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resumen

Resumen
Forests are key ecosystems providing a variety of contributions to societies that are based on the ecological processes occurring in them. Understanding the relationship between ecological processes and the climate system is essential to predict how they will respond to possible future climatic conditions and trajectories. In this study, the relationship between climate variables and vegetation dynamics was studied in different plots of preserved native [ver mas...]
dc.contributor.authorDiaz Villa, Maria Virginia Eva
dc.contributor.authorBruzzone, Octavio Augusto
dc.contributor.authorGoldstein, Guillermo Hernan
dc.contributor.authorCristiano, Maria Piedad
dc.date.accessioned2022-05-02T18:02:28Z
dc.date.available2022-05-02T18:02:28Z
dc.date.issued2022
dc.identifier.issn2352-9385
dc.identifier.otherhttps://doi.org/10.1016/j.rsase.2022.100735
dc.identifier.urihttp://hdl.handle.net/20.500.12123/11779
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S235293852200043X
dc.description.abstractForests are key ecosystems providing a variety of contributions to societies that are based on the ecological processes occurring in them. Understanding the relationship between ecological processes and the climate system is essential to predict how they will respond to possible future climatic conditions and trajectories. In this study, the relationship between climate variables and vegetation dynamics was studied in different plots of preserved native forest, selectively logged forests, and pine plantations in an area of humid subtropical forest in Misiones, Argentina. Time series analysis via gaussian processes and multiple regressions with the moving average of explanatory variables combined with Bayesian model selection using the lowest Bayesian Information Index as selection criteria were used to determine the relationship between the Enhanced Vegetation Index (EVI) and meteorological variables including temperature, rainfall, global radiation, and potential evapotranspiration. Our results showed that EVI’s variability is best explained by a combination of the moving average of temperature, global radiation, and the logarithm of potential evapotranspiration. The estimated EVI value is the minimum predicted value of each linear function of these variables, indicating that these ecosystems are conditioned by the most limiting meteorological variable for vegetation growth at each time among potential evapotranspiration, global radiation, and temperature, but not by a linear combination of these. The different ecosystems, in turn, responded differently to climatic variables. Both logged forests and pine plantations exhibited near-zero slopes with both global radiation and temperature, indicating they are close to temperature and radiation saturation points. Moreover, they presented a higher sensitivity to these variables than preserved forests that were more sensitive to atmospheric water demand. The proposed methodology allowed us to separate the external climatic influence in the forest photosynthetic activity from the internal vegetation processes. Moreover, the final model was capable to capture the multi-scale temporal patterns of forest vegetation.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourceRemote Sensing Applications: Society and Environment 26 : Art. 100735 (April 2022)es_AR
dc.subjectBosqueses_AR
dc.subjectForestseng
dc.subjectBosque Húmedoes_AR
dc.subjectRainforestseng
dc.subjectIndice de Vegetaciónes_AR
dc.subjectVegetation Indexeng
dc.subjectClimaes_AR
dc.subjectClimateeng
dc.subjectEspectrorradiómetro de Imágenes de Resolución Moderada
dc.subjectModerate Resolution Imaging Spectroradiometereng
dc.subject.otherMODIS
dc.titleClimatic determinants of photosynthetic activity in humid subtropical forests under different forestry activitieses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenEstación Experimental Agropecuaria Barilochees_AR
dc.description.filFil: Diaz Villa, Maria Virginia Eva. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Diaz Villa, Maria Virginia Eva. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genetica y Evolucion; Argentinaes_AR
dc.description.filFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentinaes_AR
dc.description.filFil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.description.filFil: Goldstein, Guillermo Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Goldstein, Guillermo Hernan. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentinaes_AR
dc.description.filFil: Goldstein, Guillermo Hernan. Universidad de Miami. Departamento de Biología; Estados Unidoses_AR
dc.description.filFil: Cristiano, Maria Piedad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Cristiano, Maria Piedad. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentinaes_AR
dc.subtypecientifico


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