Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities
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Le résumé fourni par la source
Abstract The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB ( r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities
- Date Crossref
- 03/03/2026
- Éditeur
- IOP Publishing
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of Utah pays non établi dans la noticeUniversité ou école supérieure
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Northern Arizona University pays non établi dans la noticeUniversité ou école supérieure
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Goddard Space Flight Center pays non établi dans la noticeStructure de recherche
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University of Illinois Chicago Department of Plant Biology pays non établi dans la noticeUniversité ou école supérieure
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Carnegie Department of Plant Biology pays non établi dans la noticeStructure de recherche
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Oak Ridge National Laboratory Environmental Sciences Division pays non établi dans la noticeStructure de recherche
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University of Maryland Department of Geographical Sciences pays non établi dans la noticeUniversité ou école supérieure
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School of Biological Sciences pays non établi dans la noticeUniversité ou école supérieure
University of Utah, Northern Arizona University et Goddard Space Flight Center, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.