Huanhuan Wang , Qiaoyun Xie , Sally E. Thompson , Caitlin E. Moore , David L. Miller , Erik J. Veneklaas , Richard P. Silberstein , Xing Li , Jingfeng Xiao , Belinda E. Medlyn , William K. Smith
{"title":"卫星观测揭示了澳大利亚沿降雨梯度的优势植被对短期水资源压力的抵抗力和恢复力","authors":"Huanhuan Wang , Qiaoyun Xie , Sally E. Thompson , Caitlin E. Moore , David L. Miller , Erik J. Veneklaas , Richard P. Silberstein , Xing Li , Jingfeng Xiao , Belinda E. Medlyn , William K. Smith","doi":"10.1016/j.rse.2025.115046","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change is projected to intensify water stress in many ecosystems and poses threats to their stability, which can be quantified through ecosystem resistance and resilience. Relevant studies mostly focused on multi-year or annual droughts, and in spatially homogeneous or species-specific ecosystems. However, resilience and resistance within complex ecosystems, where different plants exhibit different adaptations and recovery behaviours, are less understood. Using productivity data from satellite-derived GOSIF (Global Orbiting Carbon Observatory-2 Solar-Induced Fluorescence) and flux towers, we examined vegetation responses to short-term (<1 year) water stress events from 2000 to 2018 along the North Australia Tropical Transect, which spans a 1600 mm rainfall gradient and transitions from seasonal mesic to non-seasonal arid ecosystems. We define resistance as productivity maintained during stress relative to a multi-year average baseline, and resilience as the extent to which productivity recovered one year after stress relative to the same baseline. Our results show that ecosystem resistance to water stress was lowest in semi-arid regions but higher in both arid and mesic regions, while ecosystem resilience showed the opposite pattern. These spatial patterns occurred regardless of seasonality and were mainly associated with dominant vegetation type. Woody savanna-dominated mesic regions exhibited highest resistance (0.82 ± 0.13, <em>p</em> < 0.001) and lowest resilience (0.26 ± 0.19, <em>p</em> < 0.001), shrublands in arid areas had intermediate values of both resistance (0.81 ± 0.14, <em>p</em> < 0.001) and resilience (0.27 ± 0.22, <em>p</em> < 0.001), while the grasslands in semi-arid regions had low resistance (0.78 ± 0.15, <em>p</em> < 0.001) and high resilience (0.38 ± 0.24, <em>p</em> < 0.001). The highest likelihood (>75.0 %) of full recovery (i.e., exceeding baseline after one year) occurred during the wet season in mesic regions, likely due to energy limitation, while arid regions showed a lower likelihood (57.0 %). This study provides a remote sensing framework for quantifying ecosystem resistance and resilience under water stress.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"332 ","pages":"Article 115046"},"PeriodicalIF":11.4000,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Satellite observations reveal ecosystem resistance and resilience to short-term water stress driven by dominant vegetation along a rainfall gradient in Australia\",\"authors\":\"Huanhuan Wang , Qiaoyun Xie , Sally E. Thompson , Caitlin E. Moore , David L. Miller , Erik J. Veneklaas , Richard P. Silberstein , Xing Li , Jingfeng Xiao , Belinda E. Medlyn , William K. Smith\",\"doi\":\"10.1016/j.rse.2025.115046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Climate change is projected to intensify water stress in many ecosystems and poses threats to their stability, which can be quantified through ecosystem resistance and resilience. Relevant studies mostly focused on multi-year or annual droughts, and in spatially homogeneous or species-specific ecosystems. However, resilience and resistance within complex ecosystems, where different plants exhibit different adaptations and recovery behaviours, are less understood. Using productivity data from satellite-derived GOSIF (Global Orbiting Carbon Observatory-2 Solar-Induced Fluorescence) and flux towers, we examined vegetation responses to short-term (<1 year) water stress events from 2000 to 2018 along the North Australia Tropical Transect, which spans a 1600 mm rainfall gradient and transitions from seasonal mesic to non-seasonal arid ecosystems. We define resistance as productivity maintained during stress relative to a multi-year average baseline, and resilience as the extent to which productivity recovered one year after stress relative to the same baseline. Our results show that ecosystem resistance to water stress was lowest in semi-arid regions but higher in both arid and mesic regions, while ecosystem resilience showed the opposite pattern. These spatial patterns occurred regardless of seasonality and were mainly associated with dominant vegetation type. Woody savanna-dominated mesic regions exhibited highest resistance (0.82 ± 0.13, <em>p</em> < 0.001) and lowest resilience (0.26 ± 0.19, <em>p</em> < 0.001), shrublands in arid areas had intermediate values of both resistance (0.81 ± 0.14, <em>p</em> < 0.001) and resilience (0.27 ± 0.22, <em>p</em> < 0.001), while the grasslands in semi-arid regions had low resistance (0.78 ± 0.15, <em>p</em> < 0.001) and high resilience (0.38 ± 0.24, <em>p</em> < 0.001). The highest likelihood (>75.0 %) of full recovery (i.e., exceeding baseline after one year) occurred during the wet season in mesic regions, likely due to energy limitation, while arid regions showed a lower likelihood (57.0 %). 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Satellite observations reveal ecosystem resistance and resilience to short-term water stress driven by dominant vegetation along a rainfall gradient in Australia
Climate change is projected to intensify water stress in many ecosystems and poses threats to their stability, which can be quantified through ecosystem resistance and resilience. Relevant studies mostly focused on multi-year or annual droughts, and in spatially homogeneous or species-specific ecosystems. However, resilience and resistance within complex ecosystems, where different plants exhibit different adaptations and recovery behaviours, are less understood. Using productivity data from satellite-derived GOSIF (Global Orbiting Carbon Observatory-2 Solar-Induced Fluorescence) and flux towers, we examined vegetation responses to short-term (<1 year) water stress events from 2000 to 2018 along the North Australia Tropical Transect, which spans a 1600 mm rainfall gradient and transitions from seasonal mesic to non-seasonal arid ecosystems. We define resistance as productivity maintained during stress relative to a multi-year average baseline, and resilience as the extent to which productivity recovered one year after stress relative to the same baseline. Our results show that ecosystem resistance to water stress was lowest in semi-arid regions but higher in both arid and mesic regions, while ecosystem resilience showed the opposite pattern. These spatial patterns occurred regardless of seasonality and were mainly associated with dominant vegetation type. Woody savanna-dominated mesic regions exhibited highest resistance (0.82 ± 0.13, p < 0.001) and lowest resilience (0.26 ± 0.19, p < 0.001), shrublands in arid areas had intermediate values of both resistance (0.81 ± 0.14, p < 0.001) and resilience (0.27 ± 0.22, p < 0.001), while the grasslands in semi-arid regions had low resistance (0.78 ± 0.15, p < 0.001) and high resilience (0.38 ± 0.24, p < 0.001). The highest likelihood (>75.0 %) of full recovery (i.e., exceeding baseline after one year) occurred during the wet season in mesic regions, likely due to energy limitation, while arid regions showed a lower likelihood (57.0 %). This study provides a remote sensing framework for quantifying ecosystem resistance and resilience under water stress.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.