Functional syndromes as indicators of ecosystem change in temperate grasslands
The lack of an organizing conceptual framework to address ecosystem changes reduces our capacity to distinguish biophysical from direct human impacts on grassland dynamics. This is particularly important for subhumid temperate grasslands, one of the world’s most threatened biomes. We identified and...
| Main Authors: | , , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
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Elsevier
2018
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| Online Access: | http://hdl.handle.net/20.500.12123/3562 https://www.sciencedirect.com/science/article/pii/S1470160X1830743X?via%3Dihub https://doi.org/10.1016/j.ecolind.2018.09.046 |
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| author | Texeira González, Marcos Alexis Veron, Santiago Ramón Irisarri, Jorge Gonzalo Nicolás Oyarzabal, Mariano Staiano, Luciana Baeza, Santiago Paruelo, José María |
| author_browse | Baeza, Santiago Irisarri, Jorge Gonzalo Nicolás Oyarzabal, Mariano Paruelo, José María Staiano, Luciana Texeira González, Marcos Alexis Veron, Santiago Ramón |
| author_facet | Texeira González, Marcos Alexis Veron, Santiago Ramón Irisarri, Jorge Gonzalo Nicolás Oyarzabal, Mariano Staiano, Luciana Baeza, Santiago Paruelo, José María |
| author_sort | Texeira González, Marcos Alexis |
| collection | INTA Digital |
| description | The lack of an organizing conceptual framework to address ecosystem changes reduces our capacity to distinguish biophysical from direct human impacts on grassland dynamics. This is particularly important for subhumid temperate grasslands, one of the world’s most threatened biomes. We identified and mapped 4 functional syndromes of grassland change at the wettest end of its worldwide distribution, the Campos in Uruguay. Syndromes were defined by differences in precipitation use efficiency (PUE, ANPP/precipitation), and in precipitation marginal response (PMR, slope of the linear regression between ANPP and precipitation) between two periods (1981–1995 and 2001–2011). Temporal trends in aboveground net primary production (ANPP, obtained by splicing two sources of NDVI, LTDR and MOD13Q1) were also characterized. To rule out the effect of precipitation we analyzed temporal trends of the residuals from the relationship between ANPP and annual precipitation (RESTRENDS). Functional syndromes associated with increases in seasonality or in the abundance of annual vegetation (ΔPMR > 0, ΔPUE < 0, ∼14,000 km2) and vegetation cover loss (ΔPUE < 0 and ΔPMR < 0, >5000 km2) were the most abundant. ANPP trends were significantly negative in 3.7% of the area (2475 km2) and only positive in 0.3%. However, RESTRENDS were significant in 11% of the area (>7700 km2), and mostly negative (in ∼7200 km2). Most of these negative trends and residual trends were associated to seasonality increase and vegetation loss syndromes. These patterns were consistent with observed changes in the region. We highlight that this conceptual framework is suitable for describing patterns of change and potential causes. Moreover, it provides policymakers with a novel tool to guide management and conservation policies, pointing to sites where intervention (i.e. conservation, restoration) is needed. |
| format | Artículo |
| id | INTA3562 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA35622018-10-17T13:07:01Z Functional syndromes as indicators of ecosystem change in temperate grasslands Texeira González, Marcos Alexis Veron, Santiago Ramón Irisarri, Jorge Gonzalo Nicolás Oyarzabal, Mariano Staiano, Luciana Baeza, Santiago Paruelo, José María Pastizales Ecosistema Síntomas Espectrorradiómetro de Imágenes de Resolución Moderada Pastures Ecosystems Symptoms Moderate Resolution Imaging Spectroradiometer Aboveground Net Primary Production ANPP Ecosystem Functional Syndromes MODIS LTDR Precipitation Use Efficiency PUE Precipitation Marginal Response PMR Río de la Plata, Argentina The lack of an organizing conceptual framework to address ecosystem changes reduces our capacity to distinguish biophysical from direct human impacts on grassland dynamics. This is particularly important for subhumid temperate grasslands, one of the world’s most threatened biomes. We identified and mapped 4 functional syndromes of grassland change at the wettest end of its worldwide distribution, the Campos in Uruguay. Syndromes were defined by differences in precipitation use efficiency (PUE, ANPP/precipitation), and in precipitation marginal response (PMR, slope of the linear regression between ANPP and precipitation) between two periods (1981–1995 and 2001–2011). Temporal trends in aboveground net primary production (ANPP, obtained by splicing two sources of NDVI, LTDR and MOD13Q1) were also characterized. To rule out the effect of precipitation we analyzed temporal trends of the residuals from the relationship between ANPP and annual precipitation (RESTRENDS). Functional syndromes associated with increases in seasonality or in the abundance of annual vegetation (ΔPMR > 0, ΔPUE < 0, ∼14,000 km2) and vegetation cover loss (ΔPUE < 0 and ΔPMR < 0, >5000 km2) were the most abundant. ANPP trends were significantly negative in 3.7% of the area (2475 km2) and only positive in 0.3%. However, RESTRENDS were significant in 11% of the area (>7700 km2), and mostly negative (in ∼7200 km2). Most of these negative trends and residual trends were associated to seasonality increase and vegetation loss syndromes. These patterns were consistent with observed changes in the region. We highlight that this conceptual framework is suitable for describing patterns of change and potential causes. Moreover, it provides policymakers with a novel tool to guide management and conservation policies, pointing to sites where intervention (i.e. conservation, restoration) is needed. Instituto de Clima y Agua Fil: Texeira González, Marcos Alexis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Veron, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina Fil: Irisarri, Jorge Gonzalo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Oyarzabal, Mariano. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina Fil: Staiano, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina Fil: Baeza, Santiago. Universidad de la Republica. Facultad de Agronomía. Departamento de Sistemas Ambientales; Uruguay Fil: Paruelo, José María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Instituto Nacional de Investigación Agropecuaria. Estación Experimental La Estanzuela; Uruguay 2018-10-05T18:39:03Z 2018-10-05T18:39:03Z 2018-09-24 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/3562 https://www.sciencedirect.com/science/article/pii/S1470160X1830743X?via%3Dihub 1470-160X https://doi.org/10.1016/j.ecolind.2018.09.046 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Ecological indicators 96 (1) : 600-610. (January 2019) |
| spellingShingle | Pastizales Ecosistema Síntomas Espectrorradiómetro de Imágenes de Resolución Moderada Pastures Ecosystems Symptoms Moderate Resolution Imaging Spectroradiometer Aboveground Net Primary Production ANPP Ecosystem Functional Syndromes MODIS LTDR Precipitation Use Efficiency PUE Precipitation Marginal Response PMR Río de la Plata, Argentina Texeira González, Marcos Alexis Veron, Santiago Ramón Irisarri, Jorge Gonzalo Nicolás Oyarzabal, Mariano Staiano, Luciana Baeza, Santiago Paruelo, José María Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title | Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title_full | Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title_fullStr | Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title_full_unstemmed | Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title_short | Functional syndromes as indicators of ecosystem change in temperate grasslands |
| title_sort | functional syndromes as indicators of ecosystem change in temperate grasslands |
| topic | Pastizales Ecosistema Síntomas Espectrorradiómetro de Imágenes de Resolución Moderada Pastures Ecosystems Symptoms Moderate Resolution Imaging Spectroradiometer Aboveground Net Primary Production ANPP Ecosystem Functional Syndromes MODIS LTDR Precipitation Use Efficiency PUE Precipitation Marginal Response PMR Río de la Plata, Argentina |
| url | http://hdl.handle.net/20.500.12123/3562 https://www.sciencedirect.com/science/article/pii/S1470160X1830743X?via%3Dihub https://doi.org/10.1016/j.ecolind.2018.09.046 |
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