{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T02:50:47Z","timestamp":1774579847801,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42090012"],"award-info":[{"award-number":["42090012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2016YFB0501404"],"award-info":[{"award-number":["2016YFB0501404"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2016YFA0600103"],"award-info":[{"award-number":["2016YFA0600103"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2008085QD167"],"award-info":[{"award-number":["2008085QD167"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["42090012"],"award-info":[{"award-number":["42090012"]}]},{"name":"National Key Research and Development Program of China","award":["2016YFB0501404"],"award-info":[{"award-number":["2016YFB0501404"]}]},{"name":"National Key Research and Development Program of China","award":["2016YFA0600103"],"award-info":[{"award-number":["2016YFA0600103"]}]},{"name":"National Key Research and Development Program of China","award":["2008085QD167"],"award-info":[{"award-number":["2008085QD167"]}]},{"name":"Natural Science Foundation of Anhui province of China","award":["42090012"],"award-info":[{"award-number":["42090012"]}]},{"name":"Natural Science Foundation of Anhui province of China","award":["2016YFB0501404"],"award-info":[{"award-number":["2016YFB0501404"]}]},{"name":"Natural Science Foundation of Anhui province of China","award":["2016YFA0600103"],"award-info":[{"award-number":["2016YFA0600103"]}]},{"name":"Natural Science Foundation of Anhui province of China","award":["2008085QD167"],"award-info":[{"award-number":["2008085QD167"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The quantitative assessment of vegetation resilience and resistance is worthwhile to deeply understand the responses of vegetation growth to climate anomalies. However, few studies comprehensively evaluate the spatiotemporal resilience and resistance of global vegetation responses to climate change (i.e., temperature, precipitation, and radiation). Furthermore, although ecosystem models are widely used to simulate global vegetation dynamics, it is still not clear whether ecosystem models can capture observation-based vegetation resilience and resistance. In this study, based on remotely sensed and model-simulated leaf area index (LAI) time series and climate datasets, we quantified spatial patterns and temporal changes in vegetation resilience and resistance from 1982\u20132015. The results reveal clear spatial patterns of observation-based vegetation resilience and resistance for the last three decades, which were closely related to the local environment. In general, most of the ecosystem models capture spatial patterns of vegetation resistance to climate to different extents at the grid scale (R = 0.43 \u00b1 0.10 for temperature, R = 0.28 \u00b1 0.12 for precipitation, and R = 0.22 \u00b1 0.08 for radiation); however, they are unable to capture patterns of vegetation resilience (R = 0.05 \u00b1 0.17). Furthermore, vegetation resilience and resistance to climate change have regionally changed over the last three decades. In particular, the results suggest that vegetation resilience has increased in tropical forests and that vegetation resistance to temperature has increased in northern Eurasia. In contrast, ecosystem models cannot capture changes in vegetation resilience and resistance over the past thirty years. Overall, this study establishes a benchmark of vegetation resilience and resistance to climate change at the global scale, which is useful for further understanding ecological mechanisms of vegetation dynamics and improving ecosystem models, especially for dynamic resilience and resistance.<\/jats:p>","DOI":"10.3390\/rs14174332","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"4332","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Evaluation of Spatiotemporal Resilience and Resistance of Global Vegetation Responses to Climate Change"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6196-9817","authenticated-orcid":false,"given":"Na","family":"Sun","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6701-3864","authenticated-orcid":false,"given":"Naijing","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0155-6735","authenticated-orcid":false,"given":"Xiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1493-4723","authenticated-orcid":false,"given":"Jiacheng","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Haoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, Peking University, Beijing 100871, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4638-3743","authenticated-orcid":false,"given":"Donghai","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1038\/nclimate1633","article-title":"Increasing drought under global warming in observations and models","volume":"3","author":"Dai","year":"2013","journal-title":"Nat. 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