Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, AZ, Flagstaff, United States.
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, AZ, Flagstaff, United States.
ABR, Inc.—Environmental Research & Services, AK, Fairbanks, United States.
Department of Ecoscience, Aarhus University, Aarhus, Denmark.
Show others and affiliations
2025 (English)In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 323, article id 114717Article in journal (Refereed) Published
Abstract [en]

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m−2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m−2 (mean ≈ 350 g m−2), while predicted values ranged from 0 to ∼4000 g m−2 (mean ≈ 275 g m−2), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m−2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Place, publisher, year, edition, pages
Elsevier, 2025. Vol. 323, article id 114717
Keywords [en]
Climate change, Landsat, Pan Arctic, Plant biomass, Remote sensing, Vegetation distribution, Woody plant dominance
National Category
Climate Science
Identifiers
URN: urn:nbn:se:umu:diva-237402DOI: 10.1016/j.rse.2025.114717Scopus ID: 2-s2.0-105001483754OAI: oai:DiVA.org:umu-237402DiVA, id: diva2:1951303
Funder
Independent Research Fund Denmark, 0135-00140BIndependent Research Fund Denmark, 2032-00064BSwedish Research Council, 2021-05767)Academy of FinlandEU, FP7, Seventh Framework ProgrammeAcademy of Finland, 330319Academy of Finland, 330845Academy of Finland, 1342890European Commission, 869471Available from: 2025-04-10 Created: 2025-04-10 Last updated: 2025-04-10Bibliographically approved

Open Access in DiVA

fulltext(12967 kB)550 downloads
File information
File name FULLTEXT01.pdfFile size 12967 kBChecksum SHA-512
d0b12083bb5e11262519bd3e9bc710bf6e3c9d405f08411567b54fdad0458a3d1532cb693b7fd5cc016302a7e7d4323c19e9eab7ca9a37652e3afd83fe594a39
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Olofsson, JohanSiewert, Matthias B.
By organisation
Department of Ecology and Environmental Sciences
In the same journal
Remote Sensing of Environment
Climate Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 550 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 388 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf