{"doi":"10.1155/2014/965936","title":"Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation","abstract":"<jats:p>There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO<jats:sub>2</jats:sub>and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment.</jats:p>","journal":"Advances in Meteorology","year":2014,"id":601854,"datarank":0.6681520944380261,"base_score":4.454347296253507,"endowment":4.454347296253507,"self_citation_contribution":0.6681520944380261,"citation_network_contribution":0.0,"self_endowment_contribution":0.6681520944380261,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":85,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":148257,"name":"Hanqin Tian","orcid":null,"position":1,"is_corresponding":false},{"id":1543313,"name":"Shree R. 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Dangal","orcid":null,"position":2,"is_corresponding":false},{"id":783890,"name":"Zhiyun Ouyang","orcid":"0000-0003-0927-0499","position":3,"is_corresponding":false},{"id":113399,"name":"Bo Tao","orcid":null,"position":4,"is_corresponding":false},{"id":51054,"name":"Wei Ren","orcid":"0000-0002-3300-0993","position":5,"is_corresponding":false},{"id":1543318,"name":"Chaoqun Lu","orcid":null,"position":6,"is_corresponding":false},{"id":1543321,"name":"Steven Running","orcid":null,"position":7,"is_corresponding":false},{"id":1543310,"name":"Shufen Pan","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Modeling and Monitoring Terrestrial Primary Production in a Changing Global Environment: Toward a Multiscale Synthesis of Observation and Simulation","abstract":"<jats:p>There is a critical need to monitor and predict terrestrial primary production, the key indicator of ecosystem functioning, in a changing global environment. Here we provide a brief review of three major approaches to monitoring and predicting terrestrial primary production: (1) ground-based field measurements, (2) satellite-based observations, and (3) process-based ecosystem modelling. Much uncertainty exists in the multi-approach estimations of terrestrial gross primary production (GPP) and net primary production (NPP). To improve the capacity of model simulation and prediction, it is essential to evaluate ecosystem models against ground and satellite-based measurements and observations. As a case, we have shown the performance of the dynamic land ecosystem model (DLEM) at various scales from site to region to global. We also discuss how terrestrial primary production might respond to climate change and increasing atmospheric CO<jats:sub>2</jats:sub>and uncertainties associated with model and data. Further progress in monitoring and predicting terrestrial primary production requires a multiscale synthesis of observations and model simulations. In the Anthropocene era in which human activity has indeed changed the Earth’s biosphere, therefore, it is essential to incorporate the socioeconomic component into terrestrial ecosystem models for accurately estimating and predicting terrestrial primary production in a changing global environment.</jats:p>","is_dataset_classified":null,"base_score":4.454347296253507,"endowment":4.454347296253507,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W2063374981","authors":[],"funders":[{"funder_name":"National Science Foundation","grant_id":"AGS-1243220","title":null},{"funder_name":"National Science Foundation","grant_id":"1210360","title":"CNH: Pluvials, Droughts, Energetics, and the Mongol Empire"},{"funder_name":"National Science Foundation","grant_id":"CNS-1059376","title":null},{"funder_name":"National Science Foundation","grant_id":"NNX08AL73G_S01","title":null},{"funder_name":"National Science Foundation","grant_id":"NNX10AU06G","title":null},{"funder_name":"National Science Foundation","grant_id":"NNX11AD47G","title":null}],"total_grants":6,"fwci":7.8371,"citation_percentile":0.97833139,"influential_citations":0,"citation_trend":[{"year":2014,"count":2},{"year":2015,"count":12},{"year":2016,"count":9},{"year":2017,"count":13},{"year":2018,"count":3},{"year":2019,"count":10},{"year":2020,"count":6},{"year":2021,"count":6},{"year":2022,"count":7},{"year":2023,"count":3},{"year":2024,"count":6},{"year":2025,"count":6},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://downloads.hindawi.com/journals/amete/2014/965936.pdf","host_type":"journal"},{"url":"https://downloads.hindawi.com/journals/amete/2014/965936.pdf","host_type":"publisher"},{"url":"http://downloads.hindawi.com/journals/amete/2014/965936.pdf","host_type":"publisher"},{"url":"http://downloads.hindawi.com/journals/amete/2014/965936.xml","host_type":"publisher"},{"url":"https://doi.org/10.1155/2014/965936","host_type":"journal"},{"url":"https://scholarworks.umt.edu/decs_pubs/45","host_type":"journal"},{"url":"https://doaj.org/article/27d81c5344524a62b0cde55f748ca4aa","host_type":"repository"},{"url":"http://ir.rcees.ac.cn/handle/311016/9188","host_type":"repository"},{"url":"https://dx.doi.org/10.1155/2014/965936","host_type":""}],"fields_of_study":["Atmospheric and Environmental Gas Dynamics","Plant Water Relations and Carbon Dynamics","Land Use and Ecosystem Services","0401 agriculture, forestry, and fisheries","04 agricultural and veterinary sciences","01 natural sciences","0105 earth and related environmental sciences"],"mesh_terms":[],"keywords":["Primary production","Biosphere","Terrestrial ecosystem","Ecosystem","Environmental science","Production (economics)","Environmental resource management","Global change","Satellite","Earth observation","Primary (astronomy)","Earth system science","Global environmental analysis","Climate change","Remote sensing","Geography","Ecology","Engineering","Meteorology. 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