{"title":"阿根廷查科干旱区牧草干旱遥感研究","authors":"Lisandro Blanco , Walter Agüero , Alicia Sancho , Marcos Texeira","doi":"10.1016/j.rama.2025.07.014","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Drought is widely recognized as one of the most complex natural hazards due to its gradual onset and long-lasting impacts. With climate change, droughts are becoming increasingly intense, frequent, and prolonged, particularly in arid and semiarid rangelands, posing a serious threat to the sustainability of livestock systems. The objective of this study was to develop, calibrate, and validate a methodology for detecting forage droughts and monitoring their spatial and temporal patterns using satellite-derived anomalies in the Normalized Difference Vegetation Index (NDVI), hereafter NDVI anomalie (NDVIA).</div></div><div><h3>Methods</h3><div>Forage droughts are defined as temporary reductions in forage productivity in rangelands, grasslands, and pastures caused by rainfall falling below the long-term average. These reductions are so severe that even with adaptive forage management, the forage biomass accumulated during the growing season is insufficient to sustain livestock during the vegetative rest period (forage drought model). The study focuses on the dry Chaco region of Argentina. NDVIA values were correlated with forage biomass data collected in the field at 20 sites over a 10-yr period. Using a logistic regression model, the NDVIA threshold indicating the presence or absence of forage drought was determined.</div></div><div><h3>Results</h3><div>Results revealed a significant relationship (<em>P</em> < 0.05) between NDVIA and forage drought presence/absence. During the study period (2001–2023), forage droughts in the region typically recurred every 5 ± 2 growing seasons. A cluster analysis identified two subzones with significant differences (<em>P</em> < 0.05) in the temporal dynamics of forage drought occurrence.</div></div><div><h3>Implications</h3><div>The combined application of the forage drought model and this NDVI-based monitoring system could serve as a “guidebook” for implementing forage management strategies at the farm scale (e.g., adaptive forage management) and shaping public policies at the regional scale (e.g., satellite index-based insurance). This methodological approach, first-of-its-kind in region, could be adapted to other arid and semiarid ecosystems globally, enhancing the early warning and management of forage droughts.</div></div>","PeriodicalId":49634,"journal":{"name":"Rangeland Ecology & Management","volume":"103 ","pages":"Pages 93-103"},"PeriodicalIF":2.4000,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Remote Sensing of Forage Droughts in the Dry Chaco (Argentina)\",\"authors\":\"Lisandro Blanco , Walter Agüero , Alicia Sancho , Marcos Texeira\",\"doi\":\"10.1016/j.rama.2025.07.014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Drought is widely recognized as one of the most complex natural hazards due to its gradual onset and long-lasting impacts. With climate change, droughts are becoming increasingly intense, frequent, and prolonged, particularly in arid and semiarid rangelands, posing a serious threat to the sustainability of livestock systems. The objective of this study was to develop, calibrate, and validate a methodology for detecting forage droughts and monitoring their spatial and temporal patterns using satellite-derived anomalies in the Normalized Difference Vegetation Index (NDVI), hereafter NDVI anomalie (NDVIA).</div></div><div><h3>Methods</h3><div>Forage droughts are defined as temporary reductions in forage productivity in rangelands, grasslands, and pastures caused by rainfall falling below the long-term average. These reductions are so severe that even with adaptive forage management, the forage biomass accumulated during the growing season is insufficient to sustain livestock during the vegetative rest period (forage drought model). The study focuses on the dry Chaco region of Argentina. NDVIA values were correlated with forage biomass data collected in the field at 20 sites over a 10-yr period. Using a logistic regression model, the NDVIA threshold indicating the presence or absence of forage drought was determined.</div></div><div><h3>Results</h3><div>Results revealed a significant relationship (<em>P</em> < 0.05) between NDVIA and forage drought presence/absence. During the study period (2001–2023), forage droughts in the region typically recurred every 5 ± 2 growing seasons. A cluster analysis identified two subzones with significant differences (<em>P</em> < 0.05) in the temporal dynamics of forage drought occurrence.</div></div><div><h3>Implications</h3><div>The combined application of the forage drought model and this NDVI-based monitoring system could serve as a “guidebook” for implementing forage management strategies at the farm scale (e.g., adaptive forage management) and shaping public policies at the regional scale (e.g., satellite index-based insurance). This methodological approach, first-of-its-kind in region, could be adapted to other arid and semiarid ecosystems globally, enhancing the early warning and management of forage droughts.</div></div>\",\"PeriodicalId\":49634,\"journal\":{\"name\":\"Rangeland Ecology & Management\",\"volume\":\"103 \",\"pages\":\"Pages 93-103\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Rangeland Ecology & Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1550742425001009\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rangeland Ecology & Management","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1550742425001009","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Remote Sensing of Forage Droughts in the Dry Chaco (Argentina)
Background
Drought is widely recognized as one of the most complex natural hazards due to its gradual onset and long-lasting impacts. With climate change, droughts are becoming increasingly intense, frequent, and prolonged, particularly in arid and semiarid rangelands, posing a serious threat to the sustainability of livestock systems. The objective of this study was to develop, calibrate, and validate a methodology for detecting forage droughts and monitoring their spatial and temporal patterns using satellite-derived anomalies in the Normalized Difference Vegetation Index (NDVI), hereafter NDVI anomalie (NDVIA).
Methods
Forage droughts are defined as temporary reductions in forage productivity in rangelands, grasslands, and pastures caused by rainfall falling below the long-term average. These reductions are so severe that even with adaptive forage management, the forage biomass accumulated during the growing season is insufficient to sustain livestock during the vegetative rest period (forage drought model). The study focuses on the dry Chaco region of Argentina. NDVIA values were correlated with forage biomass data collected in the field at 20 sites over a 10-yr period. Using a logistic regression model, the NDVIA threshold indicating the presence or absence of forage drought was determined.
Results
Results revealed a significant relationship (P < 0.05) between NDVIA and forage drought presence/absence. During the study period (2001–2023), forage droughts in the region typically recurred every 5 ± 2 growing seasons. A cluster analysis identified two subzones with significant differences (P < 0.05) in the temporal dynamics of forage drought occurrence.
Implications
The combined application of the forage drought model and this NDVI-based monitoring system could serve as a “guidebook” for implementing forage management strategies at the farm scale (e.g., adaptive forage management) and shaping public policies at the regional scale (e.g., satellite index-based insurance). This methodological approach, first-of-its-kind in region, could be adapted to other arid and semiarid ecosystems globally, enhancing the early warning and management of forage droughts.
期刊介绍:
Rangeland Ecology & Management publishes all topics-including ecology, management, socioeconomic and policy-pertaining to global rangelands. The journal''s mission is to inform academics, ecosystem managers and policy makers of science-based information to promote sound rangeland stewardship. Author submissions are published in five manuscript categories: original research papers, high-profile forum topics, concept syntheses, as well as research and technical notes.
Rangelands represent approximately 50% of the Earth''s land area and provision multiple ecosystem services for large human populations. This expansive and diverse land area functions as coupled human-ecological systems. Knowledge of both social and biophysical system components and their interactions represent the foundation for informed rangeland stewardship. Rangeland Ecology & Management uniquely integrates information from multiple system components to address current and pending challenges confronting global rangelands.