Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities
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 cond...
| Autores principales: | , , , |
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| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
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Elsevier
2022
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/11779 https://www.sciencedirect.com/science/article/abs/pii/S235293852200043X https://doi.org/10.1016/j.rsase.2022.100735 |
| _version_ | 1855036636005400576 |
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| author | Diaz Villa, Maria Virginia Eva Bruzzone, Octavio Augusto Goldstein, Guillermo Hernan Cristiano, Maria Piedad |
| author_browse | Bruzzone, Octavio Augusto Cristiano, Maria Piedad Diaz Villa, Maria Virginia Eva Goldstein, Guillermo Hernan |
| author_facet | Diaz Villa, Maria Virginia Eva Bruzzone, Octavio Augusto Goldstein, Guillermo Hernan Cristiano, Maria Piedad |
| author_sort | Diaz Villa, Maria Virginia Eva |
| collection | INTA Digital |
| description | 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 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. |
| format | info:ar-repo/semantics/artículo |
| id | INTA11779 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA117792022-05-02T18:09:13Z Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities Diaz Villa, Maria Virginia Eva Bruzzone, Octavio Augusto Goldstein, Guillermo Hernan Cristiano, Maria Piedad Bosques Bosque Húmedo Indice de Vegetación Clima Forests Rainforests Vegetation Index Climate Moderate Resolution Imaging Spectroradiometer Espectrorradiómetro de Imágenes de Resolución Moderada MODIS 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 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. Estación Experimental Agropecuaria Bariloche Fil: Diaz Villa, Maria Virginia Eva. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Diaz Villa, Maria Virginia Eva. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genetica y Evolucion; Argentina Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina Fil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: Goldstein, Guillermo Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Goldstein, Guillermo Hernan. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina Fil: Goldstein, Guillermo Hernan. Universidad de Miami. Departamento de Biología; Estados Unidos Fil: Cristiano, Maria Piedad. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cristiano, Maria Piedad. Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina 2022-05-02T18:02:28Z 2022-05-02T18:02:28Z 2022 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/11779 https://www.sciencedirect.com/science/article/abs/pii/S235293852200043X 2352-9385 https://doi.org/10.1016/j.rsase.2022.100735 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Remote Sensing Applications: Society and Environment 26 : Art. 100735 (April 2022) |
| spellingShingle | Bosques Bosque Húmedo Indice de Vegetación Clima Forests Rainforests Vegetation Index Climate Moderate Resolution Imaging Spectroradiometer Espectrorradiómetro de Imágenes de Resolución Moderada MODIS Diaz Villa, Maria Virginia Eva Bruzzone, Octavio Augusto Goldstein, Guillermo Hernan Cristiano, Maria Piedad Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title | Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title_full | Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title_fullStr | Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title_full_unstemmed | Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title_short | Climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| title_sort | climatic determinants of photosynthetic activity in humid subtropical forests under different forestry activities |
| topic | Bosques Bosque Húmedo Indice de Vegetación Clima Forests Rainforests Vegetation Index Climate Moderate Resolution Imaging Spectroradiometer Espectrorradiómetro de Imágenes de Resolución Moderada MODIS |
| url | http://hdl.handle.net/20.500.12123/11779 https://www.sciencedirect.com/science/article/abs/pii/S235293852200043X https://doi.org/10.1016/j.rsase.2022.100735 |
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