An improved approach to estimate the natural land carbon sink

An improved approach to estimate the natural land carbon sink | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article An improved approach to estimate the natural land carbon sink Michael O'Sullivan, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7207206/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract The natural land carbon sink (SLAND) absorbs roughly 25-30% of anthropogenic CO2 emissions, thus playing a critical role in offsetting climate warming. In the Global Carbon Budget (GCB), SLAND is estimated using model simulations that isolate the carbon response of land to environmental changes (i.e. rising atmospheric CO2, nitrogen deposition, and changes in climate). However, these simulations assume fixed pre-industrial land cover, failing to represent today’s human-altered landscapes. This leads to a systematic overestimation of forest area, and thus CO2 sink strength, in regions heavily altered by human activity. We present a new process-based approach to estimate SLAND using Dynamic Global Vegetation Models. Our corrected estimate reduces SLAND by ~20% (0.6 PgC yr-1) over 2015-2024, from 3.00±0.94 to 2.42±0.77 PgC yr-1. We incorporate this new SLAND estimate with emissions from land-use change from bookkeeping models, to estimate a net land sink of 1.19±1.04 PgC yr-1, which aligns closely with atmospheric inversion constraints. This downward revision of SLAND reduces the magnitude of the budget imbalance for 2015-2024, indicating a more consistent partitioning of the global carbon budget. Earth and environmental sciences/Biogeochemistry/Carbon cycle Earth and environmental sciences/Climate sciences/Biogeochemistry/Carbon cycle Earth and environmental sciences/Climate sciences/Climate change/Climate and Earth system modelling carbon land global budget natural Full Text Additional Declarations The authors declare no competing interests. Supplementary Files Supplementarytext.pdf Supplementary File Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7207206","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":493794732,"identity":"1569fa66-79be-4ca1-80f2-b995cbecf343","order_by":0,"name":"Michael 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