Coupling PLUS-InVEST Models for Spatiotemporal Analysis and Prediction of Ecosystem Carbon Storage: A Case Study in the Yangtze River Delta Urban Agglomeration, China

Coupling PLUS-InVEST Models for Spatiotemporal Analysis and Prediction of Ecosystem Carbon Storage: A Case Study in the Yangtze River Delta Urban Agglomeration, China | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 18 August 2025 V1 Latest version Share on Coupling PLUS-InVEST Models for Spatiotemporal Analysis and Prediction of Ecosystem Carbon Storage: A Case Study in the Yangtze River Delta Urban Agglomeration, China Authors : Ziru Huang 0009-0009-7471-750X , Liang Liang [email protected] , Meng Li , Yanyan Shi , Shuguo Wang , and Jianrong Kang Authors Info & Affiliations https://doi.org/10.22541/au.175550069.95344755/v1 200 views 87 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The assessment of carbon storage is pivotal for evaluating ecosystem carbon balance and promoting sustainable development. This research employed the PLUS and InVEST models, combined with remote sensing-derived land use data, to analyze carbon storage trends in the Yangtze River Delta (YRD) urban agglomeration from 2000 to 2020 and to predict future land-use patterns and carbon storage across various development scenarios. The findings indicate that: (1) Carbon storage in the YRD shows spatial variability, with high-density areas mainly located in the forested southwestern mountainous regions (e.g., Hangzhou, Jinhua, Taizhou), whereas low-density areas are primarily in the northeastern plains (e.g., Shanghai, Suzhou, Yancheng, Nantong), characterized by high population density and rapid urban expansion. (2) Over the past two decades, the region’s overall carbon storage decreased by 5.51%, with a 1.94% decline from 2000 to 2010 and an accelerated decline of 3.64% from 2010 to 2020. During this period, farmland consistently decreased while urban areas expanded rapidly. (3) Future projections suggest that under an ecological protection scenario, carbon storage is expected to increase. Conversely, under natural and urban development scenarios, carbon storage is projected to continue declining. These results provide valuable insights for development planning and ecological sustainability, supporting global carbon neutrality goals. Supplementary Material File (manuscritp.docx) Download 135.17 KB Information & Authors Information Version history V1 Version 1 18 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords carbon storage invest model land use plus model the yrd urban agglomeration Authors Affiliations Ziru Huang 0009-0009-7471-750X Jiangsu Normal University View all articles by this author Liang Liang [email protected] Jiangsu Normal University View all articles by this author Meng Li Jiangsu Normal University View all articles by this author Yanyan Shi Jiangsu Normal University View all articles by this author Shuguo Wang Jiangsu Normal University View all articles by this author Jianrong Kang Jiangsu Normal University View all articles by this author Metrics & Citations Metrics Article Usage 200 views 87 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ziru Huang, Liang Liang, Meng Li, et al. Coupling PLUS-InVEST Models for Spatiotemporal Analysis and Prediction of Ecosystem Carbon Storage: A Case Study in the Yangtze River Delta Urban Agglomeration, China. Authorea . 18 August 2025. DOI: https://doi.org/10.22541/au.175550069.95344755/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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