{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T15:53:51Z","timestamp":1772553231056,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T00:00:00Z","timestamp":1656892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Collaborative Innovation Project of High-Quality Development of Agriculture in Fujian Province","award":["XTCXGC2021015"],"award-info":[{"award-number":["XTCXGC2021015"]}]},{"name":"Collaborative Innovation Project of High-Quality Development of Agriculture in Fujian Province","award":["XTCXGC2021021"],"award-info":[{"award-number":["XTCXGC2021021"]}]},{"name":"Collaborative Innovation Project of High-Quality Development of Agriculture in Fujian Province","award":["2021J01502"],"award-info":[{"award-number":["2021J01502"]}]},{"name":"Collaborative Innovation Project of High-Quality Development of Agriculture in Fujian Province","award":["CXTD2021013-1"],"award-info":[{"award-number":["CXTD2021013-1"]}]},{"name":"Natural Science Foundation of Fujian Province","award":["XTCXGC2021015"],"award-info":[{"award-number":["XTCXGC2021015"]}]},{"name":"Natural Science Foundation of Fujian Province","award":["XTCXGC2021021"],"award-info":[{"award-number":["XTCXGC2021021"]}]},{"name":"Natural Science Foundation of Fujian Province","award":["2021J01502"],"award-info":[{"award-number":["2021J01502"]}]},{"name":"Natural Science Foundation of Fujian Province","award":["CXTD2021013-1"],"award-info":[{"award-number":["CXTD2021013-1"]}]},{"name":"Fujian Intelligent Agricultural Science and Technology Innovation Team","award":["XTCXGC2021015"],"award-info":[{"award-number":["XTCXGC2021015"]}]},{"name":"Fujian Intelligent Agricultural Science and Technology Innovation Team","award":["XTCXGC2021021"],"award-info":[{"award-number":["XTCXGC2021021"]}]},{"name":"Fujian Intelligent Agricultural Science and Technology Innovation Team","award":["2021J01502"],"award-info":[{"award-number":["2021J01502"]}]},{"name":"Fujian Intelligent Agricultural Science and Technology Innovation Team","award":["CXTD2021013-1"],"award-info":[{"award-number":["CXTD2021013-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global climate change has significantly affected terrestrial carbon sinks. Net ecosystem production (NEP) plays a critical role in the global carbon cycle. However, interannual variability (IAV) of the NEP and its regional contributions and climate attributions are not well-understood on a global scale. This study used a diagnostic model driven by remote sensing leaf area index (LAI) to investigate the NEP IAV and analyze regional and climate contributions on a global scale from 1982 to 2016. We found large NEP IAV during the study period, with the NEP detrended anomaly ranging from \u22122.3 Pg C in 1998 to 1.6 Pg C in 2013 at a global scale. Furthermore, 63.7% and 34.1% of the areas showed positive and negative contributions to NEP IAVs globally, respectively. Evergreen broadleaf forest (EBF) contributed the most (31.1%) to NEP IAV, followed by cropland (21.7%) and grassland (20.8%). Temperature played the most critical roles in the global NEP IAV, with a contribution of 45.5%. However, the partial correlation between NEP and temperature was negative, and the correlation with precipitation was positive in most areas of the globe, indicating that global warming is not conducive to the global carbon sink, but abundant rainfall is important for the global carbon cycle. This study suggests that, to increase the global carbon sink, we should pay more attention to tropical forests (EBFs) and highlight the importance of water availability.<\/jats:p>","DOI":"10.3390\/rs14133208","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T20:59:18Z","timestamp":1656968358000},"page":"3208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Regional Contributions and Climate Attributions to Interannual Variation of Global Net Ecosystems Production by an ECOSYSTEM Processed Model Driven by Remote Sensing Data over the Past 35 Years"],"prefix":"10.3390","volume":"14","author":[{"given":"Miaomiao","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China"},{"name":"Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China"}]},{"given":"Shaoqiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1042-5649","authenticated-orcid":false,"given":"Bin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"405","DOI":"10.5194\/essd-10-405-2018","article-title":"Global Carbon Budget 2017","volume":"10","author":"Andrew","year":"2018","journal-title":"Earth Syst. 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