Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity...
| Autores principales: | , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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MDPI
2024
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/16897 https://www.mdpi.com/2071-1050/16/5/2025 https://doi.org/10.3390/su16052025 |
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| author | Peri, Pablo Luis Gaitan, Juan José Diaz, Boris Gaston Almonacid, Leandro Morales, Cristian Gabriel Ferrer, Francisco Lasagno, Romina Gisele Rodríguez‑Souilla, Julián Martínez Pastur, Guillermo José |
| author_browse | Almonacid, Leandro Diaz, Boris Gaston Ferrer, Francisco Gaitan, Juan José Lasagno, Romina Gisele Martínez Pastur, Guillermo José Morales, Cristian Gabriel Peri, Pablo Luis Rodríguez‑Souilla, Julián |
| author_facet | Peri, Pablo Luis Gaitan, Juan José Diaz, Boris Gaston Almonacid, Leandro Morales, Cristian Gabriel Ferrer, Francisco Lasagno, Romina Gisele Rodríguez‑Souilla, Julián Martínez Pastur, Guillermo José |
| author_sort | Peri, Pablo Luis |
| collection | INTA Digital |
| description | Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of
grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde
shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation,
vegetation management and restoration, and regional strategic decision-making. |
| format | Artículo |
| id | INTA16897 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | INTA168972024-03-04T10:08:58Z Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity Peri, Pablo Luis Gaitan, Juan José Diaz, Boris Gaston Almonacid, Leandro Morales, Cristian Gabriel Ferrer, Francisco Lasagno, Romina Gisele Rodríguez‑Souilla, Julián Martínez Pastur, Guillermo José Rangelands Livestock Carbon Ecosystem Services Vegetation Resource Conservation Soil Organic Carbon Forests Grasslands Scrublands Tierras de pastos Ganado Biodiversidad Carbono Servicios de los Ecosistemas Vegetación Conservación de los Recursos Carbono Orgánico del Suelo Nothofagus Pumilio Bosque Pastizales Tierras de Matorral Santa Cruz (Argentina) Biodiversity Carbon Balance Provisioning Ecosystem Services Ecosystem Functions Spatial Patterns Land Use Cover Steppe Grasslands Mata Negra Matorral Thicket Bare Soil Nothofagus Pumilio Forest Nothofagus Antarctica Forest PEBANPA Network Balance de Carbono Servicios Ecosistémicos de Provisión Funciones del Ecosistema Patrones Espaciales Cobertura del Uso de la Tierra Matorral Mata Negra Suelo Desnudo Bosques de Nothofagus Pumilio Bosque de Nothofagus Antarctica Red PEBANPA Región Patagónica Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making. EEA Santa Cruz Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral (UNPA); Argentina. Fil: Gaitan, Juan José. Universidad Nacional de Luján; Argentina. Fil: Gaitan, Juan José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Diaz, Boris Gaston. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Almonacid, Leandro. Municipalidad de Río Gallegos. CONVENIO INTA. Santa Cruz; Argentina. Fil: Almonacid, Leandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Morales, Cristian Gabriel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Ferrer, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Ferrer, Francisco. Universidad Nacional de la Patagonia Austral (UNPA). Departamento de Recursos Naturales; Argentina. Fil: Ferrer, Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Lasagno, Romina Gisele. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina. Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina. 2024-03-01T17:15:51Z 2024-03-01T17:15:51Z 2024-02-29 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/16897 https://www.mdpi.com/2071-1050/16/5/2025 Peri P.L.; Gaitán J.; Díaz B.; Almonacid L.; Morales C.; Ferrer F.; Lasagno R.; Rodríguez-Souilla J.; Martínez Pastur G. (2024) Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity. Sustainability 16: e2025. https://doi.org/10.3390/su16052025 2071-1050 https://doi.org/10.3390/su16052025 eng info:eu-repograntAgreement/INTA/2019-PD-E2-I038-002, Evaluación, monitoreo y manejo de la biodiversidad en sistemas agropecuarios y forestales info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Patagonia .......... (general region) (World, South America, Argentina) 7016766 MDPI Sustainability 16 : e2025 (2024) |
| spellingShingle | Rangelands Livestock Carbon Ecosystem Services Vegetation Resource Conservation Soil Organic Carbon Forests Grasslands Scrublands Tierras de pastos Ganado Biodiversidad Carbono Servicios de los Ecosistemas Vegetación Conservación de los Recursos Carbono Orgánico del Suelo Nothofagus Pumilio Bosque Pastizales Tierras de Matorral Santa Cruz (Argentina) Biodiversity Carbon Balance Provisioning Ecosystem Services Ecosystem Functions Spatial Patterns Land Use Cover Steppe Grasslands Mata Negra Matorral Thicket Bare Soil Nothofagus Pumilio Forest Nothofagus Antarctica Forest PEBANPA Network Balance de Carbono Servicios Ecosistémicos de Provisión Funciones del Ecosistema Patrones Espaciales Cobertura del Uso de la Tierra Matorral Mata Negra Suelo Desnudo Bosques de Nothofagus Pumilio Bosque de Nothofagus Antarctica Red PEBANPA Región Patagónica Peri, Pablo Luis Gaitan, Juan José Diaz, Boris Gaston Almonacid, Leandro Morales, Cristian Gabriel Ferrer, Francisco Lasagno, Romina Gisele Rodríguez‑Souilla, Julián Martínez Pastur, Guillermo José Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title | Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title_full | Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title_fullStr | Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title_full_unstemmed | Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title_short | Vegetation type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity |
| title_sort | vegetation type mapping in southern patagonia and its relationship with ecosystem services soil carbon stock and biodiversity |
| topic | Rangelands Livestock Carbon Ecosystem Services Vegetation Resource Conservation Soil Organic Carbon Forests Grasslands Scrublands Tierras de pastos Ganado Biodiversidad Carbono Servicios de los Ecosistemas Vegetación Conservación de los Recursos Carbono Orgánico del Suelo Nothofagus Pumilio Bosque Pastizales Tierras de Matorral Santa Cruz (Argentina) Biodiversity Carbon Balance Provisioning Ecosystem Services Ecosystem Functions Spatial Patterns Land Use Cover Steppe Grasslands Mata Negra Matorral Thicket Bare Soil Nothofagus Pumilio Forest Nothofagus Antarctica Forest PEBANPA Network Balance de Carbono Servicios Ecosistémicos de Provisión Funciones del Ecosistema Patrones Espaciales Cobertura del Uso de la Tierra Matorral Mata Negra Suelo Desnudo Bosques de Nothofagus Pumilio Bosque de Nothofagus Antarctica Red PEBANPA Región Patagónica |
| url | http://hdl.handle.net/20.500.12123/16897 https://www.mdpi.com/2071-1050/16/5/2025 https://doi.org/10.3390/su16052025 |
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