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Resumen
The disruption of the natural post-disturbance recovery process, either by changes in disturbance regime or by another disturbance, can trigger transitions to alternative degraded states. In a scenario of high disturbance pressure on ecological systems, it is essential to detect recovery indicators to define the period when the system needs more protection as well as the period when the system supports certain use pressure without affecting its [ver mas...]
dc.contributor.authorCavallero, Laura
dc.contributor.authorLopez, Dardo Ruben
dc.contributor.authorRaffaele, Estela
dc.contributor.authorAizen, Marcelo Adrian
dc.date.accessioned2018-11-09T12:46:05Z
dc.date.available2018-11-09T12:46:05Z
dc.date.issued2015-05
dc.identifier.issn1470-160X
dc.identifier.otherhttps://doi.org/10.1016/j.ecolind.2014.11.019
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S1470160X14005548
dc.identifier.urihttp://hdl.handle.net/20.500.12123/3843
dc.description.abstractThe disruption of the natural post-disturbance recovery process, either by changes in disturbance regime or by another disturbance, can trigger transitions to alternative degraded states. In a scenario of high disturbance pressure on ecological systems, it is essential to detect recovery indicators to define the period when the system needs more protection as well as the period when the system supports certain use pressure without affecting its resilience. Recovery indicators can be identified by non-linear changes in structural and functional variables. Fire largely modulates the dynamic and stability of plant communities worldwide, and is this the case in northwestern (NW) Patagonia. The ultimate goal of this study is to propose a structural–functional approach based on a reference system (i.e. chronosequence) as a tool to detect post-disturbance recovery indicators in forests from NW Patagonia. In NW Patagonia (40–42°S), we sampled 25 Austrocedrus chilensis and Nothofagus spp. communities differing in post-fire age (0.3–180 years). In each community we recorded structural (woody species cover and height, solar radiation, air temperature, relative humidity) and functional (annual recruitment of woody and tree species) attributes. We modeled these attributes in function of post-fire age and analized the relationship between a functional attribute and a Structural Recovery Index (SRI). Communities varying in time-since-last-fire were structurally and functionally different. Moreover, response variables showed non-linear changes along the chronosequence, allowing the selection of recovery indicators. We suggest to use vegetation variables instead of environmental variables as structural recovery indicators. Horizontal and Vertical Vegetation Heterogeneity indices provided the information necessary to describe vegetation spatial reorganization after fire. Tree species annual recruitment was a good indicator of the functional recovery of forest communities. The relationship between a functional attribute and SRI allowed us to detect phases with high- and low-risk of degradation during post-fire succession. High-risk phases (<36 years old) had the highest horizontal vegetation heterogeneity and scarce tree seedling density (<7000 seedlings ha−1 year−1). Whereas, low-risk phases (>36 years old) had the highest vertical vegetation heterogeneity and tree species seedling density (>10,000 seedlings ha−1 year−1). Due to the low structural–functional levels, communities at high-risk phases would be more vulnerable to antropic pressure (e.g. livestock raising, logging) than communities at low-risk phases. The proposed approach contributes to the sustainable management of forest communities because it allows to estimate the minimum structural–functional levels from which forest communities could be harvested.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourceEcological Indicators 52 : 85-95 (May 2015)es_AR
dc.subjectBosqueses_AR
dc.subjectForestseng
dc.subjectResiliencia Forestales_AR
dc.subjectForest Resilienceeng
dc.subjectEcosistemaes_AR
dc.subjectEcosystemseng
dc.subjectIndicadores Ecológicoses_AR
dc.subjectEcological Indicatorseng
dc.subjectMedio Ambientees_AR
dc.subjectEnvironmenteng
dc.subjectRehabilitación Forestales_AR
dc.subjectForest Rehabilitationeng
dc.subject.otherRegión Patagónica
dc.titleStructural–functional approach to identify post-disturbance recovery indicators in forests from northwestern Patagonia: a tool to prevent state transitionses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenEEA Barilochees_AR
dc.description.filFil: Cavallero, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentinaes_AR
dc.description.filFil: Lopez, Dardo Ruben. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentinaes_AR
dc.description.filFil: Raffaele, Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentinaes_AR
dc.description.filFil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentinaes_AR
dc.subtypecientifico


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