combustion during the fire. Values of nutrient content are the mean of the four experimental sites, standard errors are represented above each bar. Note in A the different scale of each graph and the breaks in Ca for better visualization.

The relative contribution of the burnt wood in relation to the soil pool was especially high in the case of N, K, Na, Mn, Fe, Zn and Cu. The burnt wood will therefore be especially suitable, helping to satisfy the requirements of these nutrients that were found insufficient in the soil. Moreover, the important contribution of micronutrients in burnt wood represents a sign of their suitable potential as a nutrient reservoir. Trees incorporate and concentrate these micronutrients in their biomass although they were very limited in the soil (Chapin et al., 2002; Clarkson and Hanson, 1980; Ingestad, 1979). As a result, a much

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greater total amount of these nutrients was contained in wood than in the first 10 cm of soil. In addition, overall the relative contributions of burnt wood remained quite constant among study sites and was independent of the different microclimate, mineralogy, pre-fire dominant species and wood biomass inventory. Nonetheless, we are aware of possible underestimation of the soil nutrients pools, since it is referred to the upper 10 cm soil layer. However, limiting nutrients for plants are mostly concentrated in the upper mineral layers (Jobbágy and Jackson, 2001), so the relative contributions of each pool are not expected to vary substantially. Summarizing, the results show that the remains of burnt wood biomass act as a relevant nutrient reservoir that help to regulate nutrient availability and ameliorate the nutrient losses associated with the wildfire.

4.4. MANAGEMENT IMPLICATIONS The prior forest conditions (tree density, tree diameter and age class, degree of management, nutritional status, etc.), fire intensity and the post-fire intervention will radically determine the magnitudes of nutrient pools in the burnt wood after a wildfire. In spite of that, the appropriate management of burnt trees after forest fires remains controversial (Beschta et al., 2004; Donato et al., 2006; Lindenmayer et al., 2004, 2008; McIver and Starr, 2001). Results in this study can assist to implement post-fire measures designed to ensure the regeneration and natural sustainability of the ecosystem. Salvage logging (felling and removing burnt trunks, often combined with the elimination of the remaining woody debris; Beschta et al., 2004; McIver and Starr, 2001) is a widely applied management practise in forest ecosystems all over the world. However, it implies the retrieval of the nutrient pool contained in burnt wood that could otherwise be reincorporated to the ecosystem biogeochemical cycle. Moreover, post-fire salvage logging represents in these cases an additional perturbation beyond the wildfire, usually

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________________________ Macro- and micronutrient capital in burnt wood after a wildfire

exceeding the resilience and adaptation capacity of the ecosystem (Lindenmayer et al., 2008; Paine et al 1998). For this reason, the biochemical impacts of salvage logging should be also added to the considerations to be evaluated during the decision-making regarding the most suitable post-fire forest management strategy.

5. ACKNOWLEDGEMENTS: We wish to thank Ramón Ruíz Puche and Enrique P. Sánchez-Cañete for their hard work in the field, Gustavo Román Reche for his assistance in processing the wood samples, Susana Hitos for her invaluable help and advice in the laboratory analyses, Francisco Martín Peinado for his help and collaboration with the soil texture and mineralogical analyses, and Ivan Janssens for his inestimably useful comments. The Consejería de Medio Ambiente (Junta de Andalucía) and the Parque Nacional y Natural de Sierra Nevada offered support in establishing the treatments. This work was financed by the by the projects (SUM2006-00010-0000) of the INIA, (10/2005) of the Organismo Autónomo de Parques Nacionales (MMA), GESBOME (P06-RNM-1890) of the Junta de Andalucía, COILEX (CGL2008-01671) of the MICINN, Subprogram for Technical Support (PTA20091782-I) of the MICINN, and by a grant FPU-MEC to S.M.J.

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Porta, J., López-Acevedo, M., Roquero, C., 2003. Edafología para la Agricultura y el Medio Ambiente, (3rd edn.) Mundiprensa, Madrid. Quinn, G.P., Keough, M.J., 2009. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge. Rademacher, P., 2005. Contents of nutrient elements in tree components of economical important species in relation to their residual utilisation. European Journal of Wood and Wood Products 63, 285-296. Raison, R.J., 1979. Modification of the soil environment by vegetation fires, with particular reference to nitrogen transformations - review. Plant and Soil 51, 73108. Saarela, K.E., Harju, L., Lill, J.O., Rajander, J., Lindroos, A., Heselius, S.J., Saari, K., 2002. Thick-target PIXE analysis of trace elements in wood incoming to a pulp mill. Holzforschung 56, 380-387. Sánchez-Marañón, M., Delgado, R., Párraga, J., Delgado, G., 1996. Multivariate analysis in the quantitative evaluation of soils for reforestation in the Sierra Nevada (southern Spain). Geoderma 69, 233-248. Schinner, F., Öhlinger, R., Kandeler, E., Margesin, R., 1995. Methods in Soil Biology. Springer, Berlin. Shakesby, R.A., 2011. Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth-Science Reviews 105, 71-100. Silver, W.L., 1998. The potential effects of elevated CO2 and climate change on tropical forest soils and biochemical cycling. Climatic Change 39, 337-361. Sparks, D.L., 1996. Methods of Soil Analysis. Part 3. Chemical Methods. Soil Science Society of America and American Society of Agronomy, Madison, WI. Stocks, B.J., Alexander, M.E., Wotton, B.M., Stefner, C.N., Flannigan, M.D., Taylor, S.W., Lavoie, N., Mason, J.A., Hartley, G.R., Maffey, M.E., Dalrymple, G.N., Blake, T.W., Cruz, M.G., Lanoville, R.A., 2004. Crown fire behaviour in a northern jack pine-black spruce forest. Canadian Journal of Forest Research-Revue Canadienne de Recherche Forestiere 34, 1548-1560. Thomas, A.D., Walsh, R.P.D., Shakesby, R.A., 1999. Nutrient losses in eroded sediment after fire in eucalyptus and pine forests in the wet Mediterranean environment of northern Portugal. Catena 36, 283-302. Thompson, L.M., Troeh, F.R., 2005. Soils and Soil Fertility, (6th Edn.). Blackwell Publishing, Oxford. Tinker, D.B., Knight, D.H., 2000. Coarse woody debris following fire and logging in wyoming lodgepole pine forests. Ecosystems 3, 472-483.

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Trabaud, L., 1994. The effect of fire on nutrient losses and cycling in a Quercus coccifera garrigue (southern France). Oecologia 99, 379-386. van Wesemael, B., 1993. Litter decomposition and nutrient distribution in humus profiles in some Mediterranean forests in Southern Tuscany. Forest Ecology and Management 57, 99-114. Wan, S.Q., Hui, D.F., Luo, Y.Q., 2001. Fire effects on nitrogen pools and dynamics in terrestrial ecosystems: A meta-analysis. Ecological Applications 11, 1349-1365. Watanabe, S., Olsen, R.S., 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 extracts from soil. Soil Science Society of America Journal, 29, 677–678. Wei, X., Kimmins, J.P., Peel, K., Steen, O., 1997. Mass and nutrients in woody debris in harvested and wildfire-killed lodgepole pine forests in the central interior of British Columbia. Canadian Journal of Forest Research-Revue Canadienne de Recherche Forestiere 27, 148-155. Whelan, R.J., 1995. The Ecology of Fire. Cambridge studies in Ecology. Cambridge University Press. Cambridge. Whittig, L.D., Allardice, W.R., 1986. X-ray diffraction techniques. In: A. Klute (Ed.) Methods of Soil Analysis. Part 1. (2nd edn.) Agronomy Monographs 9. ASA and SSSA, Madison, WI, pp. 331–362. Yang, Y.S., Guo, J.F., Chen, G.S., He, Z.M., Xie, J.S., 2003. Effect of slash burning on nutrient removal and soil fertility in Chinese fir and evergreen broadleaved forests of mid-subtropical China. Pedosphere 13, 87-96. Yildiz, O., Esen, D., Sarginci, M., Toprak, B., 2010. Effects of forest fire on soil nutrients in Turkish pine (Pinus brutia, Ten.) Ecosystems. Journal of Environmental Biology 31, 11-13.

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APPENDIX A: Table A1: Pearson correlations between each pair of soil variables. Values indicate the coefficients of each correlation. Data of all sites are pooled. Variable pH SOM CEC Ctot Ntot NH4+ NO3Pinorg Ca Mg K Na Fe Mn Zn Cu

pH 1 -0.67*** -0.46*** -0.70*** -0.78*** 0.05 -0.23* -0.35** 0.41*** 0.57*** -0.05 0.12 0.20 -0.37*** 0.14 0.11

SOM

CEC

Ctot

Ntot

NH4+

NO3-

Pinorg

Ca

Mg

K

Na

Fe

Mn

Zn

1 0.81*** 1 0.94*** 0.78*** 1 0.90*** 0.69*** 0.93*** 1 0.03 -0.01 0.01 -0.02 1 0.33** 0.23* 0.29** 0.27* 0.75*** 1 0.55*** 0.60*** 0.62*** 0.55*** -0.05 0.13 1 0.11 0.19 0.05 -0.13 -0.09 -0.08 0.06 1 -0.09 0.10 -0.18 -0.33** 0.02 -0.09 -0.01 0.78*** 1 0.31** 0.25* 0.39*** 0.34** -0.02 0.01 0.40*** 0.35** 0.25* 1 -0.04 -0.04 -0.10 -0.07 -0.09 -0.18 -0.10 0.24* 0.19 0.18 1 -0.09 -0.13 -0.07 -0.15 0.03 -0.03 -0.11 0.30** 0.14 -0.10 0.04 1 0.45*** 0.35** 0.51*** 0.46*** -0.11 -0.10 0.44*** 0.11 -0.10 0.34** 0.10 0.18 1 -0.25* -0.14 -0.23* -0.23* -0.22* -0.20 -0.15 -0.01 -0.03 -0.11 -0.12 0.24* 0.05 1 0.01 0.06 0.04 -0.07 -0.20 -0.17 0.01 0.26* 0.21 -0.01 -0.10 0.59*** 0.29* 0.35**

Cu

1

Critical probabilities of the correlations (P) are indicated: *0.01
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APPENDIX B:

Table B1: Pearson correlations between each pair of wood nutrients. Values indicate the coefficients of each correlation. Data of all sites are pooled. Variable C N P Ca 1 C 0.26*** 1 N -0.07 0.29*** 1 P 0.15* 0.25*** 0.28*** 1 Ca 0.11 0.27*** 0.43*** 0.41*** Mg 0.02 0.26*** 0.75*** 0.22** K -0.01 0.08 0.51*** -0.06 Na 0.22** 0.06 0.19** 0.17* Fe -0.01 0.13 -0.23** -0.25*** Mn 0.13 0.22** 0.03 0.01 Zn 0.24** 0.22** 0.33*** 0.20** Cu

Mg

K

Na

Fe

Mn

Zn

1 0.54*** 1 0.36*** 0.59*** 1 0.28*** 0.26*** 0.24*** 1 -0.23** -0.39*** -0.13 0.04 1 0.02 0.02 -0.04 0.33*** 0.18* 1 0.23** 0.18* 0.13 0.36*** 0.06 0.18*

Cu

1

Critical probabilities of the correlations (P) are indicated: *0.01
104

CHAPTER 2: EFFECT OF DECOMPOSING BURNT WOOD ON SOIL FERTILITY AND NUTRIENT AVAILABILITY IN A MEDITERRANEAN ECOSYSTEM

Sara Marañón-Jiménez and Jorge Castro

Under review

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______________________________________Burnt wood increases soil fertility after wildfires

ABSTRACT Burnt wood can represent a valuable nutrient reservoir for a regenerating ecosystem, helping to prevent the soil fertility losses after a wildfire. However, there is scarce information on its effect on soil nutrient cycling and availability. We established three study sites along an altitudinal gradient in a burnt pine forest (SE Spain). At each site we determined: 1) decomposition rates and nutrient dynamics in burnt logs left on the ground, 2 and 4 years after the fire, and 2) available nutrients in the soil and in the microbial fraction below burnt logs and in bare soil areas. Despite the relatively slow decay rates in this Mediterranean climate (ca. 10% of dry weight lost after four years), N and P were progressively released by logs, accounting for ca. 40% and 65% of the initial content respectively after 4 years. The presence of burnt logs consistently increased soil organic matter by around 18%, total C and N by 42% and 26%, respectively, dissolved organic C and N by 47%, inorganic P by 68%, and microbial biomass and nitrogen by 36% and 48%, respectively. By contrast, soil bulk density decreased by ca. 18% under logs compared to bare areas. Thus, the burnt wood was a useful natural element in the recovery of soil fertility and nutrient availability. Therefore, leaving the burnt wood onsite can enhance biogeochemical sustainability, microbiological processes and soil ecological functioning. The detrimental effect of post-fire salvage logging on soil fertility should therefore be considered when making management decisions.

Keywords Carbon sequestration, salvage logging, silvicultural treatments, wildfire, wood decay, wood nutrient release.

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1. INTRODUCTION

Wildfires constitute a radical perturbation for the nutrient cycle of an ecosystem, leading to an immediate nutrient mobilization from organic pools (Page-Dumroese and Jurgensen, 2006; Trabaud, 1994; Whelan, 1995). Vegetation, litter, and the soil organic layer are consumed to greater or lesser degrees by fire, and their nutrients are either released to the atmosphere in smoke or deposited on the soil as ash (DeBano and Conrand, 1978; Iglesias et al., 1997; Johnson et al., 2005; Neary et al., 1999; Raison, 1979; Yang et al., 2003). Consequently, increases in soil nutrients can appear over the short term (Gray and Dighton, 2009; Johnson and Curtis, 2001; Marcos et al., 2009). Nonetheless, nutrient enrichment is most often ephemeral, and does not usually persist more than several months after the fire (Certini et al., 2005; Iglesias et al., 1997; Wan et al., 2001; Yang et al., 2003), as deposited nutrients can be lost by leaching and erosion especially in steep areas or sandy soils (DeBano and Conrand, 1978; Fernández et al., 2007; Shakesby, 2011; Thomas et al., 1999). In addition, the loss of soil organic matter and disruption of organic cements in severe wildfires contribute to nutrient impoverishment by minimizing soil exchangeable capacity and stability (Certini et al., 2005; DeBano et al., 1998). Soil nutrient availability is, however, crucial for the recovery of vegetation after a wildfire. Furthermore, the existence of a nutrient reservoir in the ecosystem is key to ensure the sustainability of the plant community, especially during the first stages of succession (Augusto et al., 2000, 2008; Jurgensen et al., 1997; Merino et al., 2005, 2003). Dead wood progressively releases nutrients through decomposition (Brown et al., 1996; Ganjegunte et al., 2004; Palviainen et al., 2010a, 2010b; Wei et al., 1997) at rates that depend on climatic conditions, species, and substrate (Harmon et al., 1986; Zhou et al., 2007). The nutrients released could be retained by the soil, becoming available for microorganisms and developing vegetation (Brais et al.,

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2005; Grove, 2003; Jurgensen et al., 1997). The effect of decomposing wood on soil would also vary according to soil properties and nutrient status (Klinka et al., 1995; Thiffault et al., 2006). In particular, nutrient storage and contributions of dead wood are especially important in Mediterranean pine forests, which are frequently located in poor soils and yet with great nutrient demands (Costa-Tenorio et al., 1998; Sardans et al., 1995). Coarse woody debris has also been considered an important structural and functional element for many forest ecosystems (Harmon et al., 1986; Lambert et al., 1980; Spies et al., 1988) and has been defined as “hot spots” that foment spatial heterogeneity (Hafner et al., 2005; Hafner and Groffman, 2005) and wildlife diversity (Castro et al., 2010a; Hutto, 2006; Lindenmayer and Noss, 2006). Woody material also has been reported to encourage microbial diversity and the abundance of ectomycorrhizal fungi, which are used as primary indicators of a healthy forest soil (Graham et al., 1994). Moreover, the organic substrates and nutrients contained in wood promote the activity of decomposer microorganisms (Marañón-Jiménez et al., 2011), with the consequent enhancement of nutrient cycling. In addition, logs and other woody debris can mitigate erosion (Fox, 2011; Kim et al., 2008; Shakesby et al., 1996; Thomas et al., 2000), which is the main cause of nutrient loss in rain events following intense wildfires (Fernández et al., 2007; Thomas et al., 1999). Since dead wood and coarse woody debris have been demonstrated to represent a major nutrient pool in living forests (e.g. Alriksson and Eriksson, 1998; Clark et al., 2002; Ganjegunte et al., 2004; Idol et al., 2001; Merino et al., 2003), different degrees of forest management (e.g. clear cutting, logging, etc.) can strongly affect the ecosystem nutrient budget (Augusto et al., 2000, 2008; Johnson et al., 2005; Merino et al., 2005). Nutrient losses associated with wildfires depend mainly on the type of vegetation and fire intensity (Brais et al., 2000; Neary et al., 1999; Page-Dumroese and Jurgensen, 2006). However, wildfires usually remove the nutrient-rich crown material and understory, as well as the organic layer from

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the forest floor, but most of the large woody material remains in the ecosystem (Johnson et al., 2005; Tinker and Knight, 2000; Wei et al., 1997). Thus, a great amount of dead biomass can persist in standing burnt trees even after an intense wildfire, and can represent a potential nutrient reservoir for the regeneration of the ecosystem (Harmon et al., 1986; Page-Dumroese and Jurgensen, 2006; Zhou et al., 2007). In fact, burnt logs after a forest fire may still have a high nutrient concentration (Wei et al., 1997), since charring is usually limited to the bark or the outer superficial wood layer (Stocks et al., 2004). Thus, the nutrient pool in burnt logs might be comparable to that reported for unburnt dead wood. Despite the potential relevance of this nutrient source via burnt wood decay, information regarding the decomposition and nutrient dynamics of coarse woody debris in Mediterranean areas is completely lacking (Rock et al., 2008; but see Brown et al., 1996), and is also very limited in the case of burnt wood (Grove et al., 2009; Shorohova et al., 2008; Wei et al., 1997). Moreover, the effect of burnt wood on soil nutrient availability after a wildfire has not been specifically studied. In this study, we seek to analyse the role of burnt wood on the soil nutrient availability and pools in a Mediterranean pine forest after a wildfire. We investigate nutrient release by wood during decomposition and its effect on soil fertility. This was done across an altitudinal gradient that varies in climatic conditions and pine species, with the potential to affect the decay rates and the nutrient dynamics between burnt wood and soil. We hypothesise that the presence of burnt wood over the forest floor will increase soil nutrient availability as the wood decomposes. Similarly, we predict that the presence of microorganisms will be also higher in the presence of burnt wood. As a result, the burnt wood would enhance soil fertility and nutrient mobilization in the ecosystem. Thus, the main objectives of this study are to: 1) estimate the rate of nutrient release by burnt pine wood during the first four years of decomposition in a Mediterranean mountain ecosystem across an altitudinal gradient; 2) assess the effect that burnt wood left

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over the ground exerts on the soil nutrient concentrations and pools; and 3) determine its effect on the microbial biomass and nutrients, as well as on the distribution of nutrients among the soil and microbial pools. The final goal is to help clarify the potential effect of burnt wood on soil fertility and nutrient cycling.

2. MATERIAL AND METHODS 2.1. STUDY AREA AND EXPERIMENTAL DESIGN The study site is located in the Sierra Nevada Natural and National Parks (SE Spain; UTM: 456070; 4089811), where in September 2005 the Lanjarón wildfire burned ca. 1,300 ha of reforested pine forest between 35 and 45 years old. The climate is Mediterranean, with rainfall concentrated in spring and autumn, alternating with hot, dry summers. Mean annual precipitation is 470±50 mm, with summer precipitation (June, July and August pooled) of 17±4 mm (1988-2008; climatic data from a meteorological station at 1465 m a.s.l.). Snow falls during winter, usually persisting from November to March above 2000 m a.s.l. The mean annual temperature is 12.3±0.4ºC at 1652 m a.s.l. (State Meteorological Agency, period 1994-2008. Ministry of Environment) and 7.8±0.7ºC at 2300 m a.s.l. (data from meteorological station, period 2008-10). Current vegetation is composed mainly of grass and forbs with a cover of approximately 70% (Castro et al., 2010b). The burnt pine stands occupy an altitudinal gradient from ca. 1300 to 2000 m a.s.l. Across this gradient, we established 3 study sites of ca. 3 ha each located at 1477, 1698, and 2053 m a.s.l. (sites 1 to 3, respectively). The sites were homogeneous in terms of fire intensity (high), slope (25 to 35%), situation (southwest exposure), bedrock (micaschists) and soil characteristics (Table 1). The dominant pine species at each site changed according to climatic conditions, with

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Pinus pinaster Aiton. at site 1, P. nigra Arnold. at site 2, and P. sylvestris L. at site 3. Burnt tree density was 1200±40 individuals per hectare. Basal tree diameter ranged from 15.7±0.1 at site 3 to 18.3±0.1 at site 2 (Castro et al., 2010b).

Table 1 Main soil characteristics of the upper 10 cm soil layer in bare areas without burnt wood. The bulk density refers to the soil fraction <2 mm. The soil texture was determined by the standard pipette method after Robinson-Köhn or Andreasen (Pansu and Gautheyrou, 2006). The cation exchange capacity (CEC) of the soil was determined by saturation with Na+ cations and their displacement and by atomic absorption. (Pansu and Gautheyrou, 2006)

Site

Soil Parameter Bulk density (g cm-3) Soil texture

1

2

3

1.25±0.06

1.34±0.07

1.15±0.06

Sandy loam

Sandy loam

Sandy loam

Sand (%)

59.4±2.4

Coarse loam (%)

10.6±0.8

11.9±0.7

9.7±0.4

Fine loam (%)

15.2±0.7

16.7±1.3

12.5±0.4

Clay (%)

14.8±0.9

12.5±1.5

8.8±0.3

CEC (cmolc kg-1 suelo)

5.6±0.3

5.3±0.3

4.6±0.3

58.9±3.2

69.0±0.1

Between January and March 2006 (4-6 months after the wildfire), the Forest Service felled the trees with the use of manually operated chainsaws, the main branches were lopped off, and all wood was left in situ on the ground. Logs and branches diffusely covered approximately 45% of the surface at ground level (Castro et al., 2011). Afterwards (March 2006), at each site, we randomly established 50 sampling points where we placed logs to monitor wood decomposition and nutrient dynamics. Each sampling point contained 5 logs, cut by a chainsaw to a standardized length of 75 cm and spread over an area ca. 1x1 m (thus 250 logs per site; “experimental logs”, hereafter). Each experimental log at a

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sampling point came from a different tree and from a randomized location along the tree trunk. Thus, they constitute a representative sample of the log characteristics in the study sites in terms of diameter and sectional origin along the trunk.

2.2. WOOD SAMPLING 2.2.1. INITIAL WOOD NUTRIENTS AND DRY WEIGHT During the tree felling by the Forest Service (March 2006), a disc of 6-8 cm thick was sawed (with a chainsaw) from 50 logs randomly chosen per site and taken to the laboratory. These discs (“initial discs”, hereafter) are considered a representative sample of the initial characteristics of the burnt wood, since they were collected ca. 6 months (mostly winter) after the fire and showed no signs of decomposition. The remaining bark was removed and initial wood discs were oven dried at 70ºC to constant weight to determine the dry weight. Once they were dried, the disc dimensions were measured and the volume of each initial disc was calculated. The average disc diameter at each site ranged from 12.1 to 13.3 cm (Appendix A). A sample of sawdust (<1 mm) was extracted from each initial disc for chemical analysis. Sawdust samples were taken from the whole section of the disc to maintain proportions of hardwood and softwood in the log, the composition being considered representative of the whole. For this, we used an adapted mechanical saw with no lubricant to avoid contamination. All this allowed us to estimate the initial dry weight and nutrient content of subsequent decayed wood discs by means of a regression equation established with the morphometric variables of the initial wood discs (Appendix A).

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2.2.2. DECOMPOSITION AND TIME COURSES OF NUTRIENTS IN WOOD

A random subsample of 20 of the initially tagged experimental logs was harvested from each site (one per sampling point) after 2 years (June 2008) and 4 years (June 2010). Discs of 6-8 cm thick were taken from the longitudinal middle of each experimental log to standardize the possible effect of the distance to the log ends on decomposition and nutrient concentrations. Repeated sampling of discs from the same logs taken in 2006 was not possible, due to the need to standardize the possible effect of the distance to the log ends. Following the same procedure as with the initial discs in 2006, the remaining bark of the wood discs was removed and their dry weight and volume was determined. The diameter of the sampled discs in 2008 and 2010 fell within the range of initial discs (Appendix A). As before, a sample of sawdust (<1 mm) was also taken from each wood disc for chemical analysis. 2.3. SOIL SAMPLING We sampled soils associated with the logs sampled in 2008 and 2010. Two soil samples were collected per sampling point: one from soil under the harvested log and another from a nearby area of bare soil (no woody debris) (n=20 sampling points x 2 positions x 3 sites x 2 years=240 soil samples in total). For each soil sample, 3-4 soil pits were extracted using a gouge auger (2.5 cm diameter) to 10 cm depth, and homogenised to compound a single soil sample. Samples were immediately sieved at 2 mm and stored to 4ºC. Within 24 h of soil sampling, three subsamples of 15, 15, and 7.5 g of soil were extracted for 1 h in agitation with 75 mL of 2M KCl, 0.5M K2SO4, and 0.5M NaHCO3, respectively, and filtered through a Whatman GF-D filter. A 30 g subsample was oven dried at 105ºC for 48 h for gravimetric determination of water content by the difference between fresh and dry weight, and stored for further analyses. Another subsample was fumigated 114

______________________________________Burnt wood increases soil fertility after wildfires

with CHCl3 for 24 h in vacuum to release the nutrients from the microbial biomass (fumigation-extraction method; Jenkinson and Powlson, 1976), after which the soil was extracted with 0.5M K2SO4 and 0.5M NaHCO3 and filtered as above. Fumigated and nonfumigated extracts were frozen at -20ºC until analysed (Schinner et al., 1995). In 2010, the bulk density of the upper 10 cm of the soil layer was calculated from the dry weight of the soil fraction <2 mm and the volume occupied by this fraction. For each soil pit, this volume was calculated as the difference between the volume of the gouge auger to a depth of 10 cm and the volume of the water displaced by the fraction >2 mm. 2.4. CHEMICAL ANALYSES Carbon and nitrogen concentrations of the sawdust samples were determined using the combustion furnace technique at 850ºC (Leco TruSpec autoanalyzer, St. Joseph, MI, USA), and phosphorus was analysed using the molybdovanadate method [Association of Official Analytical Chemists (AOAC), 1975] with a Perkin Elmer 2400 spectrophotometer (Waltham, MA, USA). The sawdust was dried at 105ºC by a thermogravimetric analyser (Leco TGA 701), and nutrient concentrations referred to the corresponding dry weight. From the dried subsample, soil organic matter (SOM) content was determined by incineration at 550ºC with a thermobalance (Leco TGA 701) to constant weight (Sparks, 1996), whereas total C (Ctot) and N (Ntot) were determined by combustion at 850ºC (Leco TruSpec autoanalyzer). Total inorganic C (TIC) was measured by acidification with HClO4 in a coulometer (UIC CM5014, Joliet, IL, USA). The TIC showed mere trace concentrations for these acidic soils (0.0034±0.0012% at site 1 and non detectible at sites 2 and 3), so that Ctot can be considered as organic C. The soil pH was determined in 2008 samples by stirring and settling in distilled water with a pHmeter (Crison micropH-2001,

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Barcelona, Spain), according to the international standard ISO 10390 (1994) (Pansu and Gautheyrou, 2006). Ammonium (NH4+) and nitrate (NO3-) were determined from KCl extracts by the Kjeldahl method (Bremner and Keeney, 1965) with a Buchi distillation unit B-324 and a Metrohm SM Titrino 702 titrator. From K2SO4 extracts (fumigated and nonfumigated), we determined the dissolved organic C (DOC) and dissolved organic N (DON) with a Shimadzu TOC-V CSH analyser (Kyoto, Japan). Microbial C and N (Cmicro and Nmicro, respectively) were determined from the differences in DOC and DON between fumigated and nonfumigated subsamples. Inorganic P (Pinorg) was determined in nonfumigated NaHCO3 extracts by the Olsen method (Watanabe and Olsen 1965). Microbial P (Pmicro) was measured as the difference in P between the fumigated and nonfumigated extracts. Concentration values in the microbial fraction were corrected for extraction efficiency using Kec values of 0.45, 0.40 and 0.40 for Cmicro, Nmicro and Pmicro, respectively (Sparling and West, 1988). All nutrient fractions were referred to the corresponding dry weight of the soil.

2.5. DATA ANALYSIS The percentage of the initial wood weight remaining in the field following the decay process was calculated using the weight of each wood disc in 2008 and 2010 and the estimation of the initial weight for each disc (Appendix A). No relationship was found between diameter and initial wood density. Thus, the initial dry weight of the discs depended only on their volume. Furthermore, the initial disc weight better fit the volume of the disc using a linear regression model with no intercept, so this model was used to estimate the initial dry weight of the wood discs collected in 2008 and 2010 (Appendix A). The fragmentation of logs has a delay time of at least 25 years (Harmon, 1986), so external changes in log volume (bark fragmentation was not considered in this study) was deemed negligible at

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these initial stages of decay. Thus, the volume of each disc (Vd) sampled after 2 (2008) and 4 years (2010) was used to estimate the initial dry weight from the regression equations. Differences in wood weight between sites over time could not be analysed with a repeated measures ANOVA, since wood discs could not be sampled following a repeated sampling procedure for methodological reasons (see experimental design). Thus, the sampling year was considered as an independent factor in the statistical analyses. The diameter of the log (and hence size) may influence the decomposition both directly and indirectly (Grove et al., 2009; Mackensen and Bauhus, 2003; Shorohova et al., 2008). For this, the effect of decomposition time on the percentage of initial wood weight remaining was analysed at each site using an ANCOVA, with year as the independent factor and the diameter of each wood disc as a covariate. The initial sampling year (2006) was not considered in the analyses of the percentage of weight loss, since it was considered to be initially zero. For each wood disc, the estimated proportion of the initial dry weight remaining and nutrient concentration over the study period were used to calculate the nutrient content per kg of remaining wood over time. Similarly as before, changes in nutrient concentrations, C/N ratio and nutrient content over time were analysed for each site with ANCOVAs, with year as the independent factor and the diameter as a covariate. For C content, we used a generalized linear model with normal distribution and logarithmic link function. The effects of year, site, and position (under logs or in bare areas) on soil nutrient and microbial fractions were analysed with factorial ANOVAs when the transformed data satisfied linearity assumptions. For variables that did not fulfil linearity assumptions, we used generalized linear models (GLMs) with a normal distribution and logarithmic link function (Pmicro, NH4+, NO3-, Cmicro, Nmicro, C/Nmicro). Pools per square meter of soil under logs and in bare areas were calculated for the soil sampling of 2010 from the bulk density of each soil sample 117

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and its corresponding nutrient and microbial fractions. Then, the effect of site and position on the soil nutrient pool was similarly analysed with two ways factorial ANOVAs or GLMs. Data were transformed when required to improve normality and homoscedasticity (Quinn and Keough, 2009). Statistical analyses were made with JMP 7.0 software (SAS Institute). Throughout the paper, mean values are followed by ±1SE.

3. RESULTS 3.1. INITIAL WOOD NUTRIENTS AND DRY WEIGHT Initial wood density varied among sites, being 0.73±0.27 g cm-3 at site 1, 0.70±0.32 at site 2, and 0.68±0.40 at site 3 (Appendix A). The initial N concentration in wood was also different among sites (P=0.0004, one way ANOVA), being lower at site 1 (0.163±0.004%) than at sites 2 and 3 (0.187± 0.005% and 0.189±0.005%, respectively). The mean initial P wood concentration was 99.7±2.8 mg kg-1 (all sites pooled) and did not differ among sites (P=0.2011, one way ANOVA).

3.2. DECOMPOSITION AND TIME COURSES OF NUTRIENTS IN WOOD

The estimated percentage of the initial wood weight decreased mostly during the first two years of decay (Fig. 1), but not from the second to fourth year of decay (P>0.05 at all study sites, one way ANCOVAs; Fig. 1). The percentage of wood weight lost overall was 9% after two years and 10% after four years (cumulative values, Fig.1). This pattern did not differ among sites (Fig. 1) and the

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diameter had a significant effect only on dry weight losses at site 2 (F=4.54, P=0.0420, one way ANCOVA; negative correlation).

Figure 1: Time course of the wood dry weight remaining after four years of decomposition under field conditions. Dry weight is expressed as percentage of the initial dry weight of the wood discs. Initial dry weight was estimated with regression equations constructed with the volume and dry weight of initial discs collected in 2006.

The composition of burnt wood varied over time at all study sites for all elements analysed (Table 2). Overall, the wood N and P concentrations and content decreased as wood decayed (Fig. 2). In the case of N, concentrations changed slightly during the first two years of decay, but then sharply fell within four years (ca. 35% of the initial concentration, Fig. 2A). Nonetheless, net N losses were detected even after the first two years of decay when expressed as N content per mass unit of remaining wood, reaching ca. 10% and 40% of the of the initial N content lost after two and four years, respectively (Fig. 2D). The decrease in the P concentration and content was evident from the beginning of decay, with losses of ca. 40% and 65% of the initial content within two and four years, respectively 119

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(Figs. 2B and E). By contrast, the C concentration increased sharply within four years, despite an initial decrease during the first two years (Fig. 2C). The C content of the remaining wood, however, showed the same pattern as the estimated wood weight remaining, with significant C losses only during the first two years (Table 2, Fig. 2F). As a result, the wood C/N ratio increased very slightly or did not vary significantly in the first period but rose sharply afterwards (Table 2, Fig. 3). The diameter of the log also affected the wood N and C contents or concentrations, but had overall a weak effect compared to year (Table 2).

Figure 2: Time courses of the nutrient and carbon concentrations and contents in the burnt wood. Panels A, B, and C refer to the nutrient and carbon concentrations; and panels D, E, and F refer to nutrient and carbon content per kg of burnt wood remaining. Nutrient content was calculated for each wood disc with the proportion of the initial dry weight remaining and its nutrient concentrations.

120

______________________________________Burnt wood increases soil fertility after wildfires Table 2: Results of tests on wood nutrient concentrations and contents. Values of the F statistic are presented. df: degrees of freedom.

Nutrient concentration Source

Site

Year

1

56.28‡ 20.52‡ 22.72‡ 23.77‡ 24.68‡ 38.69‡ 32.05‡ 2

2

30.30‡ 54.47‡ 41.06‡ 52.80‡ 25.58‡ 77.37‡ 52.07‡

3

35.62‡ 53.46‡ 46.42‡ 51.60‡ 43.32‡ 59.69‡ 52.68‡

Diameter

Year*Diameter

C

N

P

Nutrient content

C/N

C

N

P

1

0.18

1.39

1.36

1.42

18.43‡

0.96

0.29

2

1.60

11.43†

1.03

10.71†

3.42

4.89*

0.36

3

2.63

0.19

0.91

0.04

0.57

0.87

2.71

1

0.68

5.38†

0.16

5.53† 14.13‡

1.33

0.50

2

1.56

1.31

2.61

1.39

5.92

1.49

2.09

3

1.18

3.63*

0.6

4.00*

1.52

8.69†

1.33

df

1

2

Critical probabilities of the correlations (P) are indicated: *0.01
Figure 3: Time courses of the C/N ratio of burnt wood during four years of decomposition under field conditions.

3.3. EFFECT OF BURNT WOOD ON SOIL AND MICROBIAL FRACTIONS Overall, the presence of burnt wood increased most of the soil and microbial fractions. Soil organic matter (SOM), total C and N (Ctot and Ntot), dissolved organic C and N (DOC and DON), inorganic P (Pinorg), microbial biomass (Cmicro), microbial nitrogen (Nmicro) and the soil C/N ratio (C/Nsoil) were

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higher in soil samples under logs than in bare areas (Table 3, Fig. 4). This happened at all sites and either within two or four years, with no interactions with these factors (Table 3). Exceptions to this were the interactions between position and year emerged in DON and Pinorg, although values remained higher under logs in both years (Table 3). The pH was also slightly more basic under logs, although in this case the pattern varied across sites (Table 3, Fig. 4). By contrast, bulk density was lower under logs (Table 3, Fig. 4). However, the presence of wood significantly affected neither the inorganic forms of N (NH4+ and NO3-), nor microbial P (Pmicro), nor the C/N ratio in microorganisms (C/Nmicro) (Table 3). Nonetheless, when soil and microbial fractions were expressed as content per kg of soil, no significant differences were found between positions under logs and in bare areas for any of these variables (P>0.05, two way ANOVAs or GLMs, Table 4) due to the lower bulk density under logs. Some soil fractions (SOM, Ctot, Ntot, NH4+, DOC and DON), Nmicro and C/Nmicro also differed over the years in which they were sampled (Table 3), all being higher in 2010 than in 2008 with the exception of Nmicro (Fig. 5).

122

______________________________________Burnt wood increases soil fertility after wildfires

Figure 4: Effects of the presence of burnt wood on the soil and microbial fractions, soil pH and bulk density. Bars represent mean soil pH, bulk density, organic matter (SOM), soil fractions (Ctot, Ntot, C/Nsoil, NH4+, NO3-, DOC, DON, and Pinorg) and microbial fractions (Cmicro, Nmicro, C/Nmicro and Pmicro) at the three experimental sites and the two positions: under logs (black bars) and bare soil (grey bars). Data from different years are pooled, except pH and bulk density, which are available only for 2008 and 2010, respectively. Concentration values in the microbial fractions were corrected for extraction efficiency.

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Table 3: Results of tests on soil and microbial fractions. The effects of sampling years (“year”), experimental sites (“sites”), position in relation to the burnt logs (under or in bare areas; “position”) and their interactions are shown. Soil organic matter (SOM), total carbon (Ctot), total nitrogen (Ntot), ammonium (NH4+), nitrate (NO3-), dissolved organic carbon (DOC), microbial carbon (Cmicro), dissolved organic nitrogen (DON), microbial nitrogen (Nmicro), phosphorus (Pinorg), microbial phosphorus (Pmicro), soil C/N ratio (C/Nsoil), microbial C/N ratio (C/Nmicro), soil pH (pH), bulk density (ρsoil). Values of the F statistic are presented. df: degrees of freedom.

SOM

Ctot

Ntot

NH4+

NO3-

DOC

Cmicro

DON

Nmicro

Pinorg

Pmicro

C/Nsoil

C/Nmicro

Year

22.30‡

18.62‡

34.33‡

5.39*

0.84

14.84‡

2.83

30.94‡

3.87*

0.01

2.25

1.13

13.90‡

Site

1.91

3.83*

21.65‡

3.07

7.29*

4.75†

5.72

0.39

19.48‡

11.68‡

6.13*

21.87‡

4.64

54.09‡

10.76‡

2

Position

23.25‡

50.03‡

34.59‡

0.26

3.11

28.99‡

8.00†

32.16‡

8.02†

24.06‡

0.38

21.13‡

1.54

4.06*

23.67‡

1

Year*Site

0.14

0.39

0.33

3.14

0.75

0.26

0.88

1.90

2.23

1.13

3.52

0.74

1.27

2

Year*Position

2.94

1.16

2.24

0.22

2.47

3.83

0.65

3.93*

0.48

4.16*

0.06

0.10

0.25

1

Site*Position Year*Site* Position

0.51

1.08

0.45

1.42

2.26

0.28

3.42

0.20

2.07

2.64

0.74

1.09

0.33

0.72

3.49*

4.67*

0.91

0.96

1.39

3.04

1.63

4.25

0.24

0.15

0.31

0.69

Critical probabilities of the correlations (P) are indicated: *0.01
124

pH

ρsoil

df 1

3.48*

1.57

2 2

______________________________________________________________________________Burnt wood increases soil fertility after wildfires

Table 4: Pools of soil and microbial fractions in positions located under logs and in bare areas for the upper 10 cm of soil. Values represent means±standard errors. UL: under logs, BS: bare soil

Site 1 2 3

NH4+ (g m-2)

Position

SOM (kg m-2)

Ctot (kg m-2)

Ntot (g m-2)

UL

4.855±0.233

1.706±0.078

106.40 ±7.00

0.498±0.134

BS

5.140±0.277

1.818±0.134

118.94±7.27

0.354±0.077

UL

5.065±0.406

2.176±0.119

119.91±5.68

0.610±0.111

BS

5.533±0.302

1.958±0.132

120.95±7.21

UL

4.194±0.282

1.995±0.152

BS

4.403±0.247

1.658±0.149

NO3(g m-2)

DOC (g m-2)

Cmicro (g m-2)

DON (g m-2)

Nmicro (g m-2)

Pinorg (g m-2)

Pmicro (g m-2)

0.132±0.028

13.84±1.54

20.37±4.94

0.948±0.085

1.375±0.230

0.469±0.072

0.069±0.059

0.112±0.024

15.24±2.07

32.60±6.20

1.192±0.147

2.149±0.358

0.562±0.098

0.120±0.065

0.108±0.022

16.62±2.30

34.50±5.07

1.339±0.126

3.833±0.558

0.397±0.077

0.207±0.072

0.743±0.141

0.193±0.031

13.53±2.40

29.67±3.11

1.162±0.131

2.799±0.381

0.391±0.067

0.168±0.084

126.79±8.48

0.294±0.051

0.140±0.026

8.68±0.91

28.28±3.47

0.966±0.080

2.704±0.256

0.564±0.110

0.266±0.078

123.74±10.64

0.561±0.123

0.133±0.024

9.85±1.66

21.45±2.67

0.903±0.090

1.810±0.207

0.386±0.054

0.249±0.180

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Figure 5: Differences in soil and microbial fractions between sampling years. Different sites and positions (under logs and bare areas) are pooled. Significant differences among years are indicated: *0.01
4. DISCUSSION Despite the relative slow decay rates of pine wood in this Mediterranean climate (ca. 10% of the initial wood weight was lost after four years) nutrients were progressively released from wood over the first four years of decay. Most of the soil and microbial fractions were radically affected by the presence of burnt wood scattered over the ground, with consistent increases in areas under burnt logs. Moreover, these effects became noticeable after two years of wood decomposition regardless of the site and pine wood species. The presence of logs also altered C and N cycling by modifying the distribution of limiting nutrients between the soil and microorganisms. Altogether, these results constitute clear evidence of the critical biogeochemical role of burnt wood and support the contention that the remaining wood after a wildfire represents an important component of the ecosystem, as it enhances nutrient cycling and ecosystem functioning. 126

______________________________________Burnt wood increases soil fertility after wildfires

4.1. DECOMPOSITION AND TIME COURSES OF NUTRIENTS IN WOOD The results show that the burnt wood still had a high concentration of N (ca. 0.18%) and P (ca. 100 ppm), with similar or even higher values than those reported for unburnt wood (Alriksson and Eriksson, 1998; Augusto et al., 2008; Merino et al., 2005; Palviainen et al., 2010a, 2010b). Fire usually volatilizes nutrients contained in the bark and small fractions of the tree, whereas even in intense, standreplacing fires, the chemical composition of the large wood fractions remains unaffected (Stocks et al., 2004; Wei et al., 1997). Moreover, there was a strong release of nutrients contained in the burnt wood during the first four years of decomposition. After this period, the release of N, and particularly of P, from wood was very high, accounting for ca. 40% and 65% of the initial content, respectively. For P, the decrease was constant over the two sampled periods, whereas slight initial rises in the N concentration were registered at some sites after two years, followed by a strong decrease. These patterns were consistent at the three study sites despite certain differences among them. This may be related to an initial nutrient immobilization by microorganisms colonizing of the decomposing wood (Brown et al., 1996; Laiho and Prescott, 2004; Ouro et al., 2001), and to the fact that these soils are particularly P-limited (mean of 3.54±0.33 mg kg-1), which might explain the relative higher mobilization of this element from wood (Gray and Dighton, 2009; Jonasson et al., 1996). Thus, the burnt wood left after a wildfire can still retain a large amount of nutrients, which can be used to preserve and restore the ecosystem nutrient capital. Furthermore, the progressive nutrient release is expected to continue for years as wood decay proceeds, allowing retention by the soil and regenerating vegetation. By contrast, the release of C, the main wood constituent, occurred fundamentally during the first sampling period, coupled with wood mass losses. Consequently, the C/N wood ratio remained initially constant and sharply increased

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afterwards. This contrasts with the decrease in the C/N ratio as wood decays reported in most of studies, associated mainly with a progressive N retention by the wood (Clark et al., 2002; Ganjegunte et al., 2004; Harmon et al., 1986; Idol et al., 2001; Yang et al., 2010). Nonetheless, increases in wood C concentration have been reported in some cases at initial stages of decomposition (Garret et al., 2008; Preston et al., 1998; Sandström et al., 2007; Yang et al., 2010). In our case, the microbial colonization and the associated N retention may be limited by the relatively low moisture retained by wood (Brown et al., 1996; Zhou et al., 2007), since insolation and temperatures are not ameliorated by the forest canopy. As a result, wood becomes more recalcitrant as it decomposes, accentuating the N shortage for decomposer activity (Ouro et al., 2001; Weedon et al., 2009). In summary, burnt wood played an important role as a reservoir of carbon and as well as a source of nutrients during the initial stages of decomposition, regulating the nutrient availability and preventing sudden losses in the regenerating ecosystem.

4.2. EFFECTS OF BURNT WOOD ON SOIL AND MICROBIAL FRACTIONS Overall, most of the soil and microbial fractions were higher and the pH more basic under burnt logs. This may be attributed either to the nutrient release by burnt wood (Hafner et al., 2005; Kuehne et al., 2008; Wei et al., 1997) or to physical protection of soil by logs, as logs and branches can foster a more favourable soil microclimate (Castro et al., 2011; Smaill et al., 2008; Stoddard et al., 2008) and prevent nutrient losses through soil erosion and runoff that would carry away ash deposited after the wildfire (Fox, 2011; Kim et al., 2008; Shakesby et al., 1996; Thomas et al., 2000). Thus, burnt wood prompted microbial activity and nutrient cycling, as supported similarly by higher levels of soil respiration in this treatment (Marañón-Jiménez et al., 2011). An exception was found in the inorganic fractions of N (NH4+ and NO3-), which represent the most available N

128

______________________________________Burnt wood increases soil fertility after wildfires

fractions in the soil. Their fast mobilization between soil, plants, and microorganisms is determined by the convergence of several environmental factors (Killham, 1994), making it difficult to detect an effect on them by punctual sampling. Nonetheless, the low values of NH4+ under logs coincide with the highest values of microbial biomass and N, suggesting a limitation of available N, both by direct adsorption in SOM and through microbial immobilization (Hafner et al., 2005; Magill and Aber, 2000). Probably as a consequence of this N limitation, microbial P also did not increase significantly under logs and followed a pattern similar to that of the microbial biomass and N. In addition, most of the N and C soil fractions tended to increase between the two sampling years, although proportionally, and thus without changes in the soil C/N ratio. This increase could be associated partly with the progressive nutrient release from the wood, although other factors such as interannual differences in the balance between productivity and mineralization, in the phenology of vegetation, or in short-term shifts in the nutrient demands of microorganisms and plants might also determine temporal variations in the soil fractions (Adair and Burke 2010; Hodge et al., 2000; Jandl et al., 2007). The presence of burnt wood also decreased the soil bulk density, likely due to the greater proportion of organic matter. A low bulk density is indicative of soil quality and fertility, facilitating soil aeration and root penetration (Schoenholtz et al., 2000). Lower bulk-density values are also usually associated with higher organic-matter content, porosity and more structured soil (Schoenholtz et al., 2000; Merino and Edeso, 2000). On the other hand, this implies that the nutrient pool and microbial fractions in the first 10 cm of soil did not differ between positions under logs vs. bare areas. Expressing soil and microbial fractions as pools per unit area could therefore lead to an underestimation of the overall improvement of soil fertility from the wood. In summary, the presence of wood over the soil generally increased soil nutrients, microbial fractions, and SOM, while decreasing bulk

129

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density and affecting the distribution of nutrients between the soil and microorganisms. The resulting improvement in soil fertility could enhance primary productivity and thereby the regeneration of vegetation.

4.3. IMPLICATIONS FOR MANAGEMENT AND ECOSYSTEM PROCESSES

There is currently intense debate concerning the appropriate management of burnt trees after forest fires (Beschta et al., 2004; Donato et al., 2006; Lindenmayer et al., 2004; McIver and Starr, 2001). Postfire salvage logging (felling and removing burnt trunks, often combined with the elimination of the remaining woody debris; Beschta et al., 2004; McIver and Starr, 2001) is implemented worldwide (Castro et al., 2009; Lindenmayer et al., 2004; McIver and Starr, 2001; Van Nieuwstadt et al., 2001), but recent studies show that it may impact ecosystem function and regeneration (Castro et al., 2010b, 2011; Donato et al., 2006; Lindenmayer and Noss, 2006). The felling and removal of burnt trees using ground-based yarding techniques may increase soil erosion and compaction, reduce nutrient availability, damage the seedling bank, hamper the regeneration of the plant community, reduce species richness and diversity, and ultimately raise net ecosystem CO2 emissions (Beschta et al., 2004; Castro et al., 2011; Donato et al., 2006; Lindenmayer and Noss, 2006; McIver and Starr, 2000, 2001; Serrano-Ortiz et al., 2011). However, the specific role of burnt wood on the postfire soil fertility and nutrient mobilization has not been tackled to the date. The present study shows that the burnt wood has a relevant role for nutrient cycling and the recovery of the soil fertility. Burnt wood biomass at the study site has been estimated at 43,052 kg ha-1 (66% aboveground and 34% belowground), according to allometric equations based on pine density and tree size (three sites pooled; Castro et al., 2010b). This implies an initial pool of 76.2 kg ha-1 of N and

130

______________________________________Burnt wood increases soil fertility after wildfires

4.3 kg ha-1 of P, of which 31.8 kg ha-1 of N and 2.8 kg ha-1 of P were released after only four years. Moreover, its effect may be long lasting (Smaill et al., 2008), as the nutrient release is slow and progressive. The reduction of the soil bulk density may also help to compensate for the detrimental effects that soil compaction can have on soil properties (Merino and Edeso, 1999). On the contrary, the removal of burnt wood, as during salvage logging operations, would translate to a reduction in soil fertility and hence in the regeneration capacity of vegetation (Jurgensen et al., 1997; Lindenmayer et al., 2008; Stoddard et al., 2008). Thus, salvage logging can have detrimental effects on nutrient cycling and ecosystem functioning that should be considered when making management decisions.

5. CONCLUSIONS

The burnt wood after a wildfire still contains a great amount of nutrients that are released through decomposition, augmenting soil fertility and accelerating microbiological processes. Burnt logs therefore provide a valuable ecosystem service, as they enhance the biogeochemical sustainability, resilience, and functioning, which are key ecological properties for regeneration success.

6. ACKNOWLEDGEMENTS We wish to thank Ramón Ruíz Puche for his hard work in the field, Gustavo Román Reche for his assistance in processing the wood samples, and Susana Hitos for her invaluable help and advice in the laboratory analyses. We are especially grateful to Luis Matías for his inspiring suggestions and to Andrew S. Kowalski for his personal advice. Consejería de Medio Ambiente (Junta de Andalucía) and the Parque Nacional y Natural de Sierra Nevada offered support in establishing the treatments. This work was financed by the by the projects (SUM2006-00010-00131

Chapter 2_______________________________________________________________________

00) of the INIA, (10/2005) of the Organismo Autónomo de Parques Nacionales (MMA), GESBOME (P06-RNM-1890) of the Junta de Andalucía, ConsoliderIngenio Montes (CSD2008-00040) of the MICINN, Subprogram for Technical Support (PTA2009-1782-I) of the MICINN, and by a grant FPU-MEC to S.M.J.

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Jonasson, S., Michelsen, A., Schmidt, I.K., Nielsen, E.V., Callaghan, T.V., 1996. Microbial biomass C, N and P in two arctic soils and responses to addition of NPK fertilizer and sugar: implications for plant nutrient uptake. Oecologia 106, 507515. Jurgensen, M.F., Harvey, A.E., Graham, R.T., PageDumroese, D.S., Tonn, J.R., Larsen, M.J., Jain, T.B., 1997. Impacts of timber harvesting on soil organic matter, nitrogen, productivity, and health of Inland Northwest forests. Forest Science 43, 234-251. Killham, K., 1994. Soil Ecology. Cambridge University Press, Cambridge. Kim, C.G., Shin, K., Joo, K.Y., Lee, K.S., Shin, S.S., Choung, Y., 2008. Effects of soil conservation measures in a partially vegetated area after forest fires. Science of the Total Environment 399, 158-164. Klinka, K., Lavkulich, L.M., Wang, Q., Feller, M.C., 1995. Influence of decaying wood on chemical properties of forest floors and surface mineral soils: a pilot study. Annals of Forest. Science. 52, 523-533. Kuehne, C., Donath, C., Muller-Using, S.I., Bartsch, N., 2008. Nutrient fluxes via leaching from coarse woody debris in a Fagus sylvatica forest in the Solling Mountains, Germany. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 38, 2405-2413. Laiho, R., Prescott, C.E., 2004. Decay and nutrient dynamics of coarse woody debris in northern coniferous forests: a synthesis. Canadian Journal of Forest ResearchRevue Canadienne De Recherche Forestiere 34, 763-777. Lambert, R.L., Lang, G.E., Reiners, W.A., 1980. Loss of mass and chemical change in decaying boles of a Subalpine balsam fir forest. Ecology 61, 1460-1473. Lindenmayer, D.B., Burton, P.J., Franklin, J.F., 2008. Salvage Logging and its Ecological Consequences. Island Press, Washington. Lindenmayer, D.B., Foster, D.R., Franklin, J.F., Hunter, M.L., Noss, R.F., Schmiegelow, F.A., Perry, D., 2004. Salvage harvesting policies after natural disturbance. Science 303. Lindenmayer, D.B., Noss, R.F., 2006. Salvage logging, ecosystem processes, and biodiversity conservation. Conservation Biology 20, 949-958. Mackensen, J., Bauhus, J., 2003. Density loss and respiration rates in coarse woody debris of Pinus radiata, Eucalyptus regnans and Eucalyptus maculata. Soil Biology and Biochemistry 35, 177-186. Magill, A.H., Aber, J.D., 2000. Dissolved organic carbon and nitrogen relationships in forest litter as affected by nitrogen deposition. Soil Biology and Biochemistry 32, 603-613.

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Marañón-Jiménez, S., Castro, J., Kowalski, A.S., Serrano-Ortiz, P., Reverter, B.R., Sánchez-Cañete, E.P., Zamora, R., 2011. Post-fire soil respiration in relation to burnt wood management in a Mediterranean mountain ecosystem. Forest Ecology and Management 261, 1436-1447. Marcos, E., Villalon, C., Calvo, L., Luis-Calabuig, E., 2009. Short-term effects of experimental burning on soil nutrients in the Cantabrian heathlands. Ecological Engineering 35, 820-828. McIver, J.D., Starr, L., 2000. Environmental effects of postfire logging: literature review and annotated bibliography Gen. Tech. Rep. Portland, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. PNW-GTR-486., 72. McIver, J.D., Starr, L., 2001. A literature review on the environmental effects of postfire logging. Western Journal of Applied Forestry 16, 159-168. Merino, A., Balboa, M.A., Soalleiro, R.R., Gonzalez, J.G.A., 2005. Nutrient exports under different harvesting regimes in fast-growing forest plantations in southern Europe. Forest Ecology and Management 207, 325-339. Merino, A., Edeso, J.M., 1999. Soil fertility rehabilitation in young Pinus radiata D. Don. plantations from northern Spain after intensive site preparation. Forest Ecology and Management 116, 83-91. Merino, A., Rey, C., Brañas, J., Soalleiro, R.R., 2003. Biomasa arbórea y acumulación de nutrientes en plantaciones de Pinus radiata D. Don en Galicia. Investigación agraria: Sistemas y Recursos Forestales 12, 85-98. Neary, D.G., Klopatek, C.C., DeBano, L.F., Ffolliott, P.F., 1999. Fire effects on belowground sustainability: A review and synthesis. Forest Ecology and Management 122, 51-71. Ouro, G., Perez-Batallon, P., Merino, A., 2001. Effects of silvicultural practices on nutrient status in a Pinus radiata plantation: Nutrient export by tree removal and nutrient dynamics in decomposing logging residues. Annals of Forest Science 58, 411-422. Page-Dumroese, D.S., Jurgensen, M.F., 2006. Soil carbon and nitrogen pools in mid- to late-successional forest stands of the northwestern United States: potential impact of fire. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 36, 2270-2284. Palviainen, M., Finer, L., Laiho, R., Shorohova, E., Kapitsa, E., Vanha-Majamaa, I., 2010a. Carbon and nitrogen release from decomposing Scots pine, Norway spruce and silver birch stumps. Forest Ecology and Management 259, 390-398. Palviainen, M., Finer, L., Laiho, R., Shorohova, E., Kapitsa, E., Vanha-Majamaa, I., 2010b. Phosphorus and base cation accumulation and release patterns in

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decomposing Scots pine, Norway spruce and silver birch stumps. Forest Ecology and Management 260, 1478-1489. Pansu, M., Gautheyrou, J., 2006. Handbook of Soil Analysis. Mineralogical, Organic and Inorganic Methods. Springer, Montpellier. Preston, C.M., Trofymow, J.A., Niu, J., Fyfe, C.A., 1998. PMAS-NMR spectroscopy and chemical analysis of coarse woody debris in coastal forests of Vancouver Island. Forest Ecology and Management 111, 51-68. Quinn, G.P., Keough, M.J., 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge. Raison, R.J., 1979. Modification of the soil environment by vegetation fires, with particular reference to nitrogen transformations - Review. Plant and Soil 51, 73108. Rock, J., Badeck, F.W., Harmon, M.E., 2008. Estimating decomposition rate constants for European tree species from literature sources. European Journal of Forest Research 127, 301-313. Sandström, F., Petersson, H., Kruys, N., Stahl, G., 2007. Biomass conversion factors (density and carbon concentration) by decay classes for dead wood of Pinus sylvestris, Picea abies and Betula spp. in boreal forests of Sweden. Forest Ecology and Management 243, 19-27. Sardans, J., Peñuelas, J., Rodá, F., 2005. Changes in nutrient use efficiency, status and retranslocation in young post-fire regeneration Pinus halepensis in response to sudden N and P input, irrigation and removal of competing vegetation. Trees 19 233-250. Schinner, F., Ohlinger, R., Kandeler, E., Margesin, R., 1995. Methods in Soil Biology. Springer-Verlag, Berlin. Schoenholtz, S.H., Miegroet, H.V., Burger, J.A., 2000. A review of chemical and physical properties as indicators of forest soil quality: challenges and opportunities. Forest Ecology and Management 138, 335-356. Serrano-Ortiz, P., Marañón-Jiménez, S., Reverter, B.R., Sánchez-Cañete, E.P., Castro, J., Zamora, R., Kowalski, A.S., 2011. Post-fire salvage logging reduces carbon sequestration in Mediterranean coniferous forest. Forest Ecology and Management, doi:10.1016/j.foreco.2011.08.023. Shakesby, R.A., 2011. Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth-Science Reviews 105, 71-100. Shakesby, R.A., Boakes, D.J., Coelho, C.d.O.A., Gonçalves, A.J.B., Walsh, R.P.D., 1996. Limiting the soil degradational impacts of wildfire in pine and eucalyptus forests

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in Portugal : A comparison of alternative post-fire management practices. Applied Geography 16, 337-355. Shorohova, E., Kapitsa, E., Vanha-Majamaa, I., 2008. Decomposition of stumps in a chronosequence after clear-felling vs. clear-felling with prescribed burning in a southern boreal forest in Finland. Forest Ecology and Management 255, 36063612. Smaill, S.J., Clinton, P.W., Greenfield, L.G., 2008. Postharvest organic matter removal effects on FH layer and mineral soil characteristics in four New Zealand Pinus radiata plantations. Forest Ecology and Management 256, 558-563. Spanos, I., Raftoyannis, Y., Goudelis, G., Xanthopoulou, E., Samara, T., Tsiontsis, A., 2005. Effects of postfire logging on soil and vegetation recovery in a Pinus halepensis Mill. forest of Greece. Plant and Soil 278, 171-179. Sparks, D.L., 1996. Methods of soil analysis. Part 3.Chemical Methods. Soil Science Society of America and American Society of Agronomy., Madison WI. Sparling, G., West, A., 1988. Modifications to the fumigation-extraction technique to permit simultaneous extraction and estimation of soil microbial C and microbial N. Communications in soil science and plant analysis 327-344. Spies, T.A., Franklin, J.F., Thomas, T.B., 1988. Coarse woody debris in douglas-fir forests of Western Oregon and Washington. Ecology 69, 1689-1702. Stocks, B.J., Alexander, M.E., Wotton, B.M., Stefner, C.N., Flannigan, M.D., Taylor, S.W., Lavoie, N., Mason, J.A., Hartley, G.R., Maffey, M.E., Dalrymple, G.N., Blake, T.W., Cruz, M.G., Lanoville, R.A., 2004. Crown fire behaviour in a northern jack pine-black spruce forest. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 34, 1548-1560. Stoddard, M.T., Huffman, D.W., Alcoze, T.M., Fule, P.Z., 2008. Effects of slash on herbaceous communities in pinyon-juniper woodlands of northern Arizona. Rangeland Ecology and Management 61, 485-495. Thiffault, E., Pare, D., Belanger, N., Munson, A., Marquis, F., 2006. Harvesting intensity at clear-felling in the boreal forest: Impact on soil and foliar nutrient status. Soil Science Society of America Journal 70, 691-701. Thomas, A.D., Walsh, R.P.D., Shakesby, R.A., 1999. Nutrient losses in eroded sediment after fire in eucalyptus and pine forests in the wet Mediterranean environment of northern Portugal. Catena 36, 283-302. Thomas, A.D., Walsh, R.P.D., Shakesby, R.A., 2000. Post-fire forestry management and nutrient losses in eucalyptus and pine plantations, northern Portugal. Land Degradation & Development 11, 257-271.

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Tinker, D.B., Knight, D.H., 2000. Coarse woody debris following fire and logging in wyoming lodgepole pine forests. Ecosystems 3, 472-483. Trabaud, L., 1994. The effect of fire on nutrient losses and cycling in a Quercus coccifera garrigue (southern France). Oecologia 99, 379-386. Van Nieuwstadt, M.G.L., Sheil, D., Kartawinata, K., 2001. The ecological consequences of logging in the burned forests of East Kalimantan, Indonesia. Conservation Biology 15, 1183-1186. Wan, S.Q., Hui, D.F., Luo, Y.Q., 2001. Fire effects on nitrogen pools and dynamics in terrestrial ecosystems: A meta-analysis. Ecological Applications 11, 1349-1365. Watanabe, F., 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 Extracts from Soil1. Soil Science Society of America Journal 29, 677. Weedon, J.T., Cornwell, W.K., Cornelissen, J.H.C., Zanne, A.E., Wirth, C., Coomes, D.A., 2009. Global meta-analysis of wood decomposition rates: a role for trait variation among tree species? Ecology Letters 12, 45-56. Wei, X., Kimmins, J.P., Peel, K., Steen, O., 1997. Mass and nutrients in woody debris in harvested and wildfire-killed lodgepole pine forests in the central interior of British Columbia. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 27, 148-155. Whelan, R.J., 1995. The Ecology of Fire. Cambridge University Press, Cambridge. Yang, F.F., Li, Y.L., Zhou, G.Y., Wenigmann, K.O., Zhang, D.Q., Wenigmann, M., Liu, S.Z., Zhang, Q.M., 2010. Dynamics of coarse woody debris and decomposition rates in an old-growth forest in lower tropical China. Forest Ecology and Management 259, 1666-1672. Yang, Y.S., Guo, J.F., Chen, G.S., He, Z.M., Xie, J.S., 2003. Effect of slash burning on nutrient removal and soil fertility in Chinese fir and evergreen broadleaved forests of mid-subtropical China. Pedosphere 13, 87-96. Zhou, L., Dai, L.-m., Gu, H.-y., Zhong, L., 2007. Review on the decomposition and influence factors of coarse woody debris in forest ecosystem. Journal of Forest Research 18, 48-54.

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APPENDIX A : Estimation of the initial dry weight of the wood discs to calculate

the dry weigh lost by the burnt wood over time. To estimate the initial dry weight of the discs collected after two (2008) and four (2010) years of decomposition, we used a regression model constructed with the volume and the dry weight of the wood discs initially collected in 2006. Previously, we checked that diameter had no effect on the initial wood density for any of the sites (P>0.05 for all sites), so the diameter did not have to be included as an independent variable in the model. Initial wood density differed among sites (Table A1) despite the absence of differences in the rest of variables, so a regression model was fitted separately for each site. Further, the dry weight of a wood disc must be zero when its volume is zero. For this, the intercept of the regression line was forced to be zero for each regression model. Nonetheless, once the models with intercept were fitted, the H0 that the intercept was zero was tested in all of them, and the H0 could not be rejected in most of the cases. The resulting regression equations for each site are: Wd=0.7304172*Vd for site 1; Wd=0.7348488*Vd for site 2; Wd=0.7237018*Vd for site 3; where Wd and Vd are the dry weight and the volume of the initial wood discs. As the external fragmentation of the log was negligible over the study period, we can assume that the volume of the wood discs (Vd) remained constant during these initial stages of wood decomposition. Thus, the volume of the wood discs of 2008 and 2010 (Vd) was introduced in the constructed regression model to estimate their initial dry weight (Wd).

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Chapter 2_______________________________________________________________________ Table A1 Summary of the variables measured in the wood discs collected in 2006 which were used in the regression models and results of testing the differences between the experimental sites. F: statistic of the contrast of the one-way ANOVAs; df: degrees of freedom; P: critical probability of the contrast; Фd: diameter of the discs; Wd: dry weight of the wood discs; Vd: volume of the wood discs; ρd: density of the wood discs. Different letters indicate significant differences among sites at level α=0.05.

Variable

Site 1

Site 2

Site 3

Фd (cm) 13.3

12.8

12.1

Range

22.2

18.7

10.8

Wd (g) Range 1

df

P

0.28 2 0.7575

Mean

Mean

F

0.03 2 0.9671 425.01

397.62 344.13

1390.4

1861.1 1055.8

3

Vd (cm )

0.09 2 0.9145

Mean

580.7

553.3

497.7

Range

1895.3

2231.9 1385.7

ρd (g cm-3)

6.00 2 0.0031 a

Mean

0.73

Range

0.27

0.70

a,b

0.32

0.68

b

0.40

1

Assuming a conical shape for each disc, its volume (Vd) in cm3 was calculated as follows:

Vd= 1/3πh(R2+Rr+r2) where h is the mean height of the disc in cm; R and r are, respectively, the maximum and minimum mean radii of each disc face in cm.

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CHAPTER 3: POST-FIRE SALVAGE LOGGING INCREASES WATER STRESS AND REDUCES SEEDLING GROWTH AND PERFORMANCE OF Pinus Pinaster IN THE SIERRA NEVADA (SE SPAIN)

Sara Marañón-Jiménez, Jorge Castro, Ignacio Querejeta, Emilia Fernández-Ondoño, Craig D. Allen

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ABSTRACT Intense debate surrounds the most suitable post-fire management related to the burnt wood for forest regeneration, but scant support is available from experimental studies. In this study, we experimentally analyze the effect of three post-fire management treatments on the growth and performance of seedlings of a serotinous pine (Pinus pinaster) in the Sierra Nevada (SE Spain), a Mediterranean mountain range. Treatments were applied 7 months after the September 2005 fire and differ in the degree of intervention, ranging from “Non Intervention” (NI, all trees left standing) to “Cut plus Lopping” (CL, felling most of the trees, cutting off the main branches, and leaving all the biomass in situ without mastication), and “Salvage Logging” (SL, felling and pilling up the logs, and masticating the woody debris). After three years, a random sample of naturally regenerating young pines was harvested (aboveground biomass) and analysed for growth, biomass, nutrient content, and leaf δ13C and δ15N. Total aboveground pine seedling biomass was similar among treatments, although it tended to be higher in CL. The height growth and biomass increase during the second and third growing seasons (years 2007 and 2008) was also higher in CL and NI treatments, and lowest in SL. Leaf nutrient concentrations were similar among treatments. Pines from SL also showed higher leaf δ13C values, indicating more severe water stress in this treatment. By contrast, the leaf δ15N tended to show the opposite pattern, with the lowest values in SL, suggesting less N sources and mineralization in the soil. Overall, the results support the contention that salvage logging has a detrimental effect on pine growth and performance in relation to treatments where burnt logs and branches are left in situ. This is likely associated with the amelioration of microsite conditions by the presence of remaining wood, which increases soil moisture and nutrient availability through wood decomposition. Key words: Burnt wood, facilitation, shelter structures, Pinus pinaster regeneration, postfire restoration, salvage harvesting, pine nutrient status, microclimate amelioration, wood nutrient release.

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1. INTRODUCTION A current controversial issue among restoration ecologists and forest managers concerns the appropriate management of dead burnt trees after fire. Postfire salvage logging (i.e.: the felling and removal of the burnt tree trunks, also often eliminating the remaining woody debris [branches, logs, and snags] by chipping, mastication, fire, etc.) has historically been routinely and widely practiced by forest administrations around the world (Bautista et al., 2004; Beschta et al., 2004; Lindenmayer and Noss, 2006; McIver and Starr, 2000; Spanos et al., 2005), particularly in the case of burnt conifer forests. However, there is currently intense debate about the suitability of this approach, and an increasing number of studies are showing that the felling and removal of burnt trees using ground-based yarding techniques may impact plant regeneration in several ways (Beschta et al., 2004; Donato et al., 2006; Lindenmayer and Noss, 2006; McIver and Starr, 2000, 2001; Stark et al., 2006). For example, salvage logging may increase soil erosion and compaction (Fernández et al. 2007; McIver and McNeil, 2006; Purdon et al., 2004; Wondzell, 2001), precluding seedling emergence and establishment (Donato et al., 2006). Indeed, the bank of seedlings or resprouters usually present (or starting to appear) at the moment of salvage operations can be also damaged, thus reducing seedling density at the starting point of succession (Fernández et al., 2008; Greene et al., 2006; Martínez-Sánchez et al., 1999; McIver and Starr, 2000, 2001), with the consequent reduction of the regeneration capacity. As a result, there are increasing calls to implement less aggressive post-fire treatment policies and actions, including non-intervention, associated with evidence that snags and decaying burnt wood are important components of natural systems that promote ecosystem recovery and diversity (Beschta et al., 2004; DellaSala et al., 2006; Hutto, 2006; Lindenmayer et al., 2004).

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The factors that enhance seedling recruitment, as well as the later growth and performance after a perturbation will vary depending on the species and the limiting factors at each particular site. Mediterranean ecosystems are particularly characterised by moisture limitation and are frequently established over poor soils with low nutrient availability (Costa-Tenorio et al., 1998; Sardans et al., 1995). Therefore, the reduction of drought severity and the supply of a source of nutrients would bring to a higher probability of vegetation survival (Castro et al., 2011; Jiménez et al., 2007; Querejeta et al., 2008; Matías et al., 2011; Siles et al., 2010). Water limitation can be especially accentuated after a stand replacing fire, since soil permeability and albedo decrease whereas radiation incidence and soil heating intensifies over the soil (Certini, 2005). In this regard, woody debris, remains of thinning, litter and mulching have been widely considered and used as elements to maintain soil moisture (Devine and Harrington, 2007; Harmon et al., 1986; Jiménez et al., 2007; Lindenmayer et al., 2008; Martínez-Sánchez et al., 1999; McIver and Starr, 2000; Smaill et al., 2008; Stoddard et al., 2008). In any case, organic materials covering the soil surface contribute in general to increase water availability for plant uptake, and specifically, the burnt wood scattered over the soil similarly increased soil moisture during the summer drought at this study site (Castro et al., 2011). Fires also provoke a sharp loss of nutrients from the ecosystem, which are contained in the nutrient-rich organic pools with low to medium temperature of ignition (litter, leaves, twigs and branches of small diameter) (Carter and Foster, 2004; DeBano and Conrad, 1978; Neary et al., 1999; Trabaud, 1994; Whelan, 1995). Nonetheless, a great amount of logs and coarse woody debris of greater diameter usually remain after a wildfire (Brais et al., 2005; Wei et al., 1997). In fact, they can represent a potential nutrient reservoir (Harmon et al., 1986; Johnson et al., 2005; Kappes et al., 2007; Merino et al., 2003; Zhou, 2007), as a result of the high biomass and nutrient concentrations similar to that of unburnt wood in cases

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when only the bark and the outer layer have been scorched (Wei et al., 1997). Nutrients contained in wood are progressively released as decomposition occurs (Brown et al., 1996; Ganjegunte et al., 2004; Ouro et al., 2001; Wei et al., 1997), being retained by the soil (De Marco et al., 2005; Pérez-Batallón et al., 2001; Smaill et al., 2008) and becoming available for the regenerating vegetation (Augusto et al., 2000; Jiménez et al., 2007; Stoddard et al., 2008). Thus, burnt wood may improve plant regeneration both by microclimatic amelioration as well as by the nutrient supply to the soil. In this study, we seek to determine the effect of burnt-wood management on the growth and performance of pine seedlings naturally regenerating after a fire. In September 2005, the Lanjarón fire burned ca. 3500 ha in Sierra Nevada Natural and National Park (SE Spain). Working in cooperation with the local Forest Service, we established a long-term study plot in an area dominated by the maritime pine before fire (Pinus pinaster Aiton), a serotinous pine that often regenerates abundantly after fire (Fernandes and Rigolot, 2007; Fernández et al., 2008; Rodrigo et al., 2004; Tapias et al., 2001). Three silvicultural treatments that differed in the degree of ecosystem intervention were established, ranging from no intervention to the conventional salvage logging. In a previous study, we demonstrated that salvage logging reduced the recruitment of pines and affected survival (Castro et al., 2011). Here, we explore the mechanisms that provoked differences among treatments in three years old seedlings. We hypothesized that burnt logs and branches left in situ could improve soil fertility through the nutrient release by wood decomposition. Seedlings could have more access to nutrients, resulting in a higher growth and/or nutritional status. We also hypothesize that the presence of burnt trees and woody debris will improve the water status of pine seedlings due to the shade provided at the ground level (lower soil heating, reduction of evapotranspiration, retention of soil moisture; Castro et al., 2011). This would translate to a lower water stress in seedlings that grow under the shelter

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of burnt trees and coarse woody debris, which will be reflected in its carbon isotopic signal. Altogether, this will imply a relatively lower vigour of seedlings growing in the salvaged area.

2. METHODS 2.1. STUDY SITE AND SPECIES The study site is located in Sierra Nevada Natural and National Park (SE Spain), in an area that burned in September 2005 in the Lanjarón Fire. The fire burned ca. 1300 ha of pine forests of different species with trees 35 to 50 years old, depending on the stand, distributed along an elevational / moisture gradient according to their ecological requirements. The maritime pine (Pinus pinaster) was common at lower elevations (ca. 1400 m a.s.l.). This species is native in the area, although it was extensively planted about 50 years ago to re-establish the tree cover on long-deforested hillslopes, using terraces made with bulldozers, previously a common reforestation practice on hillsides in Spain. Each terrace stairstep is composed of a steep cutslope or “backslope” (~90 cm high), and the nearly flat area of the terrace (“terrace” hereafter) of ~3 m in width. The climate of the area is Mediterranean-type, with rainfall concentrated in spring and autumn, alternating with hot, dry summers. Mean annual precipitation was 470±50 mm, with summer precipitation (June, July and August pooled) of 17±4 mm (1988-2008 period; climatic data from a near meteorological station). The mean annual temperature was 12.3±0.4ºC at 1652 m a.s.l. (State Meteorological Agency, period 1994-2008; Ministry of Environment). Pinus pinaster Aiton grows in the western Mediterranean basin and Atlantic area of the Iberian Peninsula and southern France, from sea level to 1700 m a.s.l. (Franco, 1986). It is a fast-growing species that has been widely used in

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reforestation planting, thus increasing its distribution area in the Mediterranean basin throughout the 20th century. It produces serotinous cones (Tapias et al., 2001) that protect the seeds from intense heat (Reyes and Casal, 2002). Seeds may still be viable after short heat pulses of above 100ºC (Herrero et al., 2007; MartínezSánchez et al., 1995), and the regeneration of the species after fires relies mostly on the aerial seed bank. An abundant seedling bank emerged from late February 2006 (ca. 6 months after the fire), and thus maritime pine naturally regenerated in the area (Castro et al., 2011). Accompanying post-fire vegetation was composed mainly of grass and forbs, with a mean cover of approx. 70%. (Castro et al., 2010). The most common perennial species were Ulex parviflorus, Festuca scariosa, Dactylis glomerata, and Euphorbia flavicoma.

2.2. EXPERIMENTAL DESIGN From 21 April 2006 to 10 May 2006 (ca. seven months after the 2005 forest fire), a plot of 17.7 hectares was established at 1400 m a.s.l. approx., where three replicates of each of the following treatments were implemented in a random spatial distribution: 1) “Non Intervention” (NI), leaving all of the burnt trees standing. 2) “Cut plus Lopping” (CL), a treatment where about 90% of burned trees were cut and felled, with the main branches also lopped off, but leaving all the cut biomass in situ on the ground; after treatment application, felled logs and branches covered 45% of the surface at 0-10 cm from the ground, 61% at 11-50 cm, and 9% at 51-100 cm (Castro et al., 2011). 3) “Salvage Logging” (SL), tress were cut and the trunks cleaned of branches with the use of chainsaws. Trunks were manually piled (groups of 10-15) and the woody debris was masticated using a tractor. The Forest Service planned to remove the trunks with a log forwarder in this treatment, but this step was later cancelled due to difficulties in precisely operating machinery within the spatial arrangement of the plots.

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_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

The resulting 9 experimental replicates had a size that averaged 2 hectares and was similar among treatments (Kruskal-Wallis test, P>0.05). Salvage logging is the usual post-fire action taken by the local Forest Service, and it was fully implemented throughout the rest of the burnt area where the experimental plots were located (removing the logs with a log-forwarder in this case). The three treatments differed therefore in the degree of intervention (maximum in SL, intermediate in CL, minimum in NI) and in the habitat structure generated (minimum habitat complexity in SL). The CL treatment differed from NI in the above-ground habitat structure; we hypothesize that wood decomposition would be faster in CL due to contact of burnt wood with the soil, prompting nutrient cycling and increasing soil fertility. All replicates were homogeneous in terms of orientation (SW), slope (ca. 30%), fire intensity (high intensity) and bedrock (micaschist). The fire was moderate to high in severity, consuming or totally scorching most of the tree crown. Burnt tree density before treatment application was 1477±46 individuals per hectare (estimated by counting the number of trees in four 25x25 m quadrats per experimental replicate two months after the fire) and did not differ among treatments (Kruskal-Wallis test, P=0.66). Basal trunk diameter was 17.1±0.2 cm in NI, 17±0.2 cm in SL and 18.1±0.2 in CL (estimated for 30 random trees per quadrat, thus 120 trees per replicate). Burnt trees fell in the course of consecutive years. The fallen fraction (measured in February of each year) was 0.0% in 2006 and 2007, and 13.3±0.3% in 2008 (last year of this study; measured from 100 marked trees per replicate in NI and CL; Castro et al., 2010). Thus, the NI treatment kept a vertical structure of standing trees throughout the study period.

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2.3. SEEDLING SAMPLING For each experimental replicate, we harvested 12 seedlings (cut at the ground level; 108 seedlings in total). Harvesting was performed in September 2008 (after three growing seasons) in order to ensure that the shoot elongation period of that year had finished. Seedling density was very low on the backslopes (Castro et al., 2011), and thus we restricted the seedling harvesting to the flat area of the terraces. Seedlings were chosen following a stratified random procedure, starting from a initial random point and alternating among the centre and side positions of the terrace close to the backslopes, along the width of the terrace. In only one isolated case was a clearly damaged pine seedling discarded and replaced by another seedling. In order to avoid possible effects of herbivory in the seedling growth pattern, we initially planned to discard those affected by herbivory, but no herbivory was detected (see also Castro et al., 2011) and this was finally not needed. For each seedling, we monitored the following variables: 1) Growth parameters, that included i) total height, ii) leader shoot elongation during the growing season of 2007 (measuring the length achieved in this season), iii) leader shoot elongation during growing season of 2008 (measured in a similar way), iv) basal trunk diameter, v) total biomass, vi) biomass of shoots of 2007, vii) and biomass of shoots of 2008. Biomass was estimated after ovendrying at 60ºC to constant weight (> 48 h). 2) Carbon and nutrient concentration (N, P, Ca, Mg, K, Na, Fe, Mn, Zn, and Cu) in pine needles. After drying, two subsamples of needles were taken from the leader shoot corresponding to the elongation of 2007 and 2008 of each seedling, they were ground with a dry ball-mill and homogenized. Total C and N were analysed by combustion at 850ºC with a Leco TrueSpec Autoanalyzer (St. Joseph, MI, USA). Ground samples were ignited to 750ºC and extracts were prepared by dry ashing dissolution with HCl. From these extracts, P was determined by

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_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

spectrophotometry with the molybdovanadate method [Association of Official Analytical Chemists (AOAC), 1975] with a Perkin Elmer 2400 spectrophotometer (Waltham, MA, USA). The rest of nutrients were analysed only for needles of the shoot of 2008 by atomic absorption with a Perkin Elmer 5100 spectrometer. 3) Carbon and nitrogen isotopic composition. Another subsample of the needles from the leader shoot of 2008 was ground and its isotopic C and N was analysed with a micromass isotope ratio mass spectrometer GV Instruments Iso Prime (Youngstown, OH, USA). Six standards were included for their analysis after every 7-8 samples. The repeated analysis of these standards consistently yielded a standard deviation <0.1‰. Analyses were performed on whole-leaf tissue rather than extracted cellulose, because of strong positive correlations observed between δ13C of whole tissue and cellulose (Ehleringer and Osmond, 1989; West et al., 2001). The abundance of stable isotopes is presented in delta notation (δ), relative to a standard: ⎛R



δ = ⎜⎜ samp − 1⎟⎟ × 1000 0 00 ⎝ Rst ⎠

(1)

where R is the molar ratio of the heavy to light isotopes (R=

13

C/12C or

15

N/14N).

Rsamp refers to the sample and Rst to the international standards Vienna-Pee Dee Belemnite and atmospheric N2, for C and N, respectively. The C isotope analysis has been used as an integrative method to estimate the long term water use efficiency (WUE) of plant tissue over time in response to drought (Lajtha and Marshall, 1994). WUE is defined as: WUE = A/g

(2)

where A is the photosynthetic rate and g is the stomatal conductance (Scheidegger et al., 2000). While both A and g can be negatively affected by water stress, WUE and δ13C increase in response to drought, as g usually decreases more sharply than 153

Chapter 3_______________________________________________________________________

does A (Querejeta et al., 2008). However, A is determined by biochemical factors (amount and activity of Rubisco), which are driven by temperature, irradiance and nutrient availability (Scheidegger et al., 2000). Leaf N concentration is nonetheless a good indicator of the maximum carboxylation capacity (Adams and Kolb, 2004; Field and Mooney, 1986). The δ15N has been frequently used as an integrator of N cycle processes in soil (Peñuelas et al., 1999; Robinson, 2001), where in general, an enrichment in 15

N is indicative of higher mineralization and more active N cycling (Nadelhoffer

and Fry, 1994; Craine et al., 2009). Despite the limitations related to the absence of δ15N values in the soil, discrimination during N uptake by plants is considered not to be relevant in ecosystems where N is limiting (Nadelhoffer and Fry, 1994), as in this case (available inorganic N in soil, as a sum of NH4+ and NO3-, is <4.3±0.5 ppm). Thus, the δ15N signatures of the soils are imprinted in the δ15N of plants that utilize the soil N pools for their nutrition. Foliar δ15N therefore have the potential to characterize N turnover in the soil and the source of N used by plants as an integrative proxy (Kahmen et al., 2008; Querejeta et al., 2008).

3. DATA ANALYSIS The effect of the treatments on pine seedlings was analysed for all variables using linear mixed models, with treatment as the fixed factor and replicate as a random factor nested within treatment. Thus, the hierarchical model considered was: Yijk=µ + Ti + R(T)ji + εijk where Yijk is the value of the dependent variable measured in the seedling ijk; µ is the general mean; Ti is the effect of the treatment; R(T)ji is the effect of replicates nested within each treatment, which accounted for the environmental variation 154

_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

within each treatment; and εijk is the residual error not accounted for by the rest of factors included in the model. In the case of variables measured in the leader shoot elongated in both 2007 and 2008 (leader shoot length, shoot biomass and C, N, P concentrations) the analysis was performed for each year, since we were interested in the effect of the treatments rather than in the pattern through time. Furthermore, several processes could be interacting throughout shoot growth (i.e.: biomass gains in the following years after the shoot elongation, nutrient allocation, etc.), confounding the effects of climatic or environmental factors across years. The relationship between the nutrient concentrations in needles, their isotopic composition and the growth parameters of the shoot were also explored by Pearson correlations. Data were transformed when required to improve normality and homoscedasticity (Quinn and Keough, 2009). Statistical analyses were made with JMP 7.0 software (SAS Institute). Throughout the paper, mean values are followed by ±1SE.

4. RESULTS 4.1. GROWTH PARAMETERS Overall, the growth parameters measured in the whole seedling (total biomass and height and basal trunk diameter) proved higher in CL, although only the total height showed significant differences among treatments, due to the relatively high random variance among replicates (Table 1; Fig. 1). On the other hand, the annual growth (both as elongation and biomass of shoots) was the lowest in SL (Table 1; Fig. 2). This pattern was consistent in the

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Chapter 3_______________________________________________________________________

shoots of the second and third growing season (2007 and 2008), but differences were significant only in the shoots of the last year (Table 1; Fig. 2).

Figure 1: Growth parameters of pine seedlings three growing seasons after the wildfire in the different postfire treatments of burnt wood. NI: non intervention, CL: cut plus lopping, SL: salvage logging. Different letters above bars indicate significant differences among treatments (Tukey HSD test after mixed ANOVAs).

Table 1: Summary of the effects on the growth parameters and the carbon isotopic composition of the pine seedlings. Contrasts were performed by the method of the restricted maximum likelihood (REML). The table shows the results of the contrast for the effects of the treatments (fixed factor) and the estimated percentage of the variance attributed to the random components of the model (replicate and residuals). F: values of the statistic. df: degrees of freedom of the numerator and denominator,

respectively

(constructed

using

the

Kenward-Roger's method). P: critical probability for the treatment effect.

Treatment Effect

Growth Parameter

% Variance of the Total Random Components Replicate Residual

F

df

P

Total biomass (g)

0.87

2, 5.99

0.4643

17.74

82.26

Total height (cm)

7.86

2, 6.00

0.0211

7.55

92.45

Basal trunk diameter (mm)

1.00

2, 5.98

0.4211

20.44

79.56

2007

3.37

2, 6.00

0.1046

5.24

94.76

2008

14.80

2, 6.01

0.0047

-1.36

101.36

2007

3.01

2, 6.00

0.1241

-0.80

100.80

2008

8.71

2, 5.88

0.0175

0.29

99.71

2008

17.58

2, 6.04

0.0030

6.26

93.74

Leader shoot elongation (cm) Shoot Biomass (g) 13

δ C (‰)

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_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

Figure 2: Growth parameters of the shoots of pine seedlings corresponding to the second (2007) and third (2008) growing season after the wildfire in the different post-fire treatments of burnt wood NI: non intervention, CL: cut plus lopping, SL: salvage logging. Different letters above bars indicate significant differences among treatments (Tukey HSD test after mixed ANOVAs)

4.2. NUTRIENT CONCENTRATIONS IN PINE NEEDLES Carbon and nutrient concentrations in the pine needles did not differ among treatments, neither for the shoot part elongated during the second growing season (2007), nor for the corresponding one of the third growing season (2008) (Table 2). In addition, no significant correlations were found between nutrient concentrations and biomass or shoot elongation in 2008. An exception was the correlation between the growth parameters of shoots and needle N concentration, although in these cases correlations were not very strong (R2=-0.22, P=0.021 for shoot biomass; R2=0.21, P=0.030 for shoot elongation; all treatments pooled).

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Chapter 3_______________________________________________________________________

Table 2: Concentrations of carbon, nutrients and isotopic N in the pine shoot needles and their effects. Contrasts were performed by the method of the restricted maximum likelihood (REML). The table shows the results of the contrast for the effects of the treatments (fixed factor) and the estimated percentage of the variance attributed to the random components of the model (replicate and residuals). Means±standard errors of each parameter in the different treatments are also presented. Different letters indicate significant differences among treatments (Tukey HSD test after mixed ANOVAs). F: value of the F statistic. df: degrees of freedom of the numerator and denominator, respectively (constructed using the Kenward-Roger's method). P: critical probability for the treatment effect. NI: non intervention, CL: cut plus lopping, SL: salvage logging.

Shoot 2007

2008

158

Treatment

Parameter NI

CL

SL

F

df

P

% Variance of the Random Components Replicate Residual

C (%)

51.96±0.16

52.35±0.14

52.41±0.20

0.57

2, 5.93

0.5954

22.14

77.86

N (%)

0.98±0.04

1.02±0.03

1.00±0.03

0.05

2, 5.98

0.9465

24.43

75.57

P (ppm)

496.91±43.48

598.78±50.29

577.65±52.43

0.18

2, 6.02

0.8384

38.32

61.68

15

δ N

1.03±0.32

0.76±0.28

0.19±0.39

0.36

2, 6.01

0.7116

31.63

68.37

C (%)

49.50±0.09

49.43±0.07

49.79±0.07

3.02

2, 6.01

0.1239

5.96

94.04

N (%)

1.00±0.04

0.91±0.02

0.93±0.03

1.76

2, 5.99

0.2507

5.86

94.14

P (ppm)

492.74±23.50

457.70±18.49

485.91±20.43

0.20

2, 6.02

0.8256

27.28

72.71

Ca (ppm)

1762.53±64.24

1724.60±70.39

1678.65±58.10

0.63

2, 5.73

0.5678

-2.68

102.68

Mg (ppm)

889.66±43.66

832.31±27.51

876.74±26.93

0.34

2, 5.99

0.7272

11.57

88.43

K (ppm)

6034.75±243.52

6363.65±181.57

6187.55±245.84

0.08

2, 6.00

0.9268

35.17

64.83

Na (ppm)

593.26±93.97

330.54±31.79

323.10±28.16

0.68

2, 6.01

0.5427

32.98

67.02

Fe (ppm)

51.31±3.56

63.19±2.71

64.69±3.52

2.13

2, 5.78

0.2032

11.00

89.00

Mn (ppm)

48.81±5.01

48.13±5.14

61.86±4.79

1.54

2, 5.80

0.2911

7.67

92.33

Zn (ppm)

16.63±1.31

13.69±0.72

14.17±1.13

0.35

2, 5.95

0.7199

24.53

75.47

Cu (ppm)

3.12±0.26

3.01±0.24

3.50±0.27

0.39

2, 6.07

0.6926

19.84

80.16

_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

4.3. CARBON AND NITROGEN ISOTOPIC COMPOSITION The C isotopic composition of pine needles of 2008 was the lowest in NI, followed by CL and SL (Table 1, Fig. 3). The δ13C was not correlated with the N concentrations in needles (P=0.0969; all treatments pooled). Furthermore, an inverse correlation was found among δ13C and shoot growth (R2=-0.21, P=0.030 for shoot biomass; R2=-0.40, P<0.0001 for shoot elongation; all treatments pooled).

Figure 3: Carbon isotopic composition of pine needles from the part of leader shoot elongated in 2008 in the different post-fire treatments of burnt wood. NI: non intervention, CL: cut plus lopping, SL: salvage logging. Different letters above bars indicate significant differences among treatments (Tukey HSD test after mixed ANOVAs).

Conversely, the pattern of isotopic N in the same pine needles was inverse, with the highest values in NI and the lowest in SL, although in this case differences among treatments were not significant (Table 2).

159

Chapter 3_______________________________________________________________________

5. DISCUSSION Results of this study highlight the important role that the remaining burnt wood can have over the growth and performance of regenerating pine seedlings after a wildfire. After three growing seasons, pine seedlings growing in the CL treatment tended, overall, to have greater vigour and size. Moreover, their annual growth (both as annual shoot elongation and biomass) was also higher in CL and NI compared to SL. On the other hand, the nutrient status of pine seedlings did not vary with the silvicultural treatment, likely due to the low plasticity of the nutrient composition of the maritime pine (Bará, 1990; Martins et al., 2009). However, these results would imply greater nutrient uptake by seedlings in the treatments where burnt wood was left in situ. Standing burnt trees and coarse woody debris scattered over the ground can act as shelter structures for the understorey and regenerating vegetation (Perry et al., 1989; Purdon et al., 2004). In a previous study, we verified that the radiation incidence was reduced by the presence of burnt wood by ca. 30%. As a consequence, the soil temperature was ameliorated and the soil moisture increased (Castro et al., 2011). In this study, the lowest C isotopic discrimination of pine seedlings in SL is indicative of higher water use efficiency. In the absence of additional measurements (i.e.: water potential, oxygen isotopic composition), this could be attributed to either a higher photosynthetic capacity or a reduction in stomatal conductance (Scheidegger et al., 2000). However, the growth of seedlings was also the lowest in SL, and the nutritional status neither differed among treatments or was correlated with its isotopic signal. Thus, the evidence does not support the hypothesis of a higher photosynthetic capacity in SL and likely denotes a stronger control of the water losses through evapotranspiration. Therefore, pine seedlings in all probability undergo higher water stress in SL, whereas this limitation is alleviated by the presence of burnt wood in the other treatments.

160

_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

Burnt wood can also represent a potential source of nutrients for the soil that will be progressively released during its decomposition (Brown et al., 1996; Ganjegunte et al., 2004; Harmon et al., 1986; Palviainen et al., 2010a, 2010b; Wei et al., 1997). In fact, the tendencies in the N isotopic composition of needles point to a higher mineralization in the soil where burnt wood was present and ultimately, to more active N cycling among soil, plants, and soil microorganisms (Craine et al., 2009). Trends in isotopic N could, however, be influenced by possible differences in the contribution of symbiotic N fixation among treatments, where in general, plants that rely on soil N are more enriched in 15N than plants that obtain N from symbiotic fixation (Nadelhoffer and Fry, 1994; Craine et al., 2009). Mycorrhization rates are generally higher in poor soils, since the shortage of carbohydrates and available N in soil increase the dependence of the symbiotic association between mycorrhizas and plants to satisfy their requirements (Côrrea et al., 2011; Blanke et al., 2005; Kazantseva et al., 2009). Therefore, the lower values in SL could be also due to the higher mycorrhization rates in pine roots compared to the other treatments, which would be another indication of higher limitation of C and N sources to the soil in this treatment. This would represent further evidence of improved soil conditions for seedling performance provided by the presence of burnt wood. Consequently, pine seedlings incorporate available nutrients from soil while keeping their nutritional status constant. Thus, the nutrient supply provided by woody debris also contributes to faster seedling growth and biomass gains, as well as to higher rates of nutrient uptake and mobilization. Moreover, the accentuated differences in growth parameters in the shoots of the last year suggest that the facilitative effect provided by the remaining wood could be cumulative over time, as the remaining wood releases its nutrients and ameliorates the soil microclimate. The degree of post-fire intervention and management of the remaining wood after a wildfire also determines the magnitude of the prevailing biomass pool, the diameter of wood fractions, and the degree of contact between wood and soil. 161

Chapter 3_______________________________________________________________________

These factors can exert an influence on several ecosystem processes and, in turn, on vegetation recovery (Beghin et al., 2010; Fernández et al., 2008; MartínezSánchez et al., 1999). As an example, in CL a higher degree of contact between wood and soil compared to NI will facilitate the colonization by decomposers and will help to retain in the wood substrate the level of moisture needed for their activity (Harmon et al., 1986). Thus, during the early stages of regeneration, pine seedlings could take advantage of the higher decomposition rates and nutrient releases in this treatment, as shown by the trends of greater total aboveground biomass and basal diameter. Nevertheless, standing burnt trees will fall in the near future, as the basal part of their trunks is also decomposed (Harrington, 1996; Maser and Trappe, 1984), thereby offsetting the differences between NI and CL. In summary, salvage logging implied the removal of most of the wood biomass, thus eliminating this physical protection against extreme microclimatic conditions and extracting the potential source of nutrients that would be released otherwise. This increased water stress in naturally regenerating pine seedlings after the wildfire, and hindered their annual growth and nutrient uptake. By contrast, less aggressive forms of burnt wood management can have important implications for post-fire regeneration in the long term, as their beneficial effects could be cumulative throughout the regeneration process.

6. CONCLUSIONS The results of this study support the contention that salvage logging has a detrimental effect on the growth and performance of pine seedlings in relation to treatments where burnt logs and branches are left in situ. Moreover, the wood remaining after a fire provides two main ecosystem services, ameliorating the microsite conditions, and increasing nutrient availability through wood

162

_______________Post-fire salvage logging decreased Pinus pinaster seedlings performance

decomposition. The more favourable conditions generated as a result not only enhance pine seedling recruitment and survival at early stages (Castro et al., 2011), but also their later growth and performance. This is a key point in Mediterranean and other water- and nutrient-limited ecosystems, where the amelioration of these limiting factors could have important benefits for the regeneration of vegetation (Querejeta et al., 2008; Sardans et al., 2005; Siles et al., 2010). The results of this study should be considered for less intensive management policies devoted to encourage the natural regeneration of vegetation after forest fires.

7. ACKNOWLEDGEMENTS We thank Ángela Sánchez-Miranda and Ramón Ruiz-Puche for their inestimable field and lab assistance, and Susana Hitos and Isabel Sánchez for their work and advice in chemical and isotopic analyses. The Consejeria de Medio Ambiente (Junta de Andalucía) and to the Parque Nacional y Natural de Sierra Nevada offered support in establishing the treatments. This study was financed by the projects (10/2005) of the Organismo Autónomo de Parques Nacionales (MMA), COILEX (CGL2008-01671) of the MICINN, Subprogram for Technical Support (PTA2009-1782-I) of the MICINN, and by a grant FPU-MEC to S.M.J.

163

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Kahmen, A., Wanek, W., Buchmann, N., 2008. Foliar δ15N values characterize soil N cycling and reflect nitrate or ammonium preference of plants along a temperate grassland gradient. Oecologia 156, 861-870. Kappes, H., Catalano, C., Topp, W., 2007. Coarse woody debris ameliorates chemical and biotic soil parameters of acidified broad-leaved forests. Applied Soil Ecology 36, 190-198. Lajtha, K., Marshall, J.D., 1994. Sources of variation in the stable isotopic composition of plants. In: Lajtha, K., Michener, R.H. (Eds.), Stable Isotopes in Ecology and Environmental Science. Methods in Ecology. Blackwell Scientific Publications, Oxford, pp. 1-22. Lindenmayer, D.B., Burton, P.J., Franklin, J.F., 2008. Salvage Logging and its Ecological Consequences. Island Press, Washington. Lindenmayer, D.B., Foster, D.R., Franklin, J.F., Hunter, M.L., Noss, R.F., Schmiegelow, F.A., Perry, D., 2004. Salvage harvesting policies after natural disturbance. Science, 303. Lindenmayer, D.B., Noss, R.F., 2006. Salvage logging, ecosystem processes, and biodiversity conservation. Conservation Biology 20, 949-958. Martínez-Sánchez, J.J., Ferrandis, P., De las Heras, J., Herranz, J.M., 1999. Effect of burnt wood removal on the natural regeneration of Pinus halepensis after fire in a pine forest in Tus valley (SE Spain). Forest Ecology and Management 123, 1-10. Martínez-Sánchez J.J., Marín, A., Herranz, J.M., Ferrandis, P., De las Heras, J., 1995. Effects of high temperatures on germination of Pinus halepensis Mill. and P. pinaster Aiton subsp. pinaster seeds in southeast Spain. Vegetatio 116, 69-72. Martins, P., Sampedro, L., Moreira, X., Zas, R., 2009. Nutritional status and genetic variation in the response to nutrient availability in Pinus pinaster. A multisite field study in Northwest Spain. Forest Ecology and Management 258, 1429-1436. Maser, C., Trappe, J.M., 1984. The seen and unseen world of the fallen tree. USDA Forest Service General Technical Report. Matías, L., Gómez-Aparicio, L., Zamora, R., Castro, J., 2011. Effects of resource availability on plant recruitment at the community level in a Mediterranean mountain ecosystem. Perspectives in Plant Ecology, Evolution and Systematics. doi:10.1016/j.ppees.2011.04.005 McIver, J.D., McNeil, R., 2006. Soil disturbance and hill-slope sediment transport after logging of a severely burned site in northeastern Oregon. Western Journal of Applied Forestry 21, 123-133. McIver, J.D., Starr, L., 2000. Environmental effects of postfire logging: Literature review and annotated bibliography General Technical Report. Portland, U.S. Department

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of Agriculture, Forest Service, Pacific Northwest Research Station. PNW-GTR486., 72. McIver, J.D., Starr, L., 2001. A literature review on the environmental effects of postfire logging. Western Journal of Applied Forestry 16, 159–168. Merino, A., Rey, C., Brañas, J., Soalleiro, R.R., 2003. Biomasa arbórea y acumulación de nutrientes en plantaciones de Pinus radiata D. Don en Galicia. Investigación Agraria: Sistemas y Recursos Forestales 12, 85-98. Nadelhoffer, K.J., Fry, B., 1994. Nitrogen isotope studies in forest ecosystems. In: Lajtha, K., Michener, R.H. (Eds.), Stable Isotopes in Ecology and Environmental Science. Methods in Ecology. Blackwell Scientific Publications, Oxford, pp. 22-45. Neary, D.G., Klopatek, C.C., DeBano, L.F., Ffolliott, P.F., 1999. Fire effects on belowground sustainability: a review and synthesis. Forest Ecology and Management 122, 51-71. Ouro, G., Pérez-Batallón, P., Merino, A., 2001. Effects of sylvicultural practices on nutrient status in a Pinus radiata plantation: Nutrient export by tree removal and nutrient dynamics in decomposing logging residues. Annals of Forest Science 58, 411-422. Palviainen, M., Finer, L., Laiho, R., Shorohova, E., Kapitsa, E., Vanha-Majamaa, I., 2010a. Carbon and nitrogen release from decomposing Scots pine, Norway spruce and silver birch stumps. Forest Ecology and Management 259, 390-398. Palviainen, M., Finer, L., Laiho, R., Shorohova, E., Kapitsa, E., Vanha-Majamaa, I., 2010b. Phosphorus and base cation accumulation and release patterns in decomposing Scots pine, Norway spruce and silver birch stumps. Forest Ecology and Management 260, 1478-1489. Peñuelas, J., Filella, I., Terradas, J., 1999. Variability of plant nitrogen and water use in a 100-m transect of a subdesertic depression of the Ebro valley (Spain) characterized by leaf delta C-13 and delta N-15. Acta Oecol.-International Journal of Ecology 20, 119-123. Pérez-Batallón, P., Ouro, G., Macias, F., Merino, A., 2001. Initial mineralization of organic matter in a forest plantation soil following different logging residue management techniques. Annals of Forest Science 58, 807-818. Perry, D.A., Amaranthus, M.P., Borchers, J.G., Borchers, S.L., Brainerd, R.E., 1989. Bootstrapping in Ecosystems. Bioscience 39, 230-237. Purdon, M., Brais, S., Bergeron, Y., 2004. Initial response of understorey vegetation to fire severity and salvage-logging in the southern boreal forest of Quebec. Applied Vegetation Science 7, 49-60.

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Querejeta, J.I., Barbera, G.G., Granados, A., Castillo, V.M., 2008. Afforestation method affects the isotopic composition of planted Pinus halepensis in a semiarid region of Spain. Forest Ecology and Management 254, 56-64. Quinn, G.P., Keough, M.J., 2009. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge. Reyes, O., Casal, M., 2002. Effect of high temperatures on cone opening and on the release and viability of Pinus pinaster and P. radiata seeds in NW Spain. Annals of Forest Sciences 59, 327-334. Robinson, D., 2001. delta N-15 as an integrator of the nitrogen cycle. Trends in Ecology and Evolution 16, 153-162. Rodrigo, A., Retana, J., Pico, F.X., 2004. Direct regeneration is not the only response of Mediterranean forests to large fires. Ecology 85, 716-729. Sardans, J., Peñuelas, J., Rodá, F., 2005. Changes in nutrient use efficiency, status and retranslocation in young post-fire regeneration Pinus halepensis in response to sudden N and P input, irrigation and removal of competing vegetation. Trees 19 233-250. Scheidegger, Y., Saurer, M., Bahn, M., Siegwolf, R., 2000. Linking stable oxygen and carbon isotopes with stomatal conductance and photosynthetic capacity: a conceptual model. Oecologia 125, 350-357. Siles, G., Rey, P.J., Alcantara, J.M., Bastida, J.M., Herreros, J.L., 2010. Effects of soil enrichment, watering and seedling age on establishment of Mediterranean woody species. Acta Oecol.-International Journal of Ecology 36, 357-364. Smaill, S.J., Clinton, P.W., Greenfield, L.G., 2008. Postharvest organic matter removal effects on FH layer and mineral soil characteristics in four New Zealand Pinus radiata plantations. Forest Ecology and Management 256, 558-563. Spanos, I., Raftoyannis, Y., Goudelis, G., Xanthopoulou, E., Samara, T., Tsiontsis, A., 2005. Effects of postfire logging on soil and vegetation recovery in a Pinus halepensis Mill. forest of Greece. Plant and Soil 278, 171-179. Stark, K.E., Arsenault, A., Bradfield, G.E., 2006. Soil seed banks and plant community assembly following disturbance by fire and logging in interior Douglas-fir forests of south-central British Columbia. Canadian Journal of Botany-Revue Canadienne De Botanique 84, 1548-1560. Stoddard, M.T., Huffman, D.W., Alcoze, T.M., Fule, P.Z., 2008. Effects of slash on herbaceous communities in pinyon-juniper woodlands of northern Arizona. Rangeland Ecology and Management 61, 485-495. Tapias, R., Gil, L., Fuentes-Utrilla, P., Pardos, J.A., 2001. Canopy seed banks in Mediterranean pines of southeastern Spain: a comparison between Pinus

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halepensis Mill., P. pinaster Ait., P. nigra Arn. and P. pinea L. Journal of Ecology 89, 629-638. Trabaud, L., 1994. The effect of fire on nutrient losses and cycling in a Quercus coccifera garrigue (southern France). Oecologia 99, 379-386. Wei, X., Kimmins, J.P., Peel, K., Steen, O., 1997. Mass and nutrients in woody debris in harvested and wildfire-killed lodgepole pine forests in the central interior of British Columbia. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 27, 148-155. West, A., Midgley, J., Bond, W.J., 2001. The evaluation of δ13C isotopes of trees to determine past regeneration environments. Forest Ecology and Management 147, 139–149. Whelan, R.J., 1995. The Ecology of Fire. Cambridge Studies in Ecology. Cambridge University Press. Cambridge. Wondzell, S.M., 2001. The influence of forest health and protection treatments on erosion and stream sedimentation in forested watersheds of eastern Oregon and Washington. Northwest Science 75, 128-140. Zhou, L., Dai, L., Gu, H., Zhong, L., 2007. Review on the decomposition and influence factors of coarse woody debris in forest ecosystem. Journal of Forest Research 18, 48-54.

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CHAPTER 4: POST-FIRE SOIL RESPIRATION IN RELATION TO BURNT WOOD MANAGEMENT IN A MEDITERRANEAN MOUNTAIN ECOSYSTEM

Sara Marañón-Jiménez, Jorge Castro, Andrew S. Kowalski, Penélope Serrano-Ortiz, Borja Ruíz Reverter, Enrique Pérez Sánchez-Cañete, Regino Zamora.

Published in: Forest Ecology and Management 261, 1436-1447

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ABSTRACT After a wildfire, the management of burnt wood may determine microclimatic conditions and microbiological activity with the potential to affect soil respiration. To experimentally analyze the effect on soil respiration, we manipulated a recently burned pine forest in a Mediterranean mountain (Sierra Nevada National and Natural Park, SE Spain). Three representative treatments of post-fire burnt wood management were established at two elevations: 1) “Salvage Logging” (SL), where all trees were cut, trunks removed, and branches chipped; 2) “Non Intervention” (NI), leaving all burnt trees standing; and 3) “Cut plus Lopping” (CL), a treatment where burnt trees were felled, with the main branches lopped off, but left in situ partially covering the ground surface. Seasonal measurements were carried out over the course of two years. In addition, we performed continuous diurnal campaigns and an irrigation experiment to ascertain the roles of soil temperature and moisture in determining CO2 fluxes across treatments. Soil CO2 fluxes were highest in CL (average of 3.34±0.19 μmol m-2s-1) and the lowest in SL (2.21±0.11 μmol m-2s-1). Across seasons, basal values were registered during summer (average of 1.46±0.04 μmol m-2s-1), but increased during the humid seasons (up to 10.07±1.08 μmol m-2s-1 in spring in CL). Seasonal and treatment patterns were consistent at the two elevations (1477 and 2317 m a.s.l.), although respiration was half as high at the higher altitude. Respiration was mainly controlled by soil moisture. Watering during the summer drought boosted CO2 effluxes (up to 37±6 μmol m-2s-1 just after water addition), which then decreased to basal values as the soil dried. About 64% of CO2 emissions during the first 24 h could be attributed to the degasification of soil pores, with the rest likely related to biological processes. The patterns of CO2 effluxes under experimental watering were similar to the seasonal tendencies, with the highest pulse in CL. Temperature, however, had a weak effect on soil respiration, with Q10 values of ca. 1 across seasons and soil moisture conditions. These results represent a first step towards illustrating the effects of post-fire burnt wood management on soil respiration, and eventually carbon sequestration. Keywords: Rain events, salvage logging, silvicultural treatments, soil CO2 fluxes, soil pore degasification, soil temperature, wildfire.

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1. INTRODUCTION Wildfires radically disturb carbon pools, leading to a sudden release of carbon to the atmosphere by combustion of vegetation and litter in soil (Brais et al., 2000; Conard et al., 2002; Page et al., 2002; Trabaud, 2004; Van der Werf et al., 2003). Furthermore, after the fire the ecosystem acts as a source of carbon for months to years as soil respiration exceeds photosynthesis (Amiro et al., 2003; Bond-Lamberty et al., 2007; Harden et al., 2000; Litvak et al., 2003). The magnitude of the soil CO2 efflux after the fire depends on climatic factors (Almagro et al., 2009; Davidson et al., 1998; Kirschbaum, 2000; Lloyd and Taylor, 1994) and the recovery of the vegetation (Irvine et al., 2007; Litton et al., 2003; Yanai et al., 2000). Overall, post-fire soil respiration increases with improving soil microclimatic conditions (non-limiting soil moisture and warm temperatures; Carlyle and Bathan, 1988), with the presence of carbon substrates in soil (Coleman et al., 2004; Franzluebbers et al., 2001), and with primary productivity of vegetation (Craine et al., 1998; Janssens et al., 2001; Knapp et al., 1998; Mkhabela et al., 2009). Studies of the effects of fire on soil respiration are relatively abundant and often compare a burnt area versus a reference ecosystem (e.g. Dore et al., 2010; Hamman et al., 2008; Hubbard et al., 2004; Kobziar, 2007; McCarthy and Brown, 2006) or address the progression of soil CO2 fluxes during ecosystem recovery (e.g. Gough et al., 2007; O´Neill et al., 2006; Yermakov and Rothstein, 2006). Despite the need to assess the impact of different forest management practises for sustainable carbon management (Peng et al., 2008), there is scant information about the effects of burnt wood management on soil respiration after wildfire (see Irvine et al., 2007; Mkhabela et al., 2009). Post-fire wood management has the potential to strongly affect the magnitude of the soil CO2 efflux, as burnt logs, snags or coarse woody debris can determine key factors for respiration. For

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example, microclimatic conditions (soil moisture, soil temperature) can differ depending on the amount of woody debris scattered on the ground (Castro et al., 2011; Smaill et al., 2008; Stoddard et al., 2008). Burnt wood also has a high nutrient content (Johnson et al., 2005; Kappes et al., 2007; Merino et al., 2003), which might improve soil fertility by providing nutrients and organic substrates (Coleman et al., 2004; Grove and Meggs, 2003; Harmon et al., 1986), thus favouring microbial abundance and soil respiration rates (Hamman et al., 2008; Mabuhay et al., 2006; Trumbore et al., 1996). As a consequence of the above processes, vegetation cover and development may differ with burnt-wood management (Stark et al., 2006), which will also affect soil respiration (Burton et al., 2000; Nadelhoffer, 2000; Tang et al., 2005). Salvage logging is a common post-fire silvicultural management practice for burnt wood around the world (Castro et al., 2010; Donato et al., 2006; Lindenmayer and Noss, 2006; Van Nieuwstadt et al., 2001). This practice consists of felling and removing burnt trunks, and is often combined with the elimination of the remaining woody debris (branches, logs, and snags) by chipping, grinding, mastication, or fire (Beschta et al., 2004; McIver and Starr, 2001). Salvage logging is employed for numerous reasons including silvicultural (e.g.: site improvement for plantation or natural regeneration, access, fire risk prevention), economic (value of the salvaged wood products), aesthetics, and safety (Castro et al., 2010; McIver and Starr, 2001). Some of these justifications are controversial, however (Castro et al., 2010; DellaSala et al., 2006; Donato et al., 2006; Lindenmayer and Noss, 2006), and there is increasing support for less aggressive management policies for burnt wood in the post-fire landscape, based on the contention that burnt wood can enhance ecosystem functioning (Beschta et al., 2004; Castro et al., 2010, 2011; Donato et al., 2006; Lindenmayer and Noss, 2006). However, we are not aware of any study on the impact of salvage logging on soil CO2 effluxes. This is a key

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question for optimizing post-fire forest restoration plans to mitigate the destruction of natural CO2 sinks by wildfires. In this study, we analyze the effects of different post-fire wood managements on the magnitude of soil respiration in a burned pine forest. We established three experimental treatments that differed in degree of burnt wood management, ranging from the conventional salvage logging to non intervention. We hypothesize that this will influence the magnitude of soil respiration, as the treatments contrast sharply in ecosystem characteristics such as microclimatic conditions and nutrient availability. Different elevations also imply a variation in the climatic conditions, which also may determine the vegetation composition, decomposition rates and nutrient dynamic in the ecosystem. For that, measurements were performed at seasonal intervals over the course of two years, and at two altitudes to assess spatial and temporal variation in soil respiration. Continuous 24-h campaigns and a watering experiment were also performed to discern the main factor (soil temperature versus soil moisture) determining differences in CO2 effluxes among treatments. The objectives of this study are: 1) to analyze the effect of post-fire burnt wood management on soil respiration at different altitudinal levels; 2) to determine the seasonal and daily patterns of soil CO2 fluxes in this Mediterranean mountain ecosystem; and 3) to determine the roles of soil moisture and temperature on soil respiration across treatments.

2. MATERIAL AND METHODS 2.1. STUDY AREA The study site is located in the Sierra Nevada Natural and National Parks (SE Spain), where the Lanjarón wildfire burned ca. 1300 ha of reforested pine between 35 and 45 years old in September 2005. Four sites of around 25 ha each

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along an altitudinal gradient were established to analyze the effect of burnt wood management on ecosystem regeneration and functioning (see Castro et al., 2011 for further details on experimental set-up). The lowest (LE hereafter) and highest (HE) elevations were selected for this study of soil respiration. LE is located at 1477 m a.s.l. (UTM position x, y: 456070; 4089811) and HE at 2317 m a.s.l. (UTM position x, y: 457719; 4091518). The pine species present before fire at each elevation differed, with Pinus pinaster and Pinus nigra dominating in LE and Pinus sylvestris in HE. The climate is Mediterranean-type, with rainfall concentrated in spring and autumn, alternating with hot dry summers. In LE, mean annual precipitation is 470±50 mm, with summer precipitation (June, July and August pooled) of 17±4 mm (1988-2008; climatic data from a meteorological station beside the site). Snow falls during winter, usually persisting from November to March above 2000 m a.s.l. The mean annual temperature is 12.3±0.4ºC at 1652 m a.s.l. (State Meteorological Agency, period 1994-2008. Ministry of Environment) and 7.8±0.7ºC at 2300 m a.s.l. (data from metereological station placed in HE; period 2008-10). Both elevations were homogeneous in terms of fire intensity (high), aspect (southwest exposure), and bedrock (michaschists). The slope is between 25-30% in LE and 15-20% in HE. Tree density before burning was 1480±50 ha-1 for LE and 1060±50 ha-1 for HE, with a mean height of 6.36±0.06 m and a mean d.b.h. of 13.34±0.17 cm. No trees survived inside the study area, current vegetation is mainly composed of grasses and forbs. The most common perennial species were Ulex parviflorus, Festuca scariosa, Dactylis glomerata and Euphorbia flavicoma in LE, and Genista versicolor, Festuca spp., and Sesamoides prostrata in HE.

2.2. EXPERIMENTAL DESIGN From March to May 2006 (ca. seven months after the fire) we established in LE and HE three representative post-fire burnt wood managements that differed in 177

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degree of intervention (treatments hereafter): 1) “Salvage Logging” (SL), trees were cut and the trunks cleaned of branches by chainsaw. Trunks were piled manually in groups of 10-12, and the woody debris was chipped by machine. Trunks were later removed from the site with a log forwarder, 2) “Non Intervention” (NI), leaving all of the burnt trees standing. Trees fell naturally and progressively over the years, with ≥88.6±1.9% still standing during this study; and 3) “Cut plus Lopping” (CL), a treatment where trees were felled (100% felled in HE; ca. 90% felled in LE), the main branches lopped off, and all wood left in situ on the ground. Burnt logs and branches diffusely covered around 45% of the surface at ground level (Castro et al., 2011). Each treatment was applied to a homogeneous area of at least 2 ha, adjacent to each other at each elevation. In May 2007, 20 PVC collars per treatment at each elevation (diameter 10.5 cm x height 9 cm; 120 collars in total) were inserted in the soil to ca. 5 cm depth, randomly distributed over an area of ca. 1 ha and separated by at least 10 m. For CL, we used a stratified random procedure, in which the collars were randomly installed in areas below the burnt branches. Soil respiration measurements were performed on the collars for purposes of determining two types of patterns: seasonal and diurnal.

2.3. SOIL RESPIRATION ACROSS SEASONS Soil respiration was measured in summer 2007 (four times), autumn 2007 (twice), spring 2008 (twice), summer 2008 (once), and autumn 2008 (once) in every elevation and treatment (see Appendix A for dates). During winter, snow prevented the access to the study area. Summer measurements were done under typical drought conditions, whereas spring and autumn represented the humid season for the area. Thus, calendar definitions of the seasons coincided with the influence of rainfall on the campaigns (see Appendix B for distribution of rainfall

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over the study period). Measurements were usually performed simultaneously in LE and HE (occasionally separated by one day), from ca. 9 am to 3 pm. We used two CO2 analyzer systems: the manual EGM-4/SRC-1 (PP-Systems, Hitchin, UK); and an automated Li-Cor 8100 (Lincoln, NE, USA). CO2 measurements made with the PP-Systems were calibrated against the Li-Cor 8100. A comparison was performed on 31 October 2007 in which simultaneous soil respiration records were taken alternatively with both instruments on the same collars (n=48, using collars of the three treatments). Data from the two different devices were correlated (R2=0.88), and those from the EGM-4 (PP-Systems) were corrected using the resulting linear regression (offset=0.197 μmol m-2s-1; slope=1.095). Soil CO2 fluxes were taken together with soil temperature at ca. 5 cm depth (two measurements per collar; digital thermometer probe). The order of measurement was rotated among the three treatments over the campaigns. Vegetation inside the collars was not removed since it was considered an effect of the management treatment. Thus, soil respiration reported in this study could include some above-ground autotrophic respiration. Vegetation cover was estimated visually from 0 to 100% for each campaign (Sutherland, 1996). The effect of soil water content on soil respiration was explored using the rewetting index parameter (IR) which has shown good correlation with CO2 effluxes in a Mediterranean ecosystem (Almagro et al., 2009): IR=P/t, where P is precipitation (mm) and t is time elapsed (days) between rainfall event and soil respiration measurements. 2.4. DIURNAL PATTERNS OF SOIL RESPIRATION Measurements of the diurnal CO2 fluxes allowed us to investigate the complete daily pattern of soil respiration in the different treatments and to isolate the dependence on temperature from other interacting environmental variables that can influence soil respiration (e.g.: herbaceous cover, phenological differences, soil moisture, microbial biomass and diversity, SOM content) remained relatively

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constant. For this purpose, soil respiration was measured over a cycle of 24 hours in one representative collar of each treatment in HE, using the Li-Cor 8100 programmed to take a measurement every 30 min. Soil temperature was measured every 10 min at 5 cm depth with 4 thermistors (TMC-HD, Onset Computer Corporation, Massachusetts, USA) connected to data loggers (HOBO H8, Onset Computer Corporation, Massachusetts, USA) within ca. 10 cm of the collar. Temperature was averaged and synchronized every 30 min with the corresponding CO2 flux value. Measurements were performed during the mid-summer (07/1012/2007, representing dry conditions), late summer (09/16-19/2007, dry conditions before the end of the drought period, Appendix B) and late spring (06/27-29/2009, during the period of highest soil respiration according to the observed seasonal values from the previous year). 2.5. EXPERIMENTAL ANALYSIS ON THE EFFECT OF SOIL MOISTURE Given the evidence of strong effects of water availability and weak response to soil temperature derived from seasonal and diurnal campaigns (see results), we performed a field experiment to disentangle the role of these two factors on soil CO2 fluxes. In summer 2009, one week to prior the experiment, four additional collars were installed randomly in each treatment in HE, separated by at least 10 m from each other and from the previous collars. At the beginning of the experiment, an area of 50x50 cm2 surrounding each of these collars was delimited and irrigated with 5 L of water, uniformly distributed over the 0.25 m2 surface. The quantity of water (20 mm) was chosen to simulate a typical summer storm according to the record of storms registered for Sierra Nevada (Mendoza et al., 2009). Following water addition, soil CO2 effluxes were measured on the irrigated collars to determine two types of patterns: across days and diurnal.

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For patterns across days, we measured CO2 fluxes (EGM-4), soil temperature (5 cm deep) and gravimetric soil moisture (10 cm deep) in three collars of each treatment one day before, just after, and 1, 3, 5, 7, 10, 15 and 20 days after irrigation (from 29-July to 19-August 2009), alternating the order of measurements in each treatment. Gravimetric soil moisture was calculated as the difference between wet and dry weight of the soil fraction <2 mm after oven-drying at 60ºC to constant weight. For this, one soil sample at 0-10 cm depth was taken from within the delimited perimeter surrounding each collar on every sampling date. Simultaneously, CO2 fluxes and soil temperatures were also measured in five nonirrigated collars in each treatment, which were taken as a drought-condition reference. For diurnal patterns, we measured CO2 fluxes (with the Li-8100) and temperature (with HOBO H8 loggers, 5 cm deep) at one collar of each treatment synchronized as described above. These measurements were carried out one day prior to irrigation, on the same day of the irrigation, and 3, 5 and 7 days after the irrigation. Three soil samples per collar (10 cm deep) were also taken on each of these days to determine gravimetric soil moisture.

3. DATA ANALYSIS 3.1. EFFECTS OF TREATMENTS, SEASONS AND ALTITUDINAL LEVELS ON SOIL RESPIRATION The treatment effect on soil CO2 effluxes and its variation across seasons was analyzed with a repeated-measure analysis of variance (rmANOVA) split-plot design, in which Treatment was considered the main plot factor, and Season (with five levels; summer 2007 and 2008, autumn 2007 and 2008, and spring 2008) the subplot factor (Potvin, 2001). The analysis was thus run with mean values per collar for each season. This allowed us to balance the design for the season factor

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and also produce integrated data of soil respiration per season. In any case, we also performed rmANOVA considering each date as a within factor level (10 campaigns), yielding similar results (data not shown; see Appendix A for values per date). Differences between elevations were tested for each season with one-way ANOVAs pooling data of the three treatments. The relationship between soil CO2 effluxes and herbaceous cover inside the collars was analyzed using a Spearman-rank correlation. The analyses were restricted to the two campaigns in the spring period (15-April and 19-May 2008: mean of 35.1±2.3%; all treatments, dates and elevations pooled), since herbaceous cover was very low in other seasons (summer: mean of 0.51±0.24%; autumn: mean of 9.0±0.8%; all treatments, dates and elevations pooled). Differences in herbaceous cover among treatments were tested with a one-way ANOVA for each date and elevation. The relationship between the mean CO2 flux for each date (all treatments pooled) and the rewetting index was tested using a Spearman-rank correlation.

3.2. EFFECT OF EXPERIMENTAL WATERING The effect of experimental water addition on soil CO2 effluxes and their variation across treatments and days after irrigation (time) was analyzed with a rmANOVA, with time defined as a within factor and treatment and irrigation as between factors (day before water addition were excluded of the analysis). Differences between treatments and time in soil moisture among the irrigated collars were similarly tested with rmANOVA. The relationship between soil moisture and CO2 efflux in the irrigated collars was explored by Spearman-rank correlation. For this correlation, data measured in the first 2 h after irrigating were excluded from the analysis since we interpreted their rapid exponential decay as resulting from degassing of the CO2 in soil pores displaced by water, an emission

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not directly associated with biological processes. This was evaluated by logtransforming the data of continuous CO2 effluxes and fitting linear equations to the time course of these measurements (see Appendix C). 3.3. EFFECT OF SOIL TEMPERATURE The effect of temperature on soil CO2 fluxes was analyzed for all the continuous diurnal measurements, both in irrigated and non-irrigated collars. For this purpose, Fc from each campaign was fitted versus soil temperature (Ts) using the following equation describing the response of soil respiration to soil temperature (Curiel-Yuste et al., 2004): Fc =R15Q10(Ts-15)/10 (1) with two fitting parameters: R15 is the respiratory flux predicted at 15ºC and Q10 is the factor of increasing respiration for a 10ºC rise in soil temperature. Data were log- or angular-transformed when required to improve normality and homoscedasticity (Quinn and Keough, 2009). Statistical analyses and models were made with JMP 7.0 software (SAS Institute). Throughout the paper, values of soil respiration are expressed in units of μmol m-2s-1. Mean values are followed by ±1SE.

4. RESULTS: 4.1. SOIL RESPIRATION ACROSS TREATMENTS, SEASONS AND ALTITUDINAL LEVELS Soil respiration differed among treatments and seasons in both elevations (Table 1). At the lower elevation, respiration was overall higher in CL (5.1±0.4; all campaigns pooled) than in NI (3.52±0.24) and SL (3.28±0.22; Fig. 1). The same

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pattern was registered at the higher elevation, with higher values in CL (2.29±0.16) than NI (2.07±0.17) and SL (1.50±0.10; Fig. 1). Among seasons, fluxes were much lower during summer than during spring and autumn for both elevations (mean of 2.08±0.10 in summer, 6.8±0.6 in spring and 4.45±0.18 in autumn for LE; 0.79±0.05 in summer, 2.35±0.17 in spring and 2.91±0.13 in autumn for HE; Fig. 1). An interaction emerged between treatment and season (Table 1), with CL clearly identified as the treatment with the highest soil CO2 fluxes in spring (Fig. 1). Respiration was always higher in LE than in HE in all seasons (P≤0.001, Fig. 1; mean of 3.97±0.17 and 1.95±0.09, respectively; treatments pooled).

Table 1: Summary of repeated measures analysis of variance (rmANOVA) for the seasonal CO2 fluxes. Analyses were performed with the mean value of CO2 fluxes measured at each collar by season. df: degrees of freedom of the numerator and denominator, respectively. F: value of the F statistic. Approximate value of F adjusted for the Season*Treatment interaction (Wilk`s-Lambda multivariate test). P: critical probability of the analysis.

Source

Low Elevation

High Elevation

df

F

P

df

F

P

2, 57

9.51

0.0003

2, 56

5.41

0.0071

Season

4, 54

96.29

<0.0001

4, 53

227.65

<0.0001

Season*Treatment

8, 108

5.10

<0.0001

8, 106

9.77

<0.0001

Between-subject Treatment Within -subject

Error

184

57

56

____________________________________Burnt wood management effect on soil respiration

Figure 1: Mean soil CO2 effluxes in the different altitudinal levels and post-fire silvicultural treatments over the seasons. Abbreviations for altitudinal levels and treatments: LE: low elevation (1477 m a.s.l); HE: high elevation (2317 m a.s.l.); SL: salvage logging; NI: non intervention; CL: cut plus lopping. Each bar represents the mean CO2 efflux for the 20 collars per treatment and elevation. Standard error of each mean is represented over each bar. Different letters above bars indicate significant differences between treatments within elevation and season according to Tukey test after one way-ANOVA.

Soil CO2 fluxes were positively correlated with green herbaceous cover inside the collars for the spring campaigns (ρ=0.41, P<0.0001, n=119 in LE and ρ=0.28, P<0.0028, n=109 in HE). Herbaceous cover inside the collars differed among treatments. On 15 April, it was higher in CL than SL and NI for both elevations (76±8%, 46±8% and 35± 5% respectively for LE; 47±9%, 12±2% and 11±4% for HE; P≤0.0004). On 19 May, the herbaceous cover in HE was also

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higher in CL than in NI and SL (24±5%, 8±2% and 4±1%, respectively; P=0.0002), whereas there were no differences among treatments in LE (56±8%, 38±5% and 50±8%, respectively; P=0.1828). For both elevations, soil fluxes were positively correlated with the rewetting index (ρ=0.83 in LE and ρ=0.98 in HE, P<0.0001). 4.2. EFFECT OF EXPERIMENTAL WATERING Soil moisture differed between sampling dates (P<0.0001) and was similar among treatments (P>0.05, no significant interactions). It peaked on the day of irrigation, and then decreased gradually in all cases (Fig. 2A). Irrigation stimulated soil CO2 effluxes in the three treatments, with a strong effect of date (Table 2). For the irrigated collars, soil CO2 effluxes spiked within 60 s after water addition, reached a peak on the same day (ca. 47 times the previous value before water addition) and fell rapidly during ca. 2 h due to soil pore degasification, which accounted for ca. 51-87% of emissions, depending on treatment, during the first 24 h after water addition (Fig 3; see Appendix C). Respiratory fluxes then decreased toward basal values prior to the irrigation (Fig. 2B). Soil efflux peaks following irrigation were highest in CL, followed by SL, and were lowest in NI (Fig. 2B). Soil CO2 effluxes in the reference collars without irrigation also varied with date (Table 2) but these effects can be attributed to a precipitation event that occurred thirteen days after the beginning of the experiment (12 August), which stimulated CO2 effluxes and soil moisture measured on days 15 and 20 (14 and 19 August) of the experiment (Fig. 2C). Soil CO2 effluxes in the irrigated collars were positively correlated to gravimetric soil moisture (ρ=0.62, P<0.0001).

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____________________________________Burnt wood management effect on soil respiration

Figure 2: (A) Soil moisture, (B) CO2 effluxes in irrigated collars, and (C) CO2 effluxes in reference collars not stimulated by water addition) in the different post-fire silvicultural treatments several days after the experimental watering. Arrows indicate the days when the water addition was performed and when the natural rain event occurred. CL: cut plus lopping; NI: non intervention; SL: salvage logging.

df

F

P

Irrigation

1, 16

13.93

0.0018

Treatment

2, 16

5.83

0.0125

Irrigation*Treatment

2, 16

6.94

0.0068

Source Between-subject

Table 2: Summary of repeated measures analysis of variance (rmANOVA) for CO2 fluxes after experimental irrigation. df: degrees of freedom of the numerator and denominator, respectively. F: value

Within -subject Time

7, 10

32.04

<0.0001

of the F statistic. Approximate value of

Time*Irrigation

7, 10

41.68

<0.0001

F adjusted for the Time*Treatment and

Time* Treatment

14, 20

3.79

0.0023

Time*Treatment*Elevation interactions

Time*Irrigation*Treatment

14, 20

3.76

0.1037

(Wilk`s-Lambda multivariate test). P:

Error

16

critical probability of the analysis.

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4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 -0.5

B

C

Log CO2 effluxes

A

0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5

Hour

Hour

Hour

Figure 3: Soil CO2 effluxes (logarithmic scale) just after the water irrigation (9:00 am, local hour) over the first 24 h in (A) cut plus lopping (CL), (B) non intervention (NI) and (C) salvage logging (SL). Open symbols and continuous lines correspond to effluxes and linear regressions during the respiration period (r) respectively, solid and asterisks symbols and dotted lines correspond to the linear regressions during the degassing period (d) respectively (see Appendix C). (Linear fitted equations for the respiration period: Y=2.752-0.0512*X, R2=0.81 in CL; Y=2.591-0.0904*X, R2=0.93 in NI; Y=1.352-0.0736*X, R2=0.82 in SL; and for the degassing period: Y=4.4560.9341*X, R2=0.97 in CL; Y=3.851-0.8021*X, R2=0.99 in NI; Y=3-0.6621*X, R2=0.99 in SL)

4.3. SOIL RESPIRATION SENSITIVITY TO DIURNAL TEMPERATURE OSCILLATIONS Fitted values for the parameter Q10 were very low for all treatments and seasons (between 1.29 and 0.98, R2<0.10 and P>0.05 for most cases). Due to this lack of temperature dependence (Fig. 4), the parameter R15 showed the same pattern as the mean values of CO2 fluxes, with the highest values registered in CL for all campaigns. Soil CO2 fluxes under experimental watering also showed low temperature sensitivity (Fig. 5). Overall, the temperature dependence of CO2 fluxes increased very slightly in the absence of water limitations (3 days after irrigation) and fell again as the soil dried out (7 days after irrigation, Table 3). Again, R15 showed the same pattern as mean of the fluxes for every date, being always higher in CL, followed by NI and then SL (Table 3).

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____________________________________Burnt wood management effect on soil respiration

Figure 4: Half-hourly soil CO2 effluxes and soil temperatures in the highest elevation over 24 hours. Two sampling dates are represented: (A) Late summer (16-19 September 07); (B) late spring (27-29 May 09). Measurements started at 11:00 am (local hour) and lasted 24 h. (GMT is displayed in the x axes). CL: cut plus lopping; NI: non intervention; SL: salvage logging.

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Figure 5: Half-hourly measurements of soil CO2 effluxes and soil temperature following the irrigation field experiment in the highest elevation over 24 hours. Data from four sampling dates are represented: (A) before irrigation, (B) the day of irrigation, (C) three days after irrigation, and (D) seven days after irrigation. Measurements started at 9:00 am (local hour) and lasted 24 h. CO2 effluxes measures in B) from 9:30-11:30 am are not shown since they cannot be directly attributed to biological emissions (see Appendix C). CL: cut plus lopping; NI: non intervention; SL: salvage logging.

190

____________________________________Burnt wood management effect on soil respiration Table 3: Temperature sensitivity of daily soil CO2 fluxes several days after the water addition treatment. Values of Q10 and R15 parameters were obtained by fitting measured CO2 fluxes and simultaneous soil temperature to the exponential model of the Eq. (1) dependent of soil temperature. R2 is the coefficient of correlation between measured and modelled data. Parameters for soil CO2 fluxes during the day of water addition were not calculated, now that theses fluxes are not temperature dependent but soil moisture dependent. CL: cut plus lopping; NI: non intervention; SL: salvage logging.

Treatment Days after water addition Soil moisture (%)1 CL

Q10

R15

R2

3.20±0.35

1.00±0.01 1.07±0.02 0.01

1.24±0.20

1.02±0.01 0.95±0.02 0.15

0.86±0.08

1.75±0.19 0.02±0.01 0.55

9.29±1.54

1.07±0.02 1.99±0.08 0.25

6.12±0.08

1.07±0.01 1.75±0.07 0.37

SL

5.71±0.82

1.10±0.05 0.48±0.06 0.29

CL

4.02±0.81

1.03±0.01 1.23±0.02 0.15

2.91±0.17

1.03±0.01 1.22±0.02 0.21

1.94±0.09

1.16±0.04 0.17±0.01 0.35

NI SL

1 day before (summer drought)

CL NI

NI SL

3 days after

7 days after

1

Mean of the gravimetric soil moisture of three soil samples taken inside the delimited perimeter of one collar per treatment.

5. DISCUSSION: In this study we have analyzed post-fire soil respiration considering burnt wood management and other environmental factors with the potential to affect respiration. The pattern of soil respiration was variable in time and space. On one hand, differences in altitudinal level yielded ca. twofold differences in respiration. On the other hand, soil CO2 fluxes exhibited strong seasonality, with highest values in spring and basal values during the summer drought (see Almagro et al., 2009; Rey et al., 2002; for similar patterns). Overall, this study shows three main noteworthy factors that determine rates of CO2 effluxes after fire in this Mediterranean ecosystem: 1) soil respiration is mostly determined by water

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availability, whereas soil temperature has a marginal effect; 2) soil respiration is substantially and consistently affected by burnt wood management; and 3) rain events during the dry season strongly impact soil CO2 effluxes and reinforce the role of burnt wood management. 5.1. EFFECT OF SOIL MOISTURE AND TEMPERATURE Soil moisture and temperature are the main drivers of soil CO2 effluxes (Davidson et al., 1998; Lloyd and Taylor, 1994). The combination of these two factors is particularly critical in Mediterranean ecosystems, where high temperature in summer is coupled with limiting soil moisture (Carlyle and Bathan, 1988; Davidson et al., 1998; Reverter et al., 2010; Xu and Qi, 2001). The effect of water availability on respiration was clear in this study as seen both indirectly (correlation with the rewetting index; seasonal variation of CO2 fluxes, with basal values in summer and maximum values in spring) as well as by experimental manipulation of water availability (see Almagro et al., 2009; Liu et al., 2002; Rey et al., 2002; Xu et al., 2004; for similar results). The effect of soil temperature was, by contrast, almost irrelevant. This is an expected result for the dry period (summer), when limiting soil moisture overshadows the role of temperature (Carlyle and Bathan, 1988; Davidson et al., 1998; Serrano-Ortiz et al., 2007; Sowerby et al., 2008; Xu and Qi, 2001). This result is reinforced by the restriction of the temperature sensitivity analysis to diurnal measurements at a single collar (per treatment), thus avoiding the potentially confounding and interacting effects of spatial variability, primary productivity and phenology (Curiel-Yuste et al., 2004; Janssens et al., 2001). In any case, soil fluxes at seasonal scales also showed very weak temperature sensitivity during drought conditions (data not shown). However, low values of Q10 were similarly encountered during spring (although slightly higher than in

192

____________________________________Burnt wood management effect on soil respiration

summer), as well as in the controlled irrigation experiment. This contrasts with results in most of the studies for both seasonal and diurnal fluxes in un-burnt Mediterranean climates (Raich and Schlesinger, 1992; Reichstein et al., 2002; Rey et al., 2002; Tang et al., 2003, 2005; Xu and Qi, 2001) and suggests that factors other than water limitation could be restricting the diurnal effect of soil temperature; these might include the repression of the microbial activity by the extremely high temperatures reached in the soil during the midday (Killham, 1994; Luo and Zhou, 2006; Tang et al., 2003) and during the fire (Garcia-Oliva et al., 1999; Saa et al., 1998; Zhang et al., 2005). In addition, heat and CO2 transport processes can influence Q10 values calculated from regressions of surface flux and soil temperature measured at a single depth (Phillips et al., 2011; Xu and Qi, 2001). Thus, Q10 values could be higher at greater depths. In any case, soil respiration almost halved at the higher elevation. Several factors can be involved in this pattern including lower rate of wood decomposition, lower primary productivity and subsequent root activity and litter deposition (Brischke and Rapp, 2008; Craine et al., 1998; Janssens et al., 2001; Knapp et al., 1998;), but it is very likely that colder temperatures at higher elevation influence respiration differences between altitudinal levels (Kane et al., 2003), whether directly or via interactions with the above-mentioned factors.

5.2. EFFECT OF BURNT WOOD MANAGEMENT Soil respiration was consistently affected by post-fire burnt wood management both across seasons and altitudinal levels, whatever the effects of moisture and temperature. Overall, respiration was highest in the treatment where trees were felled and lopped, leaving the soil partially covered with logs and branches (CL treatment). This may be explained by several factors. First, the decaying wood may supply the soil with nutrients that encourage microbiological

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activity (Coleman et al., 2004; Grove and Meggs, 2003; Harmon et al., 1986). The fact that trees were felled would facilitate wood-soil contact and hence decomposition (Harmon et al., 1986; Maser and Trappe, 1984), explaining the higher respiration rates in CL versus NI. Second, logs and branches spread on the ground can improve microclimate by reducing soil desiccation produced by the extreme soil heating (Castro et al., 2011; see also Smaill et al., 2008; Stoddard et al., 2008 for similar effects of non-burned woody debris). Third, vegetation cover was consistently higher in collars in CL than in the other treatments, which may increase both autotrophic (either above and belowground) and heterotrophic respiration (Reichstein et al., 2003; Tang et al., 2005). This is likely a consequence of higher nutrient availability and microclimatic amelioration (Burton et al., 2000; Irvine et al., 2007; Stark et al., 2006), but altogether exerted a direct effect on soil respiration during spring. We are not aware of studies analyzing the effect of post-fire burnt wood management on soil respiration by means of an experimental design with different levels of intervention. However, Concilio et al. (2006) and Irvine et al. (2007) reported increases in soil respiration following a fire of high intensity due to the presence of slash on the forest floor. In these cases, the increases in soil respiration were attributed to regrowth and nutrient inputs. Burnt wood management alters microclimate, nutrient content or vegetation cover regardless of the ecosystem considered (e.g.: Castro et al., 2011; Coleman et al., 2004; Grove and Meggs, 2003; Harmon et al., 1986; Stoddard et al., 2008). Thus, it is likely that burnt wood would encourage soil microbial activity and respiration rates in the upper soil layers after a wildfire.

194

____________________________________Burnt wood management effect on soil respiration

5.3. EFFECT OF RAIN EVENTS In addition to the positive relationship between soil moisture and respiration, this study shows the strong impact of evenly distributed rain events on soil CO2 effluxes of a Mediterranean ecosystem. The simulation of a summer rain event provoked a CO2 peak that reached ca. 47 times the basal values before the experimental watering. Furthermore, the effects of post-fire treatments are highlighted by the coincident patterns, both in the seasonal measurements of soil respiration and following experimental watering, with the highest values reached in the CL treatment. Vegetation was senescent at the beginning of the irrigation experiment, and no changes in living vegetation cover were observed following irrigation, so the increased soil CO2 effluxes after the first 2 h of the water addition could be attributed mainly to microbial activity. Thus, differences in soil carbon pools like those due to decaying burnt wood can alter both peak and basal respiration rates (Sanderman et al., 2003). Our results strongly suggest that a large fraction (about 64% approx.) of the initial CO2 emitted within ca. 2 h after water addition was related to degasification of CO2-rich air trapped in soil pores. During the dry season, CO2 from the past and from water-limited metabolism would be trapped in soil pores (Inglima et al., 2009; Liu et al., 2002) when the soil is very dry and the low connectivity of soil pores leads to CO2 accumulation. After initial soil degassing, rewetting leads to a cascade of responses (enhanced microbial activity and soluble organic C availability; Luo and Zhou, 2006; Xiang et al., 2008) that mobilizes and metabolizes otherwise unavailable soil carbon. This would explain the high peaks and exponential decrease of CO2 effluxes. Thus, even if differences in soil respiration among treatments were not of a high magnitude during summer, their effect can be cumulative and show up after rain events following a long dry period.

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5.4. MANAGEMENT IMPLICATIONS There is currently an intense debate concerning the appropriate management of burnt trees after forest fires (Beschta et al., 2004; Donato et al., 2006; Lindenmayer et al., 2004; McIver and Starr, 2001). Post-fire salvage logging is implemented worldwide (Castro et al., 2010; Lindenmayer et al., 2004; McIver and Starr, 2001; Van Nieuwstadt et. al., 2001), but recent studies show that it may impact ecosystem function and regeneration (Castro et al., 2010, 2011; Donato et al., 2006; Lindenmayer and Noss, 2006). The present study highlights the capacity of burnt wood management to alter soil CO2 effluxes. Overall, salvage logging was the treatment with the lowest soil respiration, probably because of harsher microclimatic conditions and reduced nutrient availability (see above). Since this pattern was consistent in the two contrasted altitudinal levels of the study, with different dominant tree species before fire disturbance, these results could be extrapolated to other forest ecosystems in water-limited climates. Post-fire management strategies should also be considered for carbon sequestration policies. Their relevance is accentuated given the increase in wildfire intensity and frequency in recent decades due to human factors (Cerdá and MataixSolera et al., 2009; Conard et al., 2002) and predicted climatic change scenarios (IPCC, 2007). Post-fire wood management can determine the rhythm of natural recovery of the ecosystem and net carbon balance by modifying soil parameters. However, the higher soil respiration reported in the “cut plus lopping” treatment does not necessarily imply an increase in net carbon emissions of the burnt area, but rather can be interpreted as a comparative diagnostic tool for soil metabolic activity in relation to forest practices (Weber, 1990). Primary production can equilibrate increases in CO2 effluxes (Irvine et al., 2007), since the herbaceous cover registered during spring was higher in this treatment. Furthermore, the effect of burnt logs, branches or coarse woody debris over the soil may be long-lasting

196

____________________________________Burnt wood management effect on soil respiration

(Smaill et al., 2008), helping to compensate ecosystems fluxes over longer time scales. In order to disentangle the role of the burnt wood management on soil carbon sequestration, complementary studies on ecosystem-atmosphere carbon exchange would be convenient. In any case, this study sets a baseline and is the first that experimentally examines the key importance of post-fire wood management practices on soil CO2 fluxes.

6. ACKNOWLEDGEMENTS: Thanks to Luis Miguel Oviedo and Cécile Lamouroux for their help in the field. Precipitation data were facilitated by Jose Ramón Francia Martínez under the project RTA2007-00008-00-00 of the INIA and cofinanced with FEDER funds of the European Union. We thank to the Consejeria de Medio Ambiente (Junta de Andalucía) and to the Parque Nacional y Natural de Sierra Nevada for support in the establishment of the treatments. This work was financed by the projects (SUM2006-00010-00-00) of the INIA, (10/2005) of the Organismo Autónomo de Parques Nacionales (MMA), GESBOME (P06-RNM-1890) of the Junta de Andalucía, and by a grant FPU-MEC to S.M.J.

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Maser, C., Trappe, J.M., 1984. The seen and unseen world of the fallen tree. Forest Service General Technical Report PNW-164. United States Department of Agriculture, Forest Service, Portland. McCarthy, D.R., Brown, K.J., 2006. Soil respiration responses to topography, canopy cover, and prescribed burning in an oak-hickory forest in southeastern Ohio. Forest Ecology and Management 237, 94-102. McIver J.D., Starr, L., 2001. A literature review on the environmental effects of postfire logging. Western Journal of Applied Forestry 16, 159-168. Mendoza, I., Zamora, R., Castro, J., 2009. A seeding experiment for testing treecommunity recruitment under variable environments: Implications for forest regeneration and conservation in Mediterranean habitats. Biological Conservation 142, 1491-1499. Merino, A., Rey, C., Brañas, J., Soalleiro, R.R., 2003. Biomasa arbórea y acumulación de nutrientes en plantaciones de Pinus radiata D. Don en Galicia. Investigación agraria: Sistemas y Recursos Forestales 12, 85-98. Mkhabela, M.S., Amiro, B.D., Barr, A.G., Black, T.A., Hawthorne, I., Kidston, J., McCaughey, J.H., Orchansky, A.L., Nesic, Z., Sass, A., Shashkov, A., Zha, T., 2009. Comparison of carbon dynamics and water use efficiency following fire and harvesting in Canadian boreal forests. Agricultural and Forest Meteorology 149, 783-794. Nadelhoffer, K.J., 2000. The potential effects of nitrogen deposition on fine-root production in forest ecosystems. New Phytologist 147, 131-139. O’Neill, K.P., Richter, D.D., Kasischke, E.S., 2006. Succession-driven changes in soil respiration following fire in black spruce stands of interior Alaska. Biogeochemistry 80, 1-20. Page, S.E., Siegert, F., Rieley, J.O., Boehm, H.D. V., Jaya, A., Limin, S., 2002. The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420, 61-65. Peng, Y.Y., Thomas, S.C., Tian, D.L., 2008. Forest management and soil respiration: Implications for carbon sequestration. Environmental Reviews 16, 93-111. Phillips, C.L., Nickerson, N., Risk, D., Bond, B.J., 2011. Interpreting diel hysteresis between soil respiration and temperature. Global Change Biology 17, 515-527. Potvin, C., 2001. ANOVA: Experimental layout an analysis, In: Scheiner, S.M., Gurevitch, J. (Eds.), Design and Analysis of Ecological Experiments. Oxford University Press, New York, pp. 63-76. Quinn, G.P., Keough, M.J., 2009. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge.

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Raich, J.W., Schlesinger, W.H., 1992. The global carbon-dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus Series B-Chemical and Physical Meteorology 44, 81-99. Reichstein, M., Rey, A., Freibauer, A., Tenhunen, J., Valentini, R., Banza, J., Casals, P., Cheng, Y., Grünzweig, J.M., Irvine, J., Joffre, R., Law, B.E., Loustau, D., Miglietta, F., Oechel, W., Ourcival, J.-M., Pereira, J.S., Peressotti, A., Ponti, F., Qi, Y., Rambal, S., Rayment, M., Romanya, J., Rossi, F., Tedeschi, V., Tirone, G., Yakir, M.X., 2003. Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices. Global biogeochemical cycles 17, 1104. Reichstein, M., Tenhunen, J.D., Roupsard, O., Ourcival, J.-M., Rambal, S., Dore, S., Valentini, R., 2002. Ecosystem respiration in two Mediterranean evergreen Holm Oak forests: drought effects and decomposition dynamics. Functional Ecology 16, 27-39. Reverter, B.R., Sánchez-Cañete, E.P., Resco, V., Serrano-Ortiz, P., Oyonarte, C., Kowalski, A.S., 2010. Analyzing the major drivers of NEE in a Mediterranean alpine shrubland. Biogeosciences Discussions 7, 671-696. Rey, A., Pegoraro, E., Tedeschi, V., De Parri, I., Jarvis, P.G., Valentini, R., 2002. Annual variation in soil respiration and its components in a coppice oak forest in Central Italy. Global Change Biology 8, 851-866. Saa, A., Trasar-Cepeda, M.C., Carballas, T., 1998. Soil P status and phosphomonoesterase activity of recently burnt and unburnt soil following laboratory incubation. Soil Biology and Biochemistry 30, 419-428. Sanderman, J., Amundson, R.G., Baldocchi, D.D., 2003. Application of eddy covariance measurements to the temperature dependence of soil organic matter mean residence time. Global Biogeochemical Cycles 17. Serrano-Ortiz, P., Kowalski, A.S., Domingo, F., Rey, A., Pegoraro, E., Villagarcia, L., Alados-Arboledas, L., 2007. Variations in daytime net carbon and water exchange in a montane shrubland ecosystem in southeast Spain. Photosynthetica 45, 30-35. Smaill, S.J., Clinton, P.W., Greenfield, L.G., 2008. Postharvest organic matter removal effects on FH layer and mineral soil characteristics in four New Zealand Pinus radiata plantations. Forest Ecology and Management 256, 558-563. Sowerby, A., Emmett, B.A., Tietema, A., Beier, C., 2008. Contrasting effects of repeated summer drought on soil carbon efflux in hydric and mesic heathland soils. Global Change Biology 14, 2388-2404. Stark, K.E., Arsenault, A., Bradfield, G.E., 2006. Soil seed banks and plant community assembly following disturbance by fire and logging in interior Douglas-fir forests of south-central British Columbia. Canadian Journal of Botany-Revue Canadienne De Botanique 84, 1548-1560.

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Stoddard, M.T., Huffman, D.W., Alcoze, T.M., Fule, P.Z., 2008. Effects of slash on herbaceous communities in pinyon-juniper woodlands of northern Arizona. Rangeland Ecology and Management 61, 485-495. Sutherland, W.J., 1996. Ecological Census Techniques: A Handbook. Cambridge University Press. Cambridge. Tang, J.W., Baldocchi, D.D., Qi, Y., Xu, L.K., 2003. Assessing soil CO2 efflux using continuous measurements of CO2 profiles in soils with small solid-state sensors. Agricultural and Forest Meteorology 118, 207-220. Tang, J., Misson, L., Gershenson, A., Cheng, W., Goldstein, A.H., 2005. Continuous measurements of soil respiration with and without roots in a ponderosa pine plantation in the Sierra Nevada Mountains. Agricultural and Forest Meteorology 132, 212-227. Trabaud, L., 2004. The effect of fire on nutrient losses and cycling in a Quercus coccifera garrigue (southern France). Oecologia 99, 379-386. Trumbore, S.E., Chadwick, O.A., Amundson, R., 1996. Rapid exchange between soil carbon and atmospheric carbon dioxide driven by temperature change. Science 272, 393-396. Van der Werf, G.R., Randerson, J.T., Collatz, G.J., Giglio, L., 2003. Carbon emissions from fires in tropical and subtropical ecosystems. Global Change Biology 9, 547562. Van Nieuwstadt, M.G.L., Sheil, D., Kartawinata, K., 2001. The ecological consequences of logging in the burned forests of East Kalimantan, Indonesia. Conservation Biology 15, 1183-1186. Weber, M.G., 1990. Forest soil respiration after cutting and burning in immature aspen ecosystems. Forest Ecology and Management 31, 1-14. Xiang, S.R., Doyle, A., Holden, P.A., Schimel, J.P., 2008. Drying and rewetting effects on C and N mineralization and microbial activity in surface and subsurface California grassland soils. Soil Biology and Biochemistry 40, 2281-2289. Xu, L., Baldocchi, D.D., Tang, J., 2004. How soil moisture, rain pulses, and growth alter the response of ecosystem respiration to temperature. Global Biogeochemical Cycles 18. Xu, M., Qi, Y., 2001. Spatial and seasonal variations of Q10 determined by soil respiration measurements at a Sierra Nevadan forest. Global Biogeochemical Cycles 15, 687696. Yanai, R.D., Arthur, M.A., Siccama, T.G., Federer, C.A., 2000. Challenges of measuring forest floor organic matter dynamics: Repeated measures from a chronosequence. Forest Ecology and Management 138, 273-283.

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Yermakov, Z., Rothstein, D.E., 2006. Changes in soil carbon and nitrogen cycling along a 72-year wildfire chronosequence in Michigan jack pine forests. Oecologia 149, 690-700. Zhang, Y.M., Wu, N., Zhou, G.Y., Bao, W.K., 2005. Changes in enzyme activities of spruce (Picea balfouriana) forest soil as related to burning in the eastern QinghaiTibetan Plateau. Applied Soil Ecology 30, 215-225.

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APPENDIX A: Table A1: Soil CO2 effluxes in each sampling date in every treatment and elevation. Mean values of soil fluxes (μmol m-2s-1) are followed by ±1SE (n=20). CL: cut plus lopping; NI: non intervention; SL: salvage logging; HE: high elevation (2317 m a.s.l.); LE: low elevation (1477 m a.s.l.)

Season

Treatment

Sampling Date Elevation CL

SL

05-July

HE

1.19±0.08 1.31±0.12 0.97±0.12

LE

2.04±0.16 2.17±0.22 1.69±0.16

19-July

HE

1.07±0.21 0.71±0.07 0.76±0.07

LE

2.37±0.30 2.16±0.25 1.90±0.28

2-August

HE

1.10±0.22 0.60±0.06 0.75±0.11

LE

2.02±0.25 2.26±0.30 2.03±0.23

30-August

HE

0.88±0.20 0.52±0.08 1.12±0.40

LE

1.92±0.19 2.00±0.29 1.93±0.32

25-September

HE

3.87±0.37 4.27±0.55 4.85±0.41

LE

5.46±0.30 4.79±0.50 4.21±0.26

30-October

HE

1.92±0.12 2.00±0.20 0.83±0.06

LE

2.45±0.21 2.42±0.33 1.83±0.15

15-April

HE

2.29±0.27 2.16±0.24 0.76±0.09

LE

5.22±0.41 3.98±0.44 2.86±0.25

19-May

HE

3.82±0.56 3.14±0.52 2.43±0.20

LE

14.92±1.87 7.38±1.18 6.57±1.13

Summer 08

02-September

HE

0.92±0.14 0.47±0.05 0.62±0.09

LE

Autumn 08

01-October

HE

2.38±0.19 2.07±0.26 1.93±0.36 3.51±0.34 3.55±0.41 1.61±0.14

LE

7.08±0.27 4.08±0.38 4.79±0.51

Summer 07

Autumn 07

Spring 08

206

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____________________________________Burnt wood management effect on soil respiration

APPENDIX B

Figure B1: Rain events during the measurement period. Data from a meteorological station near the low elevation (LE).

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APPENDIX C: Discrimination between the degassing period and the respiration

period in continuous measurements of soil CO2 fluxes after artificial irrigation.

The continuous CO2 efflux data during the first 24 hours after irrigation consistently revealed two distinct periods, each displaying linear declines when plotted on a logarithmic scale (Fig. 5 of the manuscript) and thus corresponding to exponential decay. Such linear relations can be expressed generally as

y = a + bt , where t is the time since irrigation, and the remaining variables correspond to the following assignations in the context of exponential decay:

y Æ ln (F

)

a Æ ln (F0 ) bÆ −

1

τ

In the above formulae, F is the CO2 efflux (a function of t), F0 the initial value (at

t=0), and τ the time constant describing the exponential decay. These assignations are chosen such that the decline can be expressed as 1 ln (F ) = ln (F0 ) − t .

τ

When the above equation is equated in terms of the exponent of e (ca. 2.718), an exponential decay is described as

F = F0 exp

⎛1⎞ −⎜ ⎟ t ⎝τ ⎠

,

where τ is the time required for the flux to fall to ca. 37% (e-1) of its initial value (F0).

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For every treatment, a rapid exponential decay was observed during the first 2 h, after which time a more slowly decaying efflux proceeded. We interpreted these periods as corresponding to two separate processes associated with the irrigation treatment: first, during the first couple of hours, physical degassing (period “d”) as soil pores were filled by water (Luo and Zhou, 2006); and later, the decline of respiration (period “r”) governed by enzyme kinetics (Inglima et al., 2009; Liu et al., 2002; Xiang et al., 2008) as the soil asymptotically returned to its water-limited state (Fig. 5). For each period, we determined linear fit parameters (a and b) by least-squares regression, and thereby the parameters F0 and

τ (summarized in Table C1) describing the different exponential decay processes. The purpose of this analysis was merely to exclude the degassing period and thereby isolate the respiration period (excluding the first couple of hours), in order to explore the effect of soil moisture on biologically determined CO2 fluxes in the irrigated collars.

Table C1. Exponential decay parameters for post-irrigation declines in soil CO2 effluxes. CL: cut plus lopping; NI: non intervention; SL: salvage logging.

Degassing period (d)

Treatment

F0,d (μmol m s )

CL

86.1

(h) 1.1

NI

47.0

SL

20.1

-2 -1

τd

Respiration (r) period

F0,r (μmol m-2s-1)

τr

15.7

(h) 19.5

1.2

13.3

11.1

1.5

3.9

13.6

209

210

CHAPTER 5: POST-FIRE SALVAGE LOGGING REDUCES CARBON SEQUESTRATION IN MEDITERRANEAN CONIFEROUS FOREST

Penélope Serrano-Ortiz, Sara Marañón-Jiménez, Borja Ruíz Reverter, Enrique Pérez Sánchez-Cañete, Jorge Castro, Regino Zamora, Andrew S. Kowalski.

Published in: Forest Ecology and Management doi: 10.1016/j.foreco.2011.08.023

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_________________________________Salvage logging management reduces C sequestration

ABSTRACT Post-fire salvage logging is a common silvicultural practice around the world, with the potential to alter the regenerative capacity of an ecosystem and thus its role as a source or a sink of carbon (C). However, there is no information on the effect of burnt wood management on the net ecosystem carbon balance. Here, we examine for the first time the effect of post-fire burnt wood management on the net ecosystem carbon balance by comparing the carbon exchange of two treatments in a burnt Mediterranean coniferous forest treated by “Salvage Logging” (SL, felling and removing the logs and masticating the woody debris) and “Non Intervention” (NI, all trees left standing) using eddy covariance measurements. Using different partitioning approaches, we analyze the evolution of photosynthesis and respiration processes together with measurements of vegetation cover and soil respiration and humidity to interpret the differences in the measured fluxes and underlying processes. Results show that SL enhanced CO2 emissions of this burnt pine forest by more than 120 g C m-2 compared to the NI treatment from the period JuneDecember 2009. Although soil respiration was around 30% higher in NI during growing season, this was more than offset by photosynthesis, as corroborated by increases in vegetation cover, evapotranspiration as well as reduced soil moisture in the NI treatment. Since SL is counterproductive to climate change and Kyoto protocol objectives of optimal carbon sequestration by terrestrial ecosystems, less aggressive burnt wood management policies should be considered. Keywords: Burnt wood management, eddy covariance, forest carbon balance, photosynthesis, respiration, wildfire

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1. INTRODUCTION

Wildfire is a frequent perturbation in Mediterranean-type ecosystems (Moreno et al., 1998) inducing changes in land use/cover types (Lloret et al., 2002; Quintana et al., 2004; Viedma et al., 2006) and thereby altering the balances of water, energy and carbon (Amiro et al., 1999, 2006; Beringer et al., 2003; Santos et al., 2003). Although CO2 emission immediately after fire can be reasonably estimated (Conard and Ivanova, 1997; Harden et al., 2000; Page et al., 2002; Van der Werf et al., 2003), long-term effects on the carbon balance during ecosystems to regeneration are less certain and influenced by several factors. Enhanced rates of soil CO2 efflux as well as large changes in the rate of ecosystem photosynthetic carbon uptake may also occur during several months after wildfire (Santos et al., 2003). However, other studies suggest a reduction of soil CO2 efflux in ecosystem to regeneration (Dore et al., 2010; Irvine et al., 2007) that could be attributed to the positive relation between aboveground productivity and respiration (Irvine et al., 2007; Janssens et al., 2001). Finally, some studies reveal decreased in evapotranspiration (ET) and a conversion from carbon sink to source with magnitudes differing over the years following wildfire (Amiro, 2001; Amiro et al., 2003, 2006; Mkhabela et al., 2009). Post-fire management may affect the fluxes of carbon and hence the role of the ecosystem as a carbon source or sink. The capacity for carbon sequestration after a wildfire will depend on the regenerative capacity of the vegetation that determines net primary production. For example, reforestation soon after a standreplacing disturbance accelerates the conversion from carbon source to sink (Magnani et al., 2007) although natural regeneration may similarly increase carbon sequestration (Amiro, 2001). In addition, forest fires leave large amounts of partially burnt wood that may be handled in several ways according to ecological or management requirements, increasing productivity (Castro et al., 2010a, 2011;

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_________________________________Salvage logging management reduces C sequestration

Donato et al., 2006) and simultaneously enhancing C emissions due to decomposition (Jomura et al., 2008; Marañón-Jiménez et al., 2011). Therefore, the net carbon balance after a wildfire, may differ as a consequence of forest management (Stark et al., 2006), whether by a direct effect on vegetation cover and development or as mediated by the presence of burnt wood. One of the first and most important post-fire management decisions regards the fate of the burnt wood. After a fire, forest managers frequently apply salvage logging, removing the burnt tree trunks, and often eliminating the remaining woody debris by chopping, mastication, fire, etc. (Bautista et al., 2004; Lindenmayer et al., 2008; McIver and Starr, 2000). Post-fire salvage logging has been routinely practiced by forest managers worldwide, motivated by factors economic, silvicultural, or even esthetic (Castro et al., 2009, 2011; Lindenmayer and Noss, 2006; McIver and Starr, 2000). However, there is increasing evidence that salvage logging degrades ecosystem function and structure in terms of vegetation regeneration, animal and plant diversity, watershed runoff and erosion, or nutrient cycling (Castro et al., 2010a, 2010b, 2011; Donato et al., 2006; Lindenmayer et al., 2008). In the same way, post-fire burnt wood management can potentially alter the ecosystem carbon balance. On one hand, large amounts of carbon stored in the burnt wood can decompose and be emitted as CO2 to the atmosphere. On the other hand, the presence of burnt wood can enhance regeneration capacity both by incorporating nutrients into the soil as it decomposes, and also by improving microclimatic conditions that benefit net primary productivity (Castro et al., 2010a, 2011; Donato et al., 2006; Lindenmayer et al., 2008). Post-fire burnt wood management could therefore affect the net ecosystem carbon balance even during several years after the wildfire. To date however, there are no studies on the effects of bunt wood management on net carbon exchange after a wildfire. The aim of this paper is to examine the effect of the post-fire salvage logging on the net ecosystem carbon balance. We compare the CO2 exchange, 215

Chapter 5_______________________________________________________________________

measured during the fourth year following wildfire, of two treatments with different post-fire management treatments: “Salvage Logging” (SL) and “Non Intervention” (NI). We used the eddy covariance (EC) technique to directly measure net carbon, water vapor and energy exchanges between the atmosphere and the biosphere (Baldocchi, 2003; Wofsy et al., 1993). In addition, soil CO2 effluxes, vegetation cover and meteorological variables were measured to interpret the patterns of carbon fluxes and underlying processes. We hypothesized that postfire burnt wood management would influence the magnitude of carbon exchange between the ecosystem and the atmosphere, as the presence of the burnt wood may alter both respiration rates and gross primary production. These measurements are critical to understand ecosystem carbon exchange at a global scale given the large areas of forest burned every year, and are a necessary step to ascertain the effect of management practices on the ecosystem carbon balance.

2. MATERIALS AND METHODS

2.1. STUDY AREA AND EXPERIMENTAL DESIGN The study site is located in the Sierra Nevada National Park (SE Spain). In September 2005, a wildfire burned ca. 1300 ha of reforested pine between 35 and 45 years age. The area selected for this study is located at 2320 m a.s.l. (36°58'3.68"N;

3°28'37.04"W).

The

climate

is

Mediterranean-type,

with

precipitation falling mostly during autumn and winter, and by a dry summer. Mean annual temperature is 7.8±0.7ºC (period 2008–10) and the annual precipitation 470±50 mm (period 1988–2008; climatic data from a nearby meteorological station at 1500 m a.s.l). Snow falls during winter, usually persisting from November to March, and the growing season usually starts in the second half of May. The slope is between 15-20%. The dominant pine species present before the wildfire was

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_________________________________Salvage logging management reduces C sequestration

Pinus sylvestris with a density of 1060±50 ha-1 and 13.4±0.3 cm d.b.h. and 6.63±0.17 m height. Burnt wood biomass was estimated at 46.9 Mg ha-1 (70% above and 30% belowground), according to alometric equations based on pine density and tree size (Castro et al., 2010a). This supposes a C stock in wood of 23.6 Mg ha-1 (C concentration was determined in the sawdust of 50 burnt logs with a Leco TruSpec autoanalyzer, St. Joseph, MI, USA). The fire was of high intensity and no trees survived inside the study area. Current vegetation is mainly composed by grass and forbs typical of disturbed areas in the Oromediterranean belt (MoleroMesa et al., 1996) the most common perennial species being Genista versicolor, Festuca spp. and Sessamoides prostata. Nine months after the fire, two post-fire management treatments were applied to the burnt trees of two 35-ha stands: (1) “Non Intervention” (NI): all burnt trees were left standing and fell naturally and progressively over the years, with around 25% still standing at the beginning of this study; and (2) “Salvage Logging” (SL): trees were cut and the trunks cleaned of branches by chainsaw and piled manually in groups of 10-12, with woody debris chopped by machine and trunks removed from the site with a log forwarder. The two treatments were contiguous (Fig. 1) and showed similar characteristics in terms of tree size and density, slope, bedrock (michaschists) and soil type (Humic cambisols).

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Chapter 5_______________________________________________________________________

Figure 1: Eddy tower locations as bull’s eyes in Non intervention (white) and Salvage Logging (black) treatments. For each tower, according to the Flux-Source Area model of Schmid (1994) during periods of relative static stability (periods where measured fluxes are generated most distantly to the eddy tower) defined in terms of the friction velocity (0.2 m s-1
2.2. METEOROLOGICAL AND EDDY COVARIANCE MEASUREMENTS An eddy covariance tower - with additional instrumentation for environmental and soil measurements - was installed in each treatment. Fluxes of CO2, water vapor (or latent heat flux) and sensible heat were estimated from fast response (10 Hz) instruments mounted atop towers of 10 m (NI) and 2.5 m (SL). Densities of CO2 and H2O were measured by open-path infrared gas analysers (LiCor 7500, Lincoln, NE, USA) and calibrated periodically using an N2 standard for zero and a 479.5 μmol (CO2) mol–1 gas standard as a span for both treatments. Winds and sonic temperature were measured by three-axis sonic anemometers (for NI: Model 81000, R.M. Young, Traverse City, MI, USA; for SL: CSAT-3, 218

_________________________________Salvage logging management reduces C sequestration

Campbell Scientific, Logan, UT, USA). Comparison analyses between fluxes calculated by both anemometers have been already published and show good agreement (Loescher et al., 2005; Tanny et al., 2010). Measurements were made in 2009 (the 4th year after the fire), year-round in NI, and from early June to late December in SL. Air temperature and humidity were measured by thermohygrometers (HMP 45C, CSI, USA) at 7 m (NI) and 2 m (SL) above the surface. Soil water content (SWC) was measured by two water content reflectometers (CS616, CSI) at 4 cm depth for NI treatments. Over a representative ground surface, photosynthetic photon flux densities were measured by quantum sensors (Li-190, Lincoln, NE, USA) for NI and SL treatments. In the NI treatment, a net radiometer (NR Lite, Kipp & Zonen, Delft, Netherlands) located 8 m above the surface and four heat flux plates (HFP01SC, Hukseflux, Delft, Netherlands) at 8 cm depth and two pairs of soil temperature probes (TCAV, Campbell Scientific, Logan, UT, USA) at 2 and 6 cm depth, were installed parallel to the surface to examine the energy balance closure (Wilson et al., 2002). For both treatments, data loggers (CR3000, CSI) managed the measurements and recorded the data. For eddy covariance measurements, data were saved at 10 Hz by the logger which calculated and recorded means, variances and covariances on half-hour bases following Reynolds’ rules. Eddy flux corrections for density perturbations (Webb et al., 1980) and coordinate rotation (McMillen, 1988) were applied, as well as quality control checks following Reverter et al., (2010) using an in-house program (PECADO) based on MATLAB routines.

219

Chapter 5_______________________________________________________________________

2.3. DATA QUALITY CONTROL, GAP FILLING FOR LONG TERM INTEGRATION OF FLUXES, AND PARTITIONING

Half-hour statistics were computed when data eliminated by quality control did not exceed 25% of the total. Night-time data during periods with low turbulence (friction velocity, u*<0.35 m s-1 for the NI treatement; u*<0.25 m s-1 for the SL treatment) were rejected (Goulden et al., 1996), as were three nights from February with unrealistic values. The Flux-Source Area footprint model (Schmid, 1994, 1997, 2002) was applied to verify that fluxes originated from well within the fetch (Fig. 1). Even during periods of relative static stability (0.2 m s-1
; sensible heat fluxes (H)<0), the estimated maximum source location was 101 m

for NI and 36 m for SL; the maximum distance of the 50% source area isopleths (Fig. 1) was 228 m (NI) and 68 m (SL). In addition, the energy balance closure (ratio of the sum of sensible and latent turbulent fluxes, H+LE, to the difference between net radiation and the soil heat flux, Rn-G) was 90% (R2=0.67; n=755) for the NI treatment and 96% (R2=0.60; n=1225) for SL treatment. This value is in the range reported by most FLUXNET sites (Wilson et al., 2002) and provides additional information regarding turbulent flux quality (Moncrieff et al., 1997). Data rejected due to environmental conditions or instrument malfunction amounted to 29% and 23% of the total measured period for the NI and SL treatments respectively. In addition, night-time low turbulence conditions rejected 18% and 13% of the data, resulting in 47% total data missing for NI and 36% for SL, requiring gap filling in order to estimate the annual CO2 and water vapor exchanges. Gaps were filled using the ‘‘Marginal Distribution Sampling’’ (MDS) technique (Falge et al., 2001; Reichstein et al., 2005), replacing missing values using a time window of several adjacent days. The length of the time window depends on environmental conditions and meteorological data availability. In a parallel way and only for CO2 fluxes, a semi-empirical gap filling method based on

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the response to temperature and photosynthetic photon flux density for respiration and photosynthesis respectively (Falge et al., 2001; Lasslop et al., 2010) was also applied. Results from this alternative gap-filling method are mentioned only when significant differences with the MDS method were detected (P<0.05). Random uncertainty and errors in net ecosystem carbon and water vapor exchanges introduced by the gap-filling processes were calculated using Monte Carlo simulations (Richardson and Hollinger, 2007); see Reverter et al., (2010) for more information. Positive values of net ecosystem carbon exchange denote CO2 release from the soil to the atmosphere while negative values denote CO2 uptake. Half hourly net CO2 fluxes were broken into gross primary production (GPP) and ecosystem respiration (Reco) components using two different techniques: the “night-time data-based estimate” (NB; (Reichstein et al., 2005)) and the “daytime data-based estimate” (DB; (Lasslop et al., 2010)) flux partitioning algorithms. The NB algorithm assumes that GPP is zero at night and models Reco as a function of temperature using night-time data; this relationship is extrapolated to daytime, for which the difference between the modeled Reco and measured CO2 fluxes yields the estimated GPP (see Reichstein et al., 2005 for more information). For the DB algorithm, the daytime measured CO2 fluxes are modeled using a hyperbolic light–response curve (Falge et al., 2001) for GPP and a respiration model depending on temperature for Reco (Eq. (1)); where FC is the measured CO2 flux, α (μmol C J-1) the canopy light utilization efficiency representing the initial slope of the light–response curve, β (μmol C m-2s-1; ) the maximum CO2 uptake rate of the canopy at light saturation adjusted for vapor pressure deficit limitations, Rg the global radiation (W m-2) that can be easily estimated using the measured photosynthetic photon flux density (Ceulemans et al., 2003), R15 (μmol C m-2s-1) the base respiration at 15ºC, E0 (ºC) the temperature sensitivity and Ta (ºC) the air temperature (see Lasslop et al., 2010 for more details).

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FC =

⎛ ⎞ αβ R g 1 1 ⎟ + R15 exp⎜⎜ E 0 − ⎟ αR g + β ⎝ 15 − 46.02 Ta + 46.02 ⎠

(1)

To track the respiratory and photosynthetic capacity of both treatments, mean monthly values of R15 and α estimated every two days from the DB partitioning algorithm were selected.

2.4. PLANT COVER AND SOIL RESPIRATION AND MOISTURE MEASUREMENTS In order to determine possible causes of the differences in measured FC between treatments, plant cover and soil CO2 fluxes and humidity were measured. Plant cover was sampled with a point-linear method one and two years after the fire (June 2006 and 2007, respectively) as a surrogate for regenerative capacity and primary production. In June 2006, measurements were done in 12 randomly established linear transects of 25x2 m along the maximum slope of the terrain for each treatment. The number of individuals of perennial plants was counted within each transect. For June 2007 the methodology was changed due to the high plant cover that impeded the monitoring of all individuals. In that case, three points (central and transversal sides) at each 50 cm along the transect (n=150 points per transect) were sampled, observing the nature of contact (soil or vegetation). Plant height (if present) was measured at every central point of the transect. Differences between treatments were analyzed with one-way ANOVAs for each year. Soil respiration and water content were measured six times throughout the spring of 2009 at three-week intervals from March to June. Twenty PVC collars per treatment were installed in the soil to ca. 5 cm depth, randomly distributed over an area of ca. 1 ha and separated by at least 10 m. Soil respiration measurements were performed on the collars from ca. 9 am to 3 pm using two CO2 analyzer systems: the manual EGM-4/SRC-1 (PP-Systems, Hitchin, UK); and an automated

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Li-8100 (Li-Cor; Lincoln, NE, USA). The two instruments were used in both treatments. A previous instrument intercomparison (Marañón-Jiménez et al., 2011) allowed correction of the EGM-4/SRC-1 data to match the Li-8100. During these campaigns, soil water content was also measured at 10, 20, 30 and 40 cm depth at 15 points per treatment, using the PR-2 profile probe (Delta T, Services, Cambridge, UK). Soil CO2 effluxes and their variation over sampling dates (time) were analyzed with a repeated-measure analysis of variance (rmANOVA), with sampling dates defined as the within-factor and treatment as the between-factor. Soil water content was similarly analyzed with rmANOVA. Throughout the paper mean values are followed by ±1SE.

3. RESULTS

3.1. METEOROLOGICAL CONDITIONS Meteorological conditions showed a strongly asynchronous pattern of rainfall and temperature throughout the year (Fig. 2). During summer (June, July, August), the mean daily air temperature (Ta) was 17.1ºC, while precipitation was almost negligible with only one rain event exceeding 5 mm. In winter (January, February, and December) mean daily Ta was 1ºC and the greatest precipitation fell, mostly as snow which persisted from December to March. During spring and fall, rain and Ta showed intermediate values compared with the other two seasons, with a mean daily Ta of 7.8ºC, and accumulated rainfall of 170 mm. Annual values of mean Ta and total rainfall in 2009 were 8.4ºC and 678 mm respectively.

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Figure 2: Mean daily values of air temperature (Ta: ºC; grey dots), soil water content (SWC: % vol.; black line) and total precipitation (Rain; mm; black bars) during 2009. Shaded bars denote periods of snow cover [ratio of mean daytime reflected photon flux density to mean daytime incident photon flux density higher than 0.2]

3.2. MONTHLY NET CARBON EXCHANGE AND EVAPOTRANSPIRATION Overall, the Non Intervention (NI) treatment acted as a monthly net carbon sink during nearly the whole year 2009, whereas the Salvage Logging (SL) treatment acted consistently as a source following the June installation of the eddy system (Fig. 3). The most productive period for NI was the end of spring and beginning of summer, reaching the maximum value of carbon uptake in May (around 30 g C m-2). Then, from August to October, NI emitted ca. 2 g C m-2 per month. In November (end of autumn, with fair weather) the ecosystem absorbed more than 10 g C m-2. During winter, NI was very nearly carbon neutral. However, December and January are interpreted as carbon source months if gaps were filled using the semi-empirical approach, emitting 13 and 9 g C m-2 respectively. By contrast, SL consistently emitted carbon, with maximum emissions in July (more than 20 g C m-2) and decreasing from then until the year’s end. The semi-empirical

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approach could not be applied in SL due to the inability to correlate measured CO2 fluxes with temperature or light (Lasslop et al., 2010).

Figure 3: Monthly totals of exchanged carbon (g C m-2) and evapotranspiration (mm) by forest stands during 2009 for Non Intervention (NI, grey bars) and since June 2009 for Salvage Logging (SL, dark bars) treatments, using MDS gap-filling technique. Ecosystem CO2 uptake is depicted as negative values while ecosystem CO2 release is positive.

During the measured period in both treatments, NI presented usually higher monthly evapotranspiration values (ET), with the exception of December (Fig. 3). Monthly ET for NI reached maximum values at the end of spring (May and June; ca. 60 mm) and minima at the beginning and end of the year (<25 mm). In early autumn (October), ET was similar to that of early spring (ca. 40 mm). In SL, during the measured period (June-December), maximum ET values where reached in October when the soil was moist and the temperature mild (Figs. 2 and 3). Nonetheless, monthly ET remained very low and stable over the measured period

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and never exceeded 40 mm. The monthly Bowen ratio (ratio of sensible to latent heat flux) increased from February to August for NI treatment and decreased afterwards (Table 1). For SL treatment the monthly Bowen ratio was higher than NI. Both treatments presented higher values in July and August (Table 1).

Table 1: Monthly values of the Bowen ratio for Non Intervention (NI) and Salvage Logging (SL) treatments along 2009. The error (in parentheses) is calculated based on the standard errors of H and LE.

Bowen Ratio Jan. NI

-

SL

-

Feb. 0.4 (0.2)

Mar. 1.4 (0.5)

Apr. 2.2 (0.4)

May. 1.9 (0.2)

-

-

-

-

Jun. 2.1 (0.2) 3.4 (0.5)

Jul. 3.6 (0.3) 4.2 (0.5)

Aug. 3.1 (0.3) 3..5 (0.6)

Sep. 1.8 (0.4)

Oct. 1.6 (0.2) 1.8 (0.3)

Nov. 1.2 (0.3) 2.0 (1.1)

Dec. -

3.3. DIURNAL TRENDS OF CO2 FLUXES ACROSS TREATMENTS Diurnal trends of CO2 fluxes were explored in three representative months for simplicity (Fig. 4). In general, during daytime NI acted as a consistent net CO2 sink while SL acted as a source. During night-time both treatments acted as sources of CO2. However, while SL presented values lower than 0.6 μmol m-2s-1, NI reached values exceeding 1 μmol m-2s-1 in June. Concretely, in June, daytime CO2 uptake in NI was often near 3 μmol m-2s-1 while SL acted as daytime CO2 source (ca. 1.5 μmol m-2s-1). In July, SL presented similar behavior to June whereas NI reduced its CO2 assimilation by more than a half. In November, early daytime CO2 uptake was measured in SL (FC=-0.5 μmol m-2s-1). For the NI treatment, autumn values of daytime CO2 uptake reached 2 μmol m-2s-1 and nighttime CO2 release was considerably lower than June and July.

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Figure 4: Diurnal trends in CO2 flux (Fc, μmol m-2s-1) for the monthly means (±SE) of June, July and November 2009 for (A) Non Intervention and (B) Salvage Logging treatments.

3.4. ACCUMULATED CARBON EXCHANGE Fig. 5 shows the accumulated carbon exchange estimated for NI and SL over the period when simultaneous measurements in both treatments are available (June–December of 2009). For the SL treatment, the accumulated carbon exchange showed a near constant slope (a) [a=0.6; R2=0.995] from the start of the measurements (June) until October. During this period, this treatment acted as a constant daily carbon source, emitting between 80 and 110 g C m-2 and thereafter, it acted as near neutral C sink until the end of the year. The NI treatment acted as a net carbon sink during spring, absorbing 60 g C m-2 (from April to June; data not shown). After this productive period, the net carbon uptake capacity was reduced and the ecosystem absorbed 30 g C m-2 from June to July. From this point, the NI treatment behaved as near neutral C sink until the middle of November, when this treatment recovered its sink activity until the end of the year.

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Figure 5: Cumulative carbon exchange (g C m-2) from June-December 2009 by burnt forest treated with Non intervention (NI, grey line) and Salvage Logging (SL, black line).

Over the course of 2009 the NI treatment absorbed 77±11 g C m-2. Such a confident value cannot be given for SL treatment, due to the absence of carbon exchange measurements from January to May 2009. However, crude annual estimation can be given assuming range of possible behaviors of SL treatment during the non-measured period. During winter, we can consider similar behavior for NI and SL, acting as a neutral net carbon sink due to the existence of snow cover (Harding et al., 2001). For April and May, the accumulated carbon exchange could be considered as delimited by two extreme situations: (1) a neutral net carbon exchange, given the lack of net carbon assimilation throughout the measurement period (Fig. 3) and (2) a scenario of maximum carbon emission. For the estimations under this assumption we used the “daytime data-based estimate” (DB) respiration model (Lasslop et al., 2010). The model was applied using maximum values of base respiration at 15ºC (R15) and temperature sensitivity (E0) estimated during the measured period (1.25 μmol m-2s-1 and 335ºC, respectively). Thus, in any case considered under these preliminary assumptions, the SL treatment acts as a net annual carbon source, emitting between 90 and 120 g C m-2 in 2009.

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3.5. PLANT COVER AND SOIL RESPIRATION AND MOISTURE MEASUREMENTS Plant cover in June 2006 was higher in NI (11.1±1.6 individuals m-2) than in SL (7.5±1.1 individuals m-2; F=3.24, d.f.=1, 22; P=0.086). Plant cover similarly differed between treatments in June 2007 (F=18.17, d.f.=1, 22; P<0.001), being higher in NI (61.2±1.7%) than in SL (46±4%; see also Fig. 6 for pictures of the study areas in 2009). Plant height also differed between treatments (F=4.69; d.f.=1, 453; P=0.031; log-transformed data), being likewise higher in NI (22.9±1.4 cm), than in SL (19.5±1.4 cm).

Figure 6: Appearance of burnt forest treated by Non Intervention (NI) and Salvage Logging (SL) for the 27th and 28th of May 2009 respectively.

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Soil respiration was consistently higher in NI than SL (Fig. 7A, Table 2). Soil water content decreased throughout the growing season and was constantly higher in SL (Fig. 7B; Table 3).

Figure 7: Mean values (±SE) of (A) soil CO2 effluxes of 20 PVC collars and (B) soil water content from 10 to 40 cm depth for Non Intervention (NI) and Salvage Logging (SL) treatments, for six campaigns in spring 2009.

Table 2: Summary of repeated measures analysis of variance (rmANOVA) for soil CO2 fluxes measured throughout the spring 2009. df: degrees of freedom of the numerator and denominator respectively. F: Value of the F statistic. P: Critical probability of the analysis.

df

F

P

1, 28

7.34

0.0114

Time

5, 24

4.76

0.0037

Time*Treatment

5, 24 28

2.07

0.1048

Source Between-subject Treatment Within -subject

Error

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Table 3: Summary of repeated measures analysis of variance (rmANOVA) for the soil water content measured throughout the spring of 2009. df: degrees of freedom of the numerator and denominator respectively. F: Value of the F statistic. Approximate value of F adjusted for the Time*Depth and Time*Treatment*Depth interactions (Wilk`s-Lambda multivariate test). P: Critical probability of the analysis. df

F

P

Treatment

13.61

1, 54

0.0005

Depth

0.41

3, 54

0.7464

Treatment*Depth

0.18

3, 54

0.9101

Time

5, 50

156.61

<0.0001

Time*Treatment

5, 50

9.23

<0.0001

Time*Depth

15, 138.43

3.94

<0.0001

Time*Treatment*Depth

15, 138.43

1.10

0.3572

Source Between-subject

Within -subject

Error

54

3.6. PHOTOSYNTHESIS AND RESPIRATION PARTITIONING Mean estimated values of base respiration at 15ºC (R15) and canopy light utilization efficiency (α) from the DB partitioning algorithm (Fig. 8) were used to track the respiratory and photosynthetic capacities of NI. Monthly trends of R15 and

α were very similar, showing peaks at the end of spring (May) and in the fall, with lower values during the dry summer. However, R15 lagged α by about one month in reaching its fall maximum (in October, R15=0.86 μmol m-2s-1) by which time α had dropped back to low values (ca. 0.008 μmol C J-1). Relatively high values of R15 were also estimated in December, but were accompanied by only a slight increase in α. For SL, no dependence of GPP on light, nor of Reco on temperature, was detected and thus, the DB partitioning algorithm could not been applied, except from mid-October to December, where early daytime CO2 uptake was measured in

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SL (see November 2009 in Fig. 4) and R15 reached values near 0.54 μmol m-2s-1. The estimated α was generally null, except for 22-24 October (0.0012 μmol C m-2 s-1) and 5-7 November (0.0853 μmol C m-2s-1).

Figure 8: Mean monthly values (±SE) of respiratory and photosynthetic parameters used to estimate both processes in Non Intervention (NI) treatment. Estimated values outside the range defined as “mean monthly value±SD” were rejected.

Thus, due to the lack of measured CO2 fluxes dependencies on light or temperature for SL, estimated values of gross primary production and ecosystem respiration are given only for NI. Using both algorithms, higher values of GPP were obtained in May and June, while lower values corresponded to cold winter months (January-March; Fig. 9). During end of summer, fall and beginning of winter the estimated GPP remained nearly constant according both algorithms. The same seasonal pattern for GPP was obtained using the NB algorithm. By contrast, modeled Reco showed significant differences depending on the algorithm used. For “DB” algorithm, Reco presented higher estimated values during the end of summer and early fall, and maximum in September (only for DB algorithm). A peak in Reco

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was also estimated in May. The beginning and end of the year (January and December) also presented high values similar to June and October respectively. Using the NB algorithm higher values of Reco were estimated in May and June, and minimum values during winter.

Figure 9: Estimated monthly gross primary production (GPP; negative exchanges) and ecosystem respiration (Reco; positive exchanges) using the “daytime data-based estimate” (DB; lined bars) and the “night-time data-bases estimate” (NB, white bars) flux partitioning algorithms for the non intervention treatment.

4. DISCUSSION

During the fourth year after a fire, SL management hindered the recovery of carbon sequestration in the Mediterranean coniferous forest compared to the NI treatment. Photosynthesis and respiration processes also presented different patterns between post-fire treatments. Carbon loss was mostly constant in SL and

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not related to temperature at short time scales (30 min), with very small oscillations throughout the whole measurement period at both daily and seasonal scales, evidencing very low biological activity in the soil and vegetation. By contrast, the NI treatment showed more biological activity, with higher soil respiration rates and vegetation productivity, yielding higher daily and seasonal ranges of carbon exchange. In fact, the results of this study underline higher vegetation cover and performance for NI treatment, explaining the higher ET and lower Bowen ratio compared to SL treatment, with a consequent decrease in soil water content. Furthermore, while opposing processes in the carbon cycle (plant uptake and respiration) were both enhanced in NI, the additional contributions of CO2 released by the wood decomposition (Gough et al., 2004) was overwhelmed by photosynthesis such that annual carbon emissions were reduced considerably compared to the SL treatment. Thus, despite the limited temporal extent of data coverage, the strong impact of SL management on ecosystem CO2 fluxes has been clearly demonstrated even at the initial stages of natural regeneration. Several reasons may contribute to the marked differences in the net CO2 fluxes between SL and NI treatments. First, burnt trees and coarse woody debris left after the wildfire represent a large pool of nutrients (Johnson et al., 2005; Kappes et al., 2007; Merino et al., 2007; Wei et al., 1997), that will be progressively incorporated to the soil as the trees fall and wood decomposes (Coleman et al., 2004; Grove and Meggs, 2003; Harmon et al., 1986), improving soil fertility. Second, burnt trees and branches (even after falling) act as nurse structures that improve microclimatic conditions for plant regeneration (Castro et al., 2010a, 2011; Harmon et al., 1986; Lindenmayer et al., 2008; Smaill et al., 2008; Stoddard et al., 2008). Third, salvage logging may damage the banks of seedlings and shoots that regenerate soon after the fire (Lindenmayer et al., 2008; Martínez-Sánchez et al., 1999; McIver and Starr, 2000), reducing plant density. In addition, the presence of burnt logs and branches creates habitat complexity that

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may reduce herbivore damage to the vegetation (Ripple and Larsen, 2001; see also Relva et al., (2009) for similar effect in non-burnt woody debris), and attract seeddispersing birds (Castro et al., 2010b; Rost et al., 2009, 2010). All this may translate to a higher capacity in NI for vegetation productivity and hence carbon sequestration, while SL retards vegetation recovery and carbon uptake capacity. Differences could be more accentuated in the long term, as wood decomposes and progressively releases its nutrients (Irvine et al., 2007). These results are likely extensible to many other burnt coniferous forest ecosystems subjected to post-fire salvage logging. Coarse woody debris has been widely reported to contribute to soil fertility and soil microclimate improvement in different ecosystem types (Castro et al., 2010a, 2011; Hafner and Groffman, 2005; Pérez-Batallón et al., 1998; Smaill et al., 2008; Stoddard et al., 2008), and consequently to enhance primary productivity (Burton et al., 2000; Irvine et al., 2007; Stark et al., 2006; Stoddard et al., 2008). Since partially burnt woody debris (with charring limited to the bark and the superficial layers) has similar nutrient concentrations to unburnt wood (Wei et al., 1997), the effects of burnt wood on soil fertility enrichment will be comparable to those reported for unburnt coarse woody debris. In addition, reductions in plant cover and regeneration capacity after salvage logging have been also reported in different forest types across the world (Beghin et al., 2010; Castro et al., 2011; Donato et al., 2006; Greene et al., 2006; Lindenmayer et al., 2004; Lindenmayer and Noss, 2006; Stark et al., 2006; Svoboda et al., 2010), thus with the potential to reduce carbon uptake. Finally, the generalized increase of the erosion risk after a wildfire (Lindenmayer et al., 2008; Spanos et al., 2005; Thomas et al., 1999; Yang et al., 2003) leads to a negative synergic effect through the soil impoverishment, reinforcing the impact of salvage logging on carbon emissions. Thus, in general salvage logging applied after a wildfire in coniferous forests has the potential to alter soil properties, retarding vegetation recovery and thus the carbon uptake capacity.

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4.1. MANAGEMENT IMPLICATIONS Fires destroy large areas of forest every year in many areas of the world (FAO, 2007). A key management decision after a forest fire is to determine the fate of the burnt wood, and an intense debate surrounds the practice of salvage logging as it has ecological, economical and silvicultural implications (Beschta et al., 2004; DellaSala et al., 2006; Donato et al., 2006; Lindenmayer et al., 2008). Our study demonstrates, for the first time, that the removal of burnt wood retards the capacity of such ecosystems to restore their carbon sink capacity in Mediterranean climates. Thus, in terms of policies for optimization of carbon sequestration in the context of the climate change, salvage logging should be discouraged. Potential implications at the global scale are aggravated by the predicted increase in wildfire incidence for climate change scenarios in Mediterranean and other semi-arid climates of the world (IPCC, 2007). Applying alternative management strategies for burnt wood following wildfire could therefore suppose a notable variation in carbon release to the atmosphere at a global scale, even without considering CO2 emissions by the heavy machinery used in salvage logging operations (Stephens et al., 2009).

5. ACKNOWLEDGEMENTS

Thanks to Francisco Domingo, Alfredo Durán and Ángela Sánchez– Miranda Moreno for their help in the field. We thank to the Consejeria de Medio Ambiente (Junta de Andalucía) and to the Parque Nacional y Natural de Sierra Nevada for support in the establishment of the treatments. This work was financed by the projects (SUM2006-00010-00-00) of the INIA, (10/2005) of the Organismo Autónomo de Parques Nacionales (MMA), and in part by the Spanish national CO2 flux tower network (Carbored-II; CGL2010-22193-C04-02), Consolider-Ingenio MONTES (CSD2008-00040) and the European Community 7th 9 Framework Programme project GHG-Europe (FP7/2007-2013; grant agreement 244122).

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for defensible annual sums of net ecosystem exchange. Agricultural and Forest Meteorology 107, 43 - 69. FAO, 2007. State of the World’s Forest. Food and Agriculture Organization of the United Nations, Rome. Gough, C.M., Vogel, C.S., Kazanski, C., Nagel, L., Flower, C.E., Curtis, P.S., 2004. Coarse woody debris and the carbon balance of a north temperate forest. Forest Ecology and Management 244, 60-67. Goulden, M.L., Munger, J.W., Fan, S.-M., Daube, B.C., Wofsy, S.C., 1996. Measurements of carbon sequestration by long-term eddy covariance: methods and a critical evaluation of accuracy. Global Change Biology 2, 162-182. Greene, D.F., Gauthier, S., Noel, J., Rousseau, M., Bergeron, Y., 2006. Afield experiment to determine the effect of post-fire salvage on seedbeds and tree regeneration. Frontiers in Ecology and the Environment 4, 69-74. Grove, S.J., 2003. Coarse woody debris, biodiversity and management: a review with particular reference to Tasmanian wet eucalypt forests. Australian Forestry 66, 258-272. Hafner, S.D., Groffman, P.M., 2005. Soil nitrogen cycling under litter and coarse woody debris in a mixed forest in New York State. Soil Biology and Biochemistry 37, 2159-2162. Harden, J.W., E., T.S., Stocks, B.J., Hirsch, A., Gower, S.T., O'Neill, K.P., Kasischke, E.S., 2000. The role of fire in the boreal carbon budget. Global Change Biology 6, 174-184. Harding, R.J., Gryning, S.-E., Halldin, S., Lloyd, C.R., 2001. Progress in understanding of land surface/atmosphere exchanges at high latitudes. Theoretical and Applied Climatology 70, 5-18. Harmon, M.E., Franklin, J.F., Swanson, F.J., Sollins, P., Gregory, S.V., Lattin, J.D., Anderson, N.H., Cline, S.P., Aumen, N.G., Sedell, J.R., Lienkaemper, G.W., Cromack, K., Cummins, K.W., 1986 Ecology of Coarse Woody Debris in Temperate Ecosystems. Advances in Ecological Research 15, 133-302. IPCC, 2007. Climate Change, 2007.The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC, Cambridge. Irvine, J., Law, B.E., Hibbard, K.A., 2007. Postfire carbon pools and fluxes in semiarid ponderosa pine in Central Oregon. Global Change Biology 13, 1748-1760. Janssens, I.A., Lankreijer, H., Matteucci, G., Kowalski, A.S., Buchmann, N., Epron, D., Pilegaard, K., Kutsch, W., Longdoz, B., Grünwald, T., Montagnani, L., Dore, S., Rebmann, C., Moors, E.J., Grelle, A., Rannik, Ü., Morgenstern, K., Oltchev, S., Clement, R., Gudmundsson, J., Minerbi, S., Berbigier, P., Ibrom, A., Moncrieff,

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J.B., Aubinet, M., Bernhofer, C., Jensen, N.O., Vesala, T., Granier, A., Schulze, E.-D., Lindroth, A., Dolman, A.J., Jarvis, P.G., Ceulemans, R., Valentini, R., 2001. Productivity overshadows temperature in determining soil and ecosystem respiration across European forests. Global Change Biology 7, 269 - 278. Järvi, L., Mammarella, I., Eugster, W., Ibrom, A., Siivola, E., Dellwik, E., Keronen, P., Burba, G., Vesala, T., 2009. Comparison of net CO2 fluxes measured with openand closed-path infrared gas analyzers in urban complex environment. Boreal Environmental Research 14, 499-514. Johnson, D.W., Murphy, J.F., Susfalk, R.B., Caldwell, T.G., Miller, W.W., Walker, R.F., Powers, R.F., 2005. The effects of wildfire, salvage logging, and post-fire Nfixation on the nutrient budgets of a Sierran forest. . Forest Ecology and Management 220, 155-165. Jomura, M., Kominami, Y., Dannoura, M., Kanazawa, Y., 2008. Spatial variation in respiration from coarse woody debris in a temperate secondary broad-leaved forest in Japan. . Forest Ecology and Management 255, 149-155. Kappes, H., Catalano, C., Topp, W., 2007. Coarse woody debris ameliorates chemical and biotic soil parameters of acidified broad-leaved forests. Applied Soil Ecology 36, 190-198. Lasslop, G., Reichstein, M., Papale, D., Richardson, A.D., Arneth, A., Barr, A., Stoy, P., Wohlfahrt, G., 2010. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation. Global Change Biology 16. Lindenmayer, D.B., Burton, P.J., Franklin, J.F., 2008. Salvage Logging and its Ecological Consequences. Island Press, Washington. Lindenmayer, D.B., Noss, R.F., 2006. Salvage logging, ecosystem processes, and biodiversity conservation. Conservation Biology.. 20, 949-958. Lloret, F., Calvo, E., Pons, X., Díaz-Delgado, R., 2002. Wildfires and landscape patterns in the Eastern Iberian Peninsula. Landscape Ecology 17, 745–759. Loescher, H.W., Ocheltree, T., Tanner, B.D., Swiatek, E., Dano, B., Wong, J., Zimmerman, G., Campbell, J., Stock, C., Jacobsen, L., Shiga, Y., Kollas, J., Liburdy, J., Law, B.E., 2005. Comparison of temperature and wind statistics in contrasting environments among different sonic anemometer–thermometers. Agricultural and Forest Meteorology 133, 119-139. Magnani, F., Mencuccini, M., Borghetti, M., Berbigier, P., Berninger, F., Delzon, S., Grelle, A., Hari, P., Jarvis, P.G., Kolari, P., Kowalski, A.S., Lankreijer, H., Law, B.E., Lindroth, A., Loustau, D., Manca, G., Moncrieff, J.B., Rayment, M., Tedeschi, V., Valentini, R., Grace, J., 2007. The human footprint in the carbon cycle of temperate and boreal forests. Nature 447, 848-850.

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Marañón-Jiménez, S., Castro, J., Kowalski, A.S., Serrano-Ortiz, P., Reverter, B.R., Sánchez-Cañete, E.P., Zamora, R., 2011. Post-fire soil respiration in relation to burnt wood management in a Mediterranean mountain ecosystem. Forest Ecology and Management 261, 1436-1447. Martinez-Sanchez, J.J., Ferrandis, P., de las Heras, J., Herranz, J.M., 1999. Effect of burnt wood removal on the natural regeneration of Pinus halepensis after fire in a pine forest in Tus valley (SE Spain). Forest Ecology and Management 123, 1-10. McIver, J.D., Starr, L., 2000. Environmental Effects of Postfire Logging: Literature Review and Annotated Bibliography. U.S. Department of Agriculture, Portland, Oregon. McMillen, R.T., 1988. An eddy correlation technique with extended applicability to nonsimple terrain. Boundary-Layer Meteorology 43, 231 - 245. Merino, A., Real, C., Álvarez-González, J.G., Rodríguez-Guitián, M.A., 2007. Forest structure and C stocks in natural Fagus sylvatica forest in southern Europe: The effects of past management. Forest Ecology and Management 250, 206-214. Mkhabela, M.S., Amiro, B.D., Barr, A.G., Black, T.A., Hawthorne, I., Kidston, J., McCaughey, J.H., Orchansky, A.L., Nesic, Z., Sass, A., Shashkov, A., Zha, T., 2009. Comparison of carbon dynamics and water use efficiency following fire and harvesting in Canadian boreal forests. Agricultural and Forest Meteorology 149, 783-794. Molero-Mesa, J., Pérez-Raya, F., Valle-Tendero, F., 1996. Parque Natural de Sierra Nevada, Madrid. Moncrieff, J.B., Massheder, J.M., Bruin, H., Elbers, J., Friborg, T., B., H.b., Kabat, P., Scott, S., Soegaard, H., Verhoef, A., 1997. A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide. Journal of Hydrology 188-189, 589-611. Moreno, J.M., Vázquez, A., Vélez, R., 1998. Recent history of forest fires in Spain. Large forest fire. In: Moreno, J.M. (Ed.). Backhuys Publishers, Leiden, pp. 159-185. Page, S.E., Siegert, F., Rieley, J.O., Boehm, H.-D.V., Jayak, A., Limink, S., 2002. The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420, 61-65. Pérez-Batallón, P., Ouro, G., Merino, A., Macías, F., 1998. Descomposición de materia orgánica, biomasa microbiana y emisión de CO2 en un suelo forestal bajo diferentes manejos selvícolas. Edafología 5, 83-93. Quintana, J.R., Cruz, A., Fernández-González, F., Moreno, J.M., 2004. Time of germination and establishment success after fire of three obligate seeders in a Mediterranean shrubland of central Spain. Journal of Biogeography 31, 241–249.

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Reichstein, M., Falge, E., Baldocchi, D.D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T.G., Granier, A., Grünwald, T., Havrankova, K., Ilvesniemi, H., knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.M., Pumpane, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., Valentini, R., 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11, 1-16. Relva, M.A., López-Westerholm, C., Kitzberger, T., 2009. Effects of introduced ungulates on forest understory communities in northern Patagonia are modified by timing and severity of stand mortality. . Plant Ecology 201, 11-22. Reverter, B.R., Sanchez-Cañete, E.P., Resco, V., Serrano-Ortiz, P., Oyonarte, C., Kowalski, A.S., 2010. Analyzing the major drivers of NEE in a Mediterranean alpine shrubland. Biogeosciences 7, 2601-2611. Richardson, A.D., Hollinger, D., 2007. A method to estimate the additional uncertainty in gap-filled NEE resulting from long gaps in the CO2 flux record. Agricultural and Forest Meteorology 147, 199-208. Ripple, W.J., Larsen, E.J., 2001. The role of post-fire coarse woody debris in aspen regeneration. Western Journal of Applied Forestry 16, 61-64. Rost, J., Clavero, M., Bas, J.M.P., P., 2010. Building wood debris piles benefits avian seed dispersers in burned and logged Mediterranean pine forests. . Forest Ecology and Management 260, 79-86. Rost, J., Pons, P., Bas, J.M., 2009. Can salvage logging affect seed dispersal by birds into burned forests? Acta Oecologica 35, 763-768. Santos, A.J.B., Silva, G.T.D.A., Miranda, H.S., Miranda, A.C., Lloyd, J., 2003. Effects of fire on surface carbon, energy and water vapour fluxes over campo sujo savanna in central Brazil. Functional Ecology 17, 711-719. Schmid, H.P., 1994. Source areas for scalars and scalar fluxes. Boundary-Layer Meteorolology 67, 293-318. Schmid, H.P., 1997. Experimental design for flux measurements: matching scales of observations and fluxes. Agricultural and Forest Meteorology 87, 179-200. Schmid, H.P., 2002. Footprint modeling for vegetation atmosphere exchange studies: a review and perspective. Agricultural and Forest Meteorology 113, 159–183. Smaill, S.J., Clinton, P.W., Greenfield, L.G., 2008. Postharvest organic matter removal effects on FH layer and mineral soil characteristics in four New Zealand Pinus radiata plantations. Forest Ecology and Management 256, 558-563.

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Spanos, I., Raftoyannis, Y., Goudelis, G., Xanthopoulou, E., Samara, T., Tsiontsis, A., 2005. Effects of postfire logging on soil and vegetation recovery in a Pinus halepensis Mill. forest of Greece. Plant and Soil 278, 171-179. Stark, K.E., Arsenault, A., Bradfield, G.E., 2006. Soil seed banks and plant community assembly following disturbance by fire and logging in interior Douglas-fire forests of south-central British Columbia. Canadian Journal of Botany 84, 1548-1560 Stephens, S.L., Moghaddas, J.J., Hartsough, B.R., Moghaddas, E.E.Y., Clinton, N.E., 2009. Fuel treatment effects on stand-level carbon pools, treatment-related emissions, and fire risk in a Sierra Nevada mixed-conifer forest. . Canadian Journal of Forest Research 39, 1538-1547. Stoddard, M.T., Huffman, D.W., Alcoze, T.M., Fule, P.Z., 2008. Effects of slash on herbaceous communities in pinyon-juniper woodlands of northern Arizona. Rangeland Ecology and Management 61, 485-495. Svoboda, M., Fraver, S., Janda, P., Bace, R., Zenahlikova, J., 2010. Natural development and regeneration of a Central European montane spruce forest. Forest Ecology and Management 260, 707-714. Tanny, J., Dicken, U., Cohen, S., 2010. Vertical variation in turbulence statistics and energy balance in a banana screenhouse. Biosystems Engineering 106, 175-187. Thomas, A.D., Walsh, R.P.D., Shakesby, R.A., 1999. Nutrient losses in eroded sediment after fire in eucalyptus and pine forests in the wet Mediterranean environment of northern Portugal. Catena 36, 283-302. Van der Werf, G.R., Randerson, J.T., Collatz, G.J., Giglio, L., 2003. carbon emissions from fires in tropical and subtropical ecosystems. Global Change Biology 9, 547562. Viedma, O., Moreno, J.M., Rieiro, I., 2006. Interactions between land use/land cover change, forest fires and landscape structure in Sierra de Gredos (Central Spain). Environmental Conservation 33, 212-222. Webb, E.K., Pearman, G.I., Leuning, R., 1980. Correction of flux measurements for density effects due to heat and water vapor transfer. Q. J. R. Meteorological Society 106, 85 - 100. Wei, X., Kimmins, J.P., Peel, K., Steen, O., 1997. Mass and nutrients in woody debris in harvested and wildfire-killed lodgepole pine forests in the central interior of British Columbia. . Canadian Journal of Forest Research 27, 148-155. Wilson, A., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D.D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolmanh, H., Field, C., Grelle, A., Ibrom, A., Lawl, B.E., Kowalski, A.S., Meyers, T., Moncrieffm, J., Monsonn, R., Oechel, W., Tenhunen, J., Valentini, R., Verma, S.B., 2002. Energy balance closure at FLUXNET sites. Agricultural and Forest Meteorology 113, 223-243.

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Wofsy, S.C., Goulden, M.L., Munger, J.W., Fan, S.-M., Bakwin, P.S., Daube, B.C., Bassow, S.L., Bazzaz, F.A., 1993. Net Exchange of CO2 in a Mid-Latitude Forest. Science 260, 1314-1317. Wohlfahrt, G., Fenstermaker, L.F., Arnone, J.A., 2008. Large annual net ecosystem CO2 uptake of a Mojave Desert ecosystem. Global Change Biology 14, 1475-1487. Yang, Y.S., Guo, J.F., Chen, G.S., He, Z.M., Xie, J.S., 2003. Effect of slash burning on nutrient removal and soil fertility in Chinese fir and evergreen broadleaved forests of mid-subtropical China. Pedosphere 13, 87-96.

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APPENDIX A:

Recently, a controversial correction has been proposed for eddy covariance measurements in cold environments (Burba et al., 2008). This correction can increase by over 100 g C m-2 annual carbon exchange integrations (Reverter et al., 2010) but does not change the relative difference between treatments in an identical climate. Burba et al., (2008) argued that density measurements by an open path IRGA may be biased when the instrument significantly heats the air that it measures, particularly in cold conditions. Despite the correction proposed by Burba et al., (2008), other scientists (Wohlfahrt et al., 2008; Järvi et al., 2009; Amiro, 2010) consider such an a posteriori correction to be somewhat premature, with no simple adjustment that can be applied universally. For our data, Table A1 shows monthly values of FC and ET both with and without the “self-heating correction” applied. The correction reduces CO2 uptake in NI such that only two months of net CO2 absorption are observed, and increases emissions by more than three times for SL. Notice that this result modifies substantially the absolute values of both annual net carbon exchange values, but changes relative differences between treatments only slightly. In addition, monthly GPP and Reco values, estimated by the DB algorithm, are shown in Table A1 for NI. While values of GPP do not change with the correction, monthly Reco increases dramatically as a result of the influence of the “self-heating correction” on flux partitioning algorithms. As previously reported (e.g., Reverter et al., 2010), ET is found to be comparatively insensitive to the “self-heating correction”.

245

Chapter 5_______________________________________________________________________ Table A1: Monthly values of carbon fluxes (FC, g C m-2), and evapotranspiration (ET, mm) estimated in Non Intervention and Salvage Logging treatments, and gross primary production (GPP, g C m-2) and ecosystem respiration (Reco, g C m-2) for Non Intervention, corrected by instrument heating (C) and not corrected (NC).

Salvage Logging Month

FC

Non Intervention

ET

FC

GPP

Reco

ET

NC

C

NC

C

NC

C

NC

C

NC

C

NC

C

1

-

-

2

20

2

20

9

5

19

42

13

13

2

-

-

0

16

0

16

2

2

6

29

17

17

3

-

-

-2

16

-2

16

10

6

9

27

24

25

4

-

-

-8

12

-8

12

25

23

14

32

38

38

5

-

-

-29

-10

-29

-10

59

59

28

55

60

62

6

19

57

-21

-3

-21

-3

48

48

20

48

58

60

7

22

63

-6

14

-6

14

25

26

15

46

49

50

8

19

58

2

19

2

19

24

26

26

57

38

42

9

14

53

1

17

1

17

25

21

36

50

23

25

10

8

50

2

19

2

19

25

22

31

51

38

39

11

6

46

-13

5

-13

5

18

16

9

29

21

22

12

2

43

-4

15

-4

15

20

9

33

36

24

22

TOTAL

90

371

-77

139

-77

139

290

264

245

502

403

416

246

DISCUSIÓN GENERAL

247

Discusión general________________________________________________________________

248

________________________________________________________________Discusión general

DISCUSIÓN GENERAL

El papel fundamental de los restos gruesos de madera muerta en el capital de nutrientes y los ciclos biogeoquímicos ha sido ampliamente discutido para el caso de bosques vivos poco perturbados. De este modo, se los ha considerado como elementos clave para asegurar la sostenibilidad de los ecosistemas (Harmon et al., 1986), para el mantenimiento de su productividad (Brewer, 2008; Graham et al., 1994; Jurgensen et al., 1997), así como generadores de diferentes hábitats y microclimas que promueven la mayor abundancia y diversidad de organismos (Franklin et al., 2002; Grove y Meggs, 2003; Kappes et al., 2007; McCay y Komoroski, 2004; Reynolds et al., 1992). Sin embargo, a pesar de la controversia existente sobre el manejo más adecuado de la madera quemada tras un incendio forestal, pocos trabajos se centran en el análisis de los efectos del manejo postincendio de la madera quemada sobre la dinámica de nutrientes (Brais et al., 2000; Johnson et al., 2005), el balance del carbono y el funcionamiento biogeoquímico del ecosistema (Lindenmayer et al. 2008; Lindenmayer y Noss, 2006; McIver y Starr, 2000). Además, la mayor parte de estos estudios se centran en el efecto de la extracción intensiva de la madera frente a la ausencia de intervención, a pesar del amplio abanico de posibilidades intermedias existentes. Durante las primeras etapas de establecimiento de un bosque, las plántulas dependen fundamentalmente de los nutrientes existentes en el suelo para su crecimiento y desarrollo, mientras que a medida que se cierra el dosel arbóreo las demandas se satisfacen mediante una mayor proporción de reciclaje interno y retranslocación de nutrientes (Imbert et al., 2004; Landsberg y Coger, 1997). Por ello, la disponibilidad de nutrientes en el suelo en proporciones adecuadas resulta especialmente clave durante las primeras etapas de la sucesión ecológica. Sin embargo, esta condición es particularmente limitante en ecosistemas montaña mediterránea, cuyos suelos son frecuentemente poco desarrollados y pobres en nutrientes (Costa-Tenorio, 1998; Sardans et al., 2005), y más aún cuando esta 249

Discusión general________________________________________________________________

limitación se acentúa tras las pérdidas asociadas a un incendio (Trabaud, 1994; Yang et al., 2003; Capítulo 1). A pesar de que las plantas pueden reflejar cierta limitación de nutrientes en el caso de que esta sea muy acusada, concentran en sus tejidos los elementos minerales existentes en el suelo en las proporciones necesarias para su desarrollo, absorbiendo preferentemente los nutrientes que más limitan su crecimiento (Ingestad, 1979; Capítulo 1). Aún después de un incendio de alta intensidad, en el que se queman la totalidad de las fracciones finas de vegetación con mayor concentración de nutrientes, la mayor parte de la biomasa leñosa permanece en el ecosistema (Johnson et al., 2005; Stocks et al., 2004; Tinker y Knight, 2000; Wei et al., 1997) con su composición química casi inalterada. Esto conlleva la existencia de un gran capital de nutrientes contenido en la madera quemada (Capítulo 1). De este modo, la madera puede actuar en una primera etapa como reservorio y almacén de nutrientes, amortiguando el impacto del incendio sobre la economía de nutrientes del ecosistema. Más aún, en el Capítulo 1 de esta tesis se observa cómo la relevancia de la madera como fuente potencial de nutrientes coincide bastante con aquellos nutrientes que son deficitarios en el suelo para satisfacer los requerimientos de un bosque maduro de coníferas. Sin embargo, estos nutrientes no son utilizables por la vegetación hasta que no son liberados de forma progresiva mediante la descomposición de la madera y retenidos por el suelo. En el Capítulo 2 mostramos cómo a pesar de las lentas tasas de descomposición típicas de ecosistemas mediterráneos, en los que la humedad es limitante durante los periodos de mayores temperaturas, la madera libera N y especialmente P desde etapas tempranas. Así, durante el periodo transcurrido de este estudio la liberación de N y P por la madera quemada se estima en unos 8 kg ha-1 año-1 y 0.7 kg ha-1 año-1 respectivamente, aunque esta cifra puede variar considerablemente entre años. Esto supone alrededor de un 20% de los requerimientos anuales de N y P de los bosques de coníferas (ca. 40 kg ha-1 año-1 250

________________________________________________________________Discusión general

de N y 4 kg ha-1 año-1 de P; Cole y Rapp, 1981; Helmisaari, 1995; Johnson y Lindberg, 1992; Miller, 1986). Estos aportes superan además las contribuciones de otras posibles entradas en el ecosistema, como las asociadas a la deposición atmosférica (ca. 6.3 kg ha-1 año-1 año de N y 0.2 kg ha-1 año-1 de P; MoralesBaquero et al., 2006), o las debidas a la fijación de N en las raíces de leguminosas como Adenocarpus decorticans, presentes en la zona de estudio (ca. 1 kg ha-1 año-1 de N; Moro et al., 1996). La presencia de la madera quemada provoca, ya sea de forma directa a través de los aportes de nutrientes de la madera, o indirectamente, mediante la reducción de las pérdidas de nutrientes por erosión (Thomas et al., 2000) o mejora del microclima (Bros et al., 2011; Castro et al., 2011), un aumento efectivo del contenido en materia orgánica, de la biomasa microbiana, de la disponibilidad de nutrientes, y en su retención por parte de los microorganismos del suelo. Estos factores, unidos a la reducción de la densidad aparente del suelo, suponen un aumento de la fertilidad, el fomento de los procesos de reciclaje de nutrientes y, en definitiva, la mejora de las funciones ecológicas del suelo (Capítulos 2 y 3). Todo ello nos lleva a considerar la madera quemada como un elemento del ecosistema que desempeña importantes servicios ecosistémicos (Millennium Ecosystem Assessment [MEA], 2003), dado el beneficio que reporta al conjunto de la sociedad por su capacidad reguladora de procesos ecosistémicos clave (servicio de regulación) sobre la degradación del suelo y la erosión, así como el suministro de servicios de base, como la formación del suelo, el secuestro de carbono y los ciclos de los nutrientes. La mayor calidad del suelo y la mejora del microclima por la presencia de restos de madera tienen implicaciones directas sobre la regeneración de la vegetación tras el incendio. De este modo, y tal como queda de manifiesto en el Capítulo 3, las plántulas de pino establecidas en los tratamientos con restos de madera quemada tienen un mayor crecimiento, biomasa y vigor, probablemente asociados a la reducción del estrés hídrico, por un lado, y a la mayor disponibilidad

251

Discusión general________________________________________________________________

de nutrientes en el suelo (Capítulo 2), por otro. Sin embargo, al igual que en la madera de los árboles quemados (Capítulo 1), las concentraciones de nutrientes en las acículas de las plántulas de pino reflejaron deficiencias en micronutrientes (Fe, Mn, Zn, Cu), siendo estas muy bajas comparadas con los valores encontrados en la literatura para las mismas especies (Bonneau, 1995; López Varela et al., 2008; Merino et al., 2005; van Wesemael, 1993). Entre los macronutrientes, las acículas también mostraron carencias de P y, en menor medida, de N (Álvarez-Álvarez et al., 2011; Augusto et al., 2008; Bará, 1991; Bonneau, 1995; Dumbrell y McGrath, 2003; Merino et al., 2005; Montero et al., 1999; Warren et al., 2005) prevaleciendo estas deficiencias independientemente del tratamiento. A pesar de que la madera quemada ha demostrado mejorar la fertilidad y disponibilidad de nutrientes en el suelo (Capítulo 2), la incorporación de estos nutrientes por las plantas estará condicionada por su existencia en formas asimilables y en proporciones adecuadas. De este modo, la carencia de un determinado nutriente en sus formas asimilables o su existencia en proporciones muy diferentes a las necesarias para las plantas puede interferir en la incorporación de otros nutrientes y provocar incluso una ralentización del crecimiento (Chapin et al., 2002; Clarkson y Hanson, 1980, en Schlesinger, 1997). Los aportes de estos nutrientes limitantes en los tratamientos donde no se extrajo la madera quemada explicarían, en parte, el mayor crecimiento y biomasa de los pinos a pesar de la ausencia de diferencias en su estado nutricional entre los diferentes tratamientos. Estos resultados implican además una mayor incorporación de nutrientes por las plántulas en presencia de madera quemada, lo que sugiere la mitigación de esta limitación aunque no desaparezca por completo. En definitiva, los resultados muestran que la presencia de madera se traduce en una mejora de las condiciones microclimáticas (Castro et al., 2011) y edáficas (Capítulo 2) para el desarrollo de las plántulas de pino. Las ramas y troncos quemados actúan así como estructuras nodriza que facilitan la regeneración tras el incendio sin añadir con ello una competencia por los recursos a nivel de las raíces (Castro et al., 2011). 252

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El manejo post-incendio de la madera quemada tiene también implicaciones de gran relevancia en el ciclo del carbono, ya que este elemento es el principal componente de la madera. En este estudio, la cantidad de carbono existente inicialmente tras el incendio en la biomasa aérea de madera quemada y las raíces se estimó en unos 22.000±3.000 kg ha-1, mientras que los primeros 10 cm del suelo albergaron unos 20.000±5.000 kg ha-1 de carbono (Capítulo 1). Por tanto, la madera quemada supuso, en aquellos tratamientos en los que no se extrajo, un 54% aprox. del carbono total contenido en ambos reservorios. Parte de este carbono es emitido de forma directa y progresiva a la atmósfera como CO2 (Gough y Seiler, 2004; Progar et al., 2000; Wang et al., 2002), y otra parte es liberada al suelo en forma de sustratos orgánicos potencialmente mineralizables por los microorganismos (Hafner et al., 2005; Kuenhe et al., 2008; Spears y Lajha, 2004). Así, durante la primera etapa de descomposición recogida en este estudio, se estima que la madera quemada libera anualmente unos 430 kg ha-1 de carbono al suelo y a la atmósfera, aunque esta cantidad es también bastante variable entre años, siendo esperable que decrezca exponencialmente a medida que disminuye su cantidad y se hace más recalcitrante (Brown et al., 1996; Weedon et al., 2009; Capítulo 2). Así, la presencia de la madera incrementó la concentración de materia orgánica en el suelo en un 18%, el carbono total un 42% y el carbono orgánico disuelto un 49% (Capítulo 2). Por tanto, dada la lenta descomposición de la madera y la difícil mineralización de los compuestos orgánicos liberados al suelo, éstos pueden constituir un importante almacén potencial de carbono en el ecosistema (Laiho y Prescott, 2004; Mackensen y Bauhus, 2003). Por otro lado, la presencia de la madera quemada favorece el aumento de las tasas de actividad biológica, lo cual se refleja tanto en la productividad de la vegetación como de la respiración del suelo, como se discute en los Capítulos 3, 4 y 5. Esto se interpreta como un incremento de las tasas de mineralización, incorporación y reciclaje de nutrientes y, por tanto, del funcionamiento ecológico

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del suelo. Este hecho también se constata en el Capítulo 2, en el que se muestra cómo la biomasa microbiana y la incorporación de nutrientes por parte de los microorganismos se ven favorecidas bajo los troncos de madera quemada. Además, la relación C/N en los microorganismos del suelo también desciende, a pesar de que el incremento de la relación C/N en el suelo puede acentuar la limitación de N para los microorganismos (Hafner et al., 2005; Magill y Aber, 2000). No obstante, la mineralización de la materia orgánica del suelo y, por tanto, la liberación de nutrientes en formas asimilables por las plantas, sería comparativamente más lenta que en casos de aportes de materia orgánica de menor ratio C/N y/o fácilmente mineralizables (Phillips et al., 2011). De hecho, la adición de sustratos orgánicos lábiles y nutrientes (N y P) puede estimular la descomposición del carbono orgánico ya existente en el suelo (Kuzyakov, 2010; Milcu et al., 2011) y, por tanto, incrementar la emisión de CO2 (Heath et al., 2005), lo cual resultaría, por otro lado, contraproducente para el mantenimiento de la capacidad de secuestro de carbono del suelo (Hoosbeek et al., 2004). Los aportes de sustratos orgánicos de difícil mineralización, sin embargo, posibilitan el aumento de la capacidad de retención del suelo por la mayor persistencia de la materia orgánica (Capítulo 2), lo que ayudaría a reducir las pérdidas de nutrientes por lavado y lixiviación.  La madera quemada además desempeña una importante función ayudando a amortiguar y favorecer las condiciones microclimáticas del suelo. En este tipo de ecosistemas mediterráneos la disponibilidad de agua puede resultar particularmente limitante para el desarrollo de la vegetación y la actividad microbiana (Almagro et al., 2009; Casals et al., 2000; Sardans et al., 2005; Xu y Baldocchi, 2004; ver Capítulos 3 y 4). Además, tras un incendio, las temperaturas que alcanza el suelo durante las horas centrales del día pueden llegar a ser muy elevadas, debido al color oscuro de los restos vegetales carbonizados y la consiguiente reducción del albedo (Amiro et al., 1999; Majorowicz y Skinner, 1997; ver temperaturas del suelo en Capítulo 4 y razón de Bowen en el Capítulo 5). La presencia de madera quemada

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contribuye a reducir el calentamiento del suelo y al mantenimiento de la humedad, particularmente cuando los restos de madera quemada se encuentran en contacto con el suelo (Castro et al., 2011; Bros et al., 2011). Como se ha mencionado, esta función ecosistémica de la madera quemada contribuye a reducir el estrés hídrico de las plantas (Capítulo 3) y los microorganismos del suelo (Capítulo 4), contribuyendo a acelerar el desarrollo y crecimiento de la vegetación y las tasas de respiración y mineralización de los microorganismos (Capítulos 3 y 4). Desde el punto de vista de las emisiones globales de CO2, la productividad primaria supone un sumidero de carbono, mientras que la respiración del suelo y las emisiones directas de carbono a la atmósfera por la descomposición de la madera constituyen fuentes de emisión de CO2. Al constituir flujos contrapuestos, estos procesos son contrarios en cuanto sus implicaciones para el ciclo del carbono, aunque se verán favorecidos simultáneamente por los mismos factores (disponibilidad nutrientes, agua, temperatura, etc.; Irvine et al., 2007; Janssens et al., 2001; Mkhabela et al., 2009). Por tanto, la evaluación del efecto neto resultante de la presencia de la madera quemada en las emisiones de carbono a nivel de ecosistema no resulta sencilla. En el Capítulo 5, se muestra cómo el aumento de la productividad primaria de la vegetación en presencia de madera quemada contribuye a compensar las mayores emisiones de CO2 por respiración (vistas en el Capítulo 4) y descomposición de la madera, inclinando el balance hacia un mayor secuestro de carbono. Para la evaluación de las implicaciones que los diferentes tratamientos de manejo de la madera quemada tendrían en el balance neto del carbono debería incluirse además el consumo de combustibles fósiles durante los trabajos de extracción de la madera, su transporte y su procesado (Stephens et al., 2009). Esto llevaría a incrementar aún más las diferencias existentes en el balance global del carbono entre la extracción intensiva de la madera y la ausencia de intervención. Además, en el caso de la retirada de la madera, el uso final que se le da a la madera 255

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quemada y la proporción de los productos destinados a los reservorios de carbono de corto (i.e.: papel, biomasa, etc.) o largo plazo (i.e.: mobiliario, estructuras, etc.) también será determinante (Lindenmayer et al., 2008), aspectos que no han sido considerados en la presente tesis. Otros aspectos a tener en cuenta cuando se interviene en un bosque tras un incendio, y que no se han considerado específicamente en este trabajo, son el impacto que produce la introducción de maquinaria pesada en el ecosistema. A menudo, los trabajos de corte y extracción de la madera coinciden con el periodo de emergencia de las plántulas (Donato et al., 2006; Fernández et al., 2008; Greene et al., 2006; Martínez-Sánchez et al., 1999), sobre todo en el caso de especies pirófitas como son los pinos procedentes de semillas liberadas de piñas serotinas (Tapias et al., 2001). Esto implica con frecuencia una mayor mortalidad de las plántulas emergentes (Donato et al., 2006; Fernández et al., 2008; MartínezSánchez et al., 1999). Además, la compactación del suelo que se produce en las zonas donde se introduce la maquinaria pesada (McIver y McNeil, 2006; McIver y Starr, 2000, 2001) puede dificultar la penetración de las raíces (Schoenholtz et al., 2000) y modificar la disponibilidad de agua (Gómez et al., 2002), con el consiguiente detrimento en el desarrollo y supervivencia de las plántulas. La persistencia de la madera quemada in situ sin la utilización de maquinaria pesada puede provocar, sin embargo, una reducción de la densidad aparente del suelo (Capítulo 2) y dar lugar, por tanto, a una mayor porosidad y aireación (Merino y Edeso, 1999; Schoenholtz et al., 2000). Ello favorece la penetración de las raíces y el agua de lluvia con lo que se reduce la escorrentía y arrastre del suelo. Más aún, la disposición de los troncos, ramas quemadas y otros restos orgánicos sobre el suelo ha demostrado actuar como barreras de contención que reducen el arrastre y pérdida de suelo y cenizas que se depositan tras el incendio, ya sea cuando estas se disponen estratégicamente con esta finalidad (Fox, 2011; Kim et al., 2008; Robichaud, 2005; Robichaud et al., 2008; Wagenbrenner et al., 2006) o bien

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simplemente debido a su presencia sobre el suelo (Fernández et al., 2007; Shakesby et al., 1996; Thomas et al., 2000; observación personal). Esta función de los restos de madera quemados reporta, por tanto, beneficios al ecosistema tanto desde el punto de vista biogeoquímico, al reducir la pérdida de nutrientes (Beschta et al., 2004; McIver y McNeil, 2006), como hidrológico, al reducir la concentración de sedimentos y de estos elementos en las aguas (Karr et al., 2004; Wondzell, 2001). En resumen, los resultados de esta tesis doctoral ponen de manifiesto que la madera quemada tras un incendio forestal desempeña un papel esencial en la regulación de la disponibilidad de nutrientes y la protección física del suelo, mejorando el microclima y reduciendo el riesgo de erosión y arrastre. Estas funciones contribuyen a la recuperación de funcionalidad ecológica y el mantenimiento de procesos ecológicos clave, como son la fertilidad del suelo, la actividad microbiológica y la movilización de nutrientes, lo que favorece el desarrollo de la vegetación y la recuperación de la capacidad de secuestro de carbono del ecosistema. Por el contrario, la retirada intensiva de la madera quemada supone una perturbación adicional al ecosistema que se añade a las perturbaciones ya ejercidas por los incendios. Su efecto acumulado puede tener un impacto sinérgico negativo sobre el ecosistema (Lindenmayer et al., 2008), aumentando el riesgo de superar el umbral de impacto reversible (Lindenmayer y Ough, 2006; Paine et al., 1998). Los resultados de esta tesis pretenden servir de ayuda de manera directa en la toma de decisiones sobre el manejo de la madera quemada tras un incendio forestal. Las conclusiones que se extraen en el presente estudio son especialmente extrapolables a ecosistemas mediterráneos, así como a otros ecosistemas con similar limitación de nutrientes y humedad, en los que la persistencia de la madera quemada en el ecosistema actúe aliviando dichos factores limitantes para la regeneración de la vegetación.

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Merino, A., Edeso, J.M., 1999. Soil fertility rehabilitation in young Pinus radiata D. Don. plantations from Northern Spain after intensive site preparation. Forest Ecology and Management 116, 83-91. Milcu, A., Heim, A., Ellis, R.J., Scheu, S., Manning, P., 2011. Identification of general patterns of nutrient and labile carbon control on soil carbon dynamics across a successional gradient. Ecosystems 14, 710-719. Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being: Synthesis.Island Press, Washington, DC. Miller, H.G., 1986. Carbon x nutrient interactions - the limitations to productivity. Tree Physiology 2, 373-385. Mkhabela, M.S., Amiro, B.D., Barr, A.G., Black, T.A., Hawthorne, I., Kidston, J., McCaughey, J.H., Orchansky, A.L., Nesic, Z., Sass, A., Shashkov, A., Zha, T., 2009. Comparison of carbon dynamics and water use efficiency following fire and harvesting in Canadian boreal forests. Agricultural and Forest Meteorology 149, 783-794. Montero, G., Ortega, C., Cañellas, I., Bachiller, A., 1999. Productividad aérea y dinámica de nutrientes en una repoblación de Pinus pinaster Ait. sometida a distintos regímenes de claras. Investigación Agraria: Sistemas y Recursos Forestales Fuera de Serie n° 1. Morales-Baquero, R., Pulido-Villena, E., Reche, I., 2006. Atmospheric inputs of phosphorus and nitrogen to the southwest Mediterranean region: Biogeochemical responses of high mountain lakes. Limnology and Oceanography 51, 830-837. Moro, M.J., Domingo, F., Escarre, A., 1996. Organic matter and nitrogen cycles in a pine afforested catchment with a shrub layer of Adenocarpus decorticans and Cistus laurifolius in south-eastern Spain. Annals of Botany 78, 675-685. Paine, R.T., Tegner, M.J., Johnson, E.A., 1998. Compounded perturbations yield ecological surprises. Ecosystems 1, 535-545. Phillips, R.P., Finzi, A.C., Bernhardt, E.S., 2011. Enhanced root exudation induces microbial feedbacks to N cycling in a pine forest under long-term CO2 fumigation. Ecology Letters 14, 187-194. Progar, R.A., Schowalter, T.D., Freitag, C.M., Morrell, J.J., 2000. Respiration from coarse woody debris as affected by moisture and saprotroph functional diversity in Western Oregon. Oecologia 124, 426-431. Reynolds, R.T., Graham, R.T., Reiser, M.H., Bassett, R.L., Kennedy, P.L., Boyce Jr, D.A., Goodwin, G., Smith, R., Fisher, E.L., 1992. Management recommendations for the northern goshawk in the Southwestern United States. USDA Forest Service General Technical Report RM-217, 90.

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Robichaud, P.R., 2005. Measurement of post-fire hillslope erosion to evaluate and model rehabilitation treatment effectiveness and recovery. International Journal of Wildland Fire 14, 475-485. Robichaud, P.R., Pierson, F.B., Brown, R.E., Wagenbrenner, J.W., 2008. Measuring effectiveness of three postfire hillslope erosion barrier treatments, western Montana, USA. Hydrological Processes 22, 159-170. Sardans, J., Peñuelas, J., Rodá, F., 2005. Changes in nutrient use efficiency, status and retranslocation in young post-fire regeneration Pinus halepensis in response to sudden N and P input, irrigation and removal of competing vegetation. Trees 19 233-250. Schlesinger, W.H., 1997. Biogeochemistry-An analysis of Global Change. Academic Press, San Diego. Schoenholtz, S.H., Miegroet, H.V., Burger, J.A., 2000. A review of chemical and physical properties as indicators of forest soil quality: challenges and opportunities. Forest Ecology and Management 138, 335-356. Shakesby, R.A., Boakes, D.J., Coelho, C.d.O.A., Gonçalves, A.J.B., Walsh, R.P.D., 1996. Limiting the soil degradational impacts of wildfire in pine and eucalyptus forests in Portugal : A comparison of alternative post-fire management practices. Applied Geography 16, 337-355. Spears, J.D.H., Lajtha, K., 2004. The imprint of coarse woody debris on soil chemistry in the western Oregon Cascades. Biogeochemistry 71, 163-175. Stephens, S.L., Moghaddas, J.J., Hartsough, B.R., Moghaddas, E.E.Y., Clinton, N.E., 2009. Fuel treatment effects on stand-level carbon pools, treatment-related emissions, and fire risk in a Sierra Nevada mixed-conifer forest. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 39, 1538-1547. Stocks, B.J., Alexander, M.E., Wotton, B.M., Stefner, C.N., Flannigan, M.D., Taylor, S.W., Lavoie, N., Mason, J.A., Hartley, G.R., Maffey, M.E., Dalrymple, G.N., Blake, T.W., Cruz, M.G., Lanoville, R.A., 2004. Crown fire behaviour in a northern jack pine-black spruce forest. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 34, 1548-1560. Tapias, R., Gil, L., Fuentes-Utrilla, P., Pardos, J.A., 2001. Canopy seed banks in Mediterranean pines of southeastern Spain: a comparison between Pinus halepensis Mill., P. pinaster Ait., P. nigra Arn. and P. pinea L. Journal of Ecology 89, 629-638. Thomas, A.D., Walsh, R.P.D., Shakesby, R.A., 2000. Post-fire forestry management and nutrient losses in eucalyptus and pine plantations, northern Portugal. Land Degradation and Development 11, 257-271.

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Tinker, D.B., Knight, D.H., 2000. Coarse woody debris following fire and logging in wyoming lodgepole pine forests. Ecosystems 3, 472-483. Trabaud, L., 1994. The effect of fire on nutrient losses and cycling in a Quercus coccifera garrigue (southern France). Oecologia 99, 379-386. van Wesemael, B., 1993. Litter decomposition and nutrient distribution in humus profiles in some Mediterranean forests in Southern Tuscany. Forest Ecology and Management 57, 99-114. Wagenbrenner, J.W., MacDonald, L.H., Rough, D., 2006. Effectiveness of three post-fire rehabilitation treatments in the Colorado Front Range. Hydrological Processes 20, 2989-3006. Wang, C.K., Bond-Lamberty, B., Gower, S.T., 2002. Environmental controls on carbon dioxide flux from black spruce coarse woody debris. Oecologia 132, 374-381. Warren, C.R., McGrath, J.F., Adams, M.A., 2005. Differential effects of N, P and K on photosynthesis and partitioning of N in Pinus pinaster needles. Annals of Forest Science 62, 1-8. Weedon, J.T., Cornwell, W.K., Cornelissen, J.H.C., Zanne, A.E., Wirth, C., Coomes, D.A., 2009. Global meta-analysis of wood decomposition rates: a role for trait variation among tree species? Ecology Letters 12, 45-56. Wei, X., Kimmins, J.P., Peel, K., Steen, O., 1997. Mass and nutrients in woody debris in harvested and wildfire-killed lodgepole pine forests in the central interior of British Columbia. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 27, 148-155. Wondzell, S.M., 2001. The influence of forest health and protection treatments on erosion and stream sedimentation in forested watersheds of eastern Oregon and Washington. Northwest Science 75, 128-140. Xu, L.K., Baldocchi, D.D., 2004. Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California. Agricultural and Forest Meteorology 123, 79-96. Yang, Y.S., Guo, J.F., Chen, G.S., He, Z.M., Xie, J.S., 2003. Effect of slash burning on nutrient removal and soil fertility in Chinese fir and evergreen broadleaved forests of mid-subtropical China. Pedosphere 13, 87-96.

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CONCLUSIONES

1. La madera quemada que queda tras un incendio forestal contiene aún una importante cantidad de nutrientes y actúa como reserva para el ecosistema en regeneración, lo cual resulta especialmente relevante en ecosistemas asentados sobre suelos pobres o degradados como es el caso. En este estudio, la magnitud de estas reservas fue especialmente importante en el caso del N, K y los micronutrientes Na, Mn, Fe, Zn y Cu, en los que el contenido en la madera quemada fue mayor respecto al existente en los primeros 10 cm de suelo. Es más, la relevancia de la madera como fuente potencial de nutrientes coincidió con buena parte de aquellos nutrientes que son deficitarios en el suelo para satisfacer los requerimientos de un bosque maduro.

2. A medida que se descompone sobre el suelo, la madera actúa como fuente de nutrientes para el ecosistema en regeneración. Ya en los primeros años de descomposición, se produjo una progresiva liberación de N y P, a pesar de la lenta descomposición de la madera en este ecosistema mediterráneo.

3. La presencia de la madera quemada sobre el suelo supuso un aumento efectivo del contenido en materia orgánica, de la biomasa microbiana, de la disponibilidad de nutrientes, y en su retención por parte de los microorganismos del suelo. Estos factores, unidos a la reducción de la densidad aparente del suelo, conllevan un aumento de la fertilidad, el fomento de los procesos de reciclaje de nutrientes y, en definitiva, la mejora de las funciones ecológicas del suelo, ayudando así a restaurar las pérdidas de nutrientes y de fertilidad asociadas a un incendio.

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4. El tratamiento post-incendio de la madera quemada afectó, asimismo, la eficiencia de la regeneración natural del pino resinero. La presencia de la madera quemada tras el incendio incrementó el crecimiento, vigor y con ello, la asimilación de nutrientes de las plántulas durante las primeras etapas de crecimiento. Este efecto facilitador de la madera quemada se asocia probablemente a la reducción del estrés hídrico de las plántulas por la mejora del microclima y a la mayor disponibilidad de nutrientes en el suelo, lo cual supone la aminoración de los factores típicamente limitantes de los bosques de coníferas mediterráneos.

5. La presencia de madera quemada también incrementó la actividad respiratoria del suelo y, por tanto, la emisión de CO2, especialmente en el tratamiento en el que la madera quemada se encuentra en contacto con el suelo. Esta mayor tasa de actividad microbiana en el suelo se interpreta como un indicador del restablecimiento de los procesos de mineralización de la materia orgánica, y de la mejora de la calidad, fertilidad y condiciones edáficas en respuesta a la amortiguación del microclima, al aporte de nutrientes y sustratos orgánicos por parte de la madera quemada y a las contribuciones directas o indirectas de la vegetación a través de la respiración de sus raíces o el suministro de exudados orgánicos fácilmente degradables por los microorganismos.

6. A pesar de las mayores emisiones de CO2 existentes en el tratamiento en el que la madera no fue extraída, el aumento de la productividad primaria de la vegetación en presencia de madera quemada compensó estas emisiones y equilibró el balance neto hacia un mayor secuestro de carbono. Por tanto, en bosques de coníferas mediterráneos afectados por incendios, la extracción intensiva de la madera quemada no se encuentra en consonancia con los

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objetivos de optimización del secuestro de C acordados en el protocolo de Kyoto.

7. En resumen, la madera quemada tras un incendio forestal es un elemento natural que puede proporcionar importantes servicios ecosistémicos, como son, entre otros, la regulación de la disponibilidad de nutrientes y la protección física del suelo, mejorando el microclima y reduciendo el riesgo de erosión y arrastre. Estas funciones favorecen la recuperación y reactivación de procesos ecológicos clave para la regeneración y sostenibilidad del ecosistema. Por el contrario, la retirada intensiva de la madera quemada supone una perturbación adicional que se añade a las perturbaciones ya ejercidas por los incendios, lo cual puede implicar un impacto negativo y sinérgico sobre el ecosistema y un aumento del riesgo de procesos de degradación irreversibles.

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CONCLUSIONS

1. The burnt wood remaining after a forest fire still contains an important amount of nutrients and acts as a reservoir for the regenerating ecosystem. This is especially relevant in ecosystems located over poor or degraded soils as in the present case. In this study, the magnitude of these stocks was especially important in the case of N, K and the micronutrients Na, Mn, Fe, Zn and Cu, whose stocks in the burnt wood were higher than those existing in the upper 10 cm soil layer. Moreover, the relevance of wood as a potential nutrient source coincided with those nutrients that were deficient to satisfy the requirements of a mature forest.

2. As decomposition occurs over the soil, the wood acts as a source of nutrients for the regenerating ecosystem. A progressive release of N and P occurred even during the first years of decomposition, despite the slow wood decay in this Mediterranean ecosystem.

3. The presence of burnt wood over the soil produced an effective increase in the organic matter content, in the microbial biomass, in the nutrient availability, and in its retention by soil microorganisms. These factors, together with the reduction of the soil bulk density, led to increased fertility, enhanced nutrient cycling processes and, ultimately improved soil ecological functions, helping therefore to restore the nutrients and fertility following the wildfire.

4. The post-fire treatment of burnt wood also affected the natural regeneration efficiency of maritime pine. The burnt wood remaining after the fire increased the growth, vigour and thus, the nutrient assimilation of seedlings during the first growing seasons. This facilitative effect of the burnt wood is

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likely attributable to the reduction of the water stress of seedlings, due to the more favourable microclimate, and to higher soil nutrient availability. All this represents the amelioration of factors that typically limit Mediterranean coniferous forests.

5. The presence of burnt wood also increased soil respiratory activity and hence CO2 emissions, especially in the treatment where the burnt wood was in contact with the ground. This higher microbial activity in the soil is interpreted as an indicator of the reestablishment of mineralization processes, and of the improvement of the quality and fertility of edaphic conditions. This is also the consequence of microclimatic amelioration, of the supply of nutrients and organic substrates by the burnt wood, and of the direct and indirect contributions of vegetation through root respiration or organic exudates that are easy for microorganisms to mineralize.

6. Despite the higher CO2 emissions in the treatment where the wood was not removed, the increase in primary productivity in the presence of burnt wood compensated these emissions and pushed the net balance towards higher carbon sequestration. Therefore, in Mediterranean coniferous forests, salvage logging is not consistent with the Kyoto protocol objectives of optimizing carbon sequestration.

7. Summarizing, the burnt wood after a forest fire is a natural element that can provide important ecosystem services, such as the regulation of nutrient availability and soil physical protection, ameliorating the microclimate and reducing the risks of erosion and runoff. These functions stimulate the recovery and reactivation of key ecological processes for regeneration and ecosystem sustainability. On the contrary, burnt wood salvage logging represents an additional perturbation beyond those exerted by wildfires. 274

_____________________________________________________________________Conclusions

This can involve a negative and synergic impact on the ecosystem and a higher risk of irreversible degradation processes.

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