{"title":"Mitigating the negative effects of droughts on alpine grassland productivity in the northern Xizang Plateau via degradation-combating actions","authors":"Yuting Yang , Jianshuang Wu , Ben Niu , Meng Li","doi":"10.1016/j.jag.2024.104171","DOIUrl":null,"url":null,"abstract":"<div><p>The Qinghai-Xizang Plateau, hosting the world’s largest alpine pastures, plays a pivotal environmental role in Asia. These ecosystems face alterations driven by both climate change and anthropogenic activities, resulting in the widespread consideration of grassland degradation. From 2000 to 2020, the northern Xizang Plateau experienced a pronounced escalation in drought conditions, particularly following a management policy aimed at combating grassland degradation, via restricting livestock numbers and implementing fencing enclosures, initiated in 2009. Specially, following the enforcement of this policy (2010–2020), there was a substantial 13.5 % reduction in soil moisture levels compared to the pre-implementation period (2000–2009), accompanied by a 42.8 % increase in drought severity (measured by the Palmer Drought Severity Index, PDSI) and an 11.6 % rise in drought duration. Under these challenging drought conditions, we identified negative trends of potential grassland Net Primary Productivity (NPP) which in absence of anthropogenic influence, as simulated by terrestrial ecosystem model (TEM). Contrary to this simulation, satellite time series observations revealed a widespread increase in actual grassland productivity. Remarkably, despite the challenging drought conditions between 2010 and 2020, we observed a substantial increase of 4.8 % in actual NPP (measured by light use efficiency model), 2.7 % in Normalized Difference Vegetation Index (NDVI), 10 % in solar-induced chlorophyll fluorescence (SIF), and 7.95 % in Gross Primary Productivity (GPP), respectively. Much of this enhancement in grassland productivity occurred in areas where livestock populations had markedly declined. Notably, the percentage of NPP increase mainly caused by degradation-combating actions doubled from 24.8 % during 2000–2009 to 49.8 % during 2010–2020 across the northern Xizang Plateau. In conclusion, our findings highlight the potential of large-scale degradation-combating actions to mitigate the negative impacts of climate change and contribute to a greener Earth.</p></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"134 ","pages":"Article 104171"},"PeriodicalIF":7.6000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1569843224005272/pdfft?md5=c5dbc610180052546ab0d66052eb2c08&pid=1-s2.0-S1569843224005272-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843224005272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
The Qinghai-Xizang Plateau, hosting the world’s largest alpine pastures, plays a pivotal environmental role in Asia. These ecosystems face alterations driven by both climate change and anthropogenic activities, resulting in the widespread consideration of grassland degradation. From 2000 to 2020, the northern Xizang Plateau experienced a pronounced escalation in drought conditions, particularly following a management policy aimed at combating grassland degradation, via restricting livestock numbers and implementing fencing enclosures, initiated in 2009. Specially, following the enforcement of this policy (2010–2020), there was a substantial 13.5 % reduction in soil moisture levels compared to the pre-implementation period (2000–2009), accompanied by a 42.8 % increase in drought severity (measured by the Palmer Drought Severity Index, PDSI) and an 11.6 % rise in drought duration. Under these challenging drought conditions, we identified negative trends of potential grassland Net Primary Productivity (NPP) which in absence of anthropogenic influence, as simulated by terrestrial ecosystem model (TEM). Contrary to this simulation, satellite time series observations revealed a widespread increase in actual grassland productivity. Remarkably, despite the challenging drought conditions between 2010 and 2020, we observed a substantial increase of 4.8 % in actual NPP (measured by light use efficiency model), 2.7 % in Normalized Difference Vegetation Index (NDVI), 10 % in solar-induced chlorophyll fluorescence (SIF), and 7.95 % in Gross Primary Productivity (GPP), respectively. Much of this enhancement in grassland productivity occurred in areas where livestock populations had markedly declined. Notably, the percentage of NPP increase mainly caused by degradation-combating actions doubled from 24.8 % during 2000–2009 to 49.8 % during 2010–2020 across the northern Xizang Plateau. In conclusion, our findings highlight the potential of large-scale degradation-combating actions to mitigate the negative impacts of climate change and contribute to a greener Earth.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.