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Using Satellite Remote Sensing to Estimate Rangeland Carrying Capacity for Sustainable Management of the Marismeño Horse in Doñana National Park, Spain.

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Titel: Using Satellite Remote Sensing to Estimate Rangeland Carrying Capacity for Sustainable Management of the Marismeño Horse in Doñana National Park, Spain.
Autoren: Ramírez-Juidias, Emilio, Díaz de la Serna-Moreno, Ángel, Delgado-Pertíñez, Manuel
Quelle: Animals (2076-2615); Dec2025, Vol. 15 Issue 24, p3507, 24p
Schlagwörter: SATELLITE-based remote sensing, PASTURE management, OVERGRAZING, LIVESTOCK breeds, NATIONAL parks & reserves, PLANT growth, SUSTAINABILITY, GRAZING
Geografische Kategorien: SPAIN, SOUTHERN Europe
Abstract: Simple Summary: The Marismeño horse, a free-ranging and endangered livestock breed native to Doñana National Park in southern Spain, depends entirely on natural pastures within a highly dynamic wetland ecosystem. Seasonal drought, flooding, and salinity changes strongly affect the availability and nutritional quality of its forage, yet reliable tools to monitor these conditions have been limited. This study aimed to develop a satellite-based method to estimate vegetation growth, forage quality, and grazing pressure across Doñana's main grazing units over a six-year period (2015–2020). By analyzing more than one thousand satellite images from Landsat 8 and Sentinel-2 and integrating them with field data, we identified clear seasonal patterns, with spring showing the highest forage production and late summer the lowest quality. Ecotonal zones such as La Vera y Sotos acted as critical refuges for grazing when the marshes dried out. The results demonstrate that remote sensing can provide managers with timely and objective information to guide adaptive herd management, safeguard the ecological integrity of the park, and help preserve this emblematic horse breed. This approach can also be applied to other Mediterranean and semi-arid ecosystems facing similar challenges from climate variability and water scarcity. Rangeland degradation poses a serious challenge for the sustainable management of free-ranging livestock in Mediterranean wetlands. In Doñana National Park, Spain, the endangered Marismeño horse depends exclusively on natural forage, making it essential to monitor vegetation productivity and grazing suitability under increasing climate variability. This study presents a satellite-based assessment of rangeland carrying capacity to support the adaptive management of this iconic breed. A six-year time series (2015–2020) of 1242 images from Landsat 8 OLI/TIRS and Sentinel-2 (L1C/L2A) was processed using ILWIS and Python-based workflows to derive vegetation indices (GNDVI, NDMI) and model aboveground biomass, forage energy, and grazing pressure across five grazing units. Results revealed strong seasonal cycles, with biomass and nutritive value peaking in spring and declining sharply in summer. Ecotonal zones such as La Vera y Sotos acted as crucial refuges during drought-induced resource shortages. The harmonized multi-sensor approach demonstrated high reliability for mapping forage dynamics and assessing carrying capacity at fine scales. This remote sensing framework offers an effective, scalable tool for sustainable livestock management in Doñana, directly supporting biodiversity conservation and the long-term resilience of Mediterranean rangeland ecosystems. [ABSTRACT FROM AUTHOR]
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Datenbank: Biomedical Index
Beschreibung
Abstract:Simple Summary: The Marismeño horse, a free-ranging and endangered livestock breed native to Doñana National Park in southern Spain, depends entirely on natural pastures within a highly dynamic wetland ecosystem. Seasonal drought, flooding, and salinity changes strongly affect the availability and nutritional quality of its forage, yet reliable tools to monitor these conditions have been limited. This study aimed to develop a satellite-based method to estimate vegetation growth, forage quality, and grazing pressure across Doñana's main grazing units over a six-year period (2015–2020). By analyzing more than one thousand satellite images from Landsat 8 and Sentinel-2 and integrating them with field data, we identified clear seasonal patterns, with spring showing the highest forage production and late summer the lowest quality. Ecotonal zones such as La Vera y Sotos acted as critical refuges for grazing when the marshes dried out. The results demonstrate that remote sensing can provide managers with timely and objective information to guide adaptive herd management, safeguard the ecological integrity of the park, and help preserve this emblematic horse breed. This approach can also be applied to other Mediterranean and semi-arid ecosystems facing similar challenges from climate variability and water scarcity. Rangeland degradation poses a serious challenge for the sustainable management of free-ranging livestock in Mediterranean wetlands. In Doñana National Park, Spain, the endangered Marismeño horse depends exclusively on natural forage, making it essential to monitor vegetation productivity and grazing suitability under increasing climate variability. This study presents a satellite-based assessment of rangeland carrying capacity to support the adaptive management of this iconic breed. A six-year time series (2015–2020) of 1242 images from Landsat 8 OLI/TIRS and Sentinel-2 (L1C/L2A) was processed using ILWIS and Python-based workflows to derive vegetation indices (GNDVI, NDMI) and model aboveground biomass, forage energy, and grazing pressure across five grazing units. Results revealed strong seasonal cycles, with biomass and nutritive value peaking in spring and declining sharply in summer. Ecotonal zones such as La Vera y Sotos acted as crucial refuges during drought-induced resource shortages. The harmonized multi-sensor approach demonstrated high reliability for mapping forage dynamics and assessing carrying capacity at fine scales. This remote sensing framework offers an effective, scalable tool for sustainable livestock management in Doñana, directly supporting biodiversity conservation and the long-term resilience of Mediterranean rangeland ecosystems. [ABSTRACT FROM AUTHOR]
ISSN:20762615
DOI:10.3390/ani15243507