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Record W4409124806 · doi:10.1016/j.rse.2025.114717

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

2025· article· en· W4409124806 on OpenAlexafffund
Kathleen M. Orndahl, Logan T. Berner, Matthew J. Macander, Marie Frost Arndal, Heather D. Alexander, Elyn Humphreys, M. M. Loranty, S. Ludwig, Johanna Nyman, Sari Juutinen, Mika Aurela, Juha Mikola, Michelle C. Mack, Melissa Rose, Mathew R. Vankoughnett, Colleen M. Iversen, Jitendra Kumar, Verity Salmon, Dedi Yang, Paul Grogan, Ryan K. Danby, Neal A. Scott, Johan Olofsson, Matthias Siewert, Lucas Deschamps, Vincent Maire, Esther Lévesque, Gilles Gauthier, Stéphane Boudreau, Anna Gaspard, M. Syndonia Bret‐Harte, Martha K. Raynolds, Donald A. Walker, Anders Michelsen, Timo Kumpula, Miguel Villoslada, Henni Ylänne, Miska Luoto, Tarmo Virtanen, Heather E. Greaves, Bruce C. Forbes, Ramona Julia Heim, Norbert Hölzel, Howard E. Epstein, Andrew G. Bunn, R. M. Holmes, Susan M. Natali, Anna‐Maria Virkkala, S. J. Goetz

Bibliographic record

VenueRemote Sensing of Environment · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsQueen's UniversityNova Scotia Community CollegeCarleton University
FundersH2020 Fast Track to InnovationBiological and Environmental ResearchDivision of Environmental BiologyFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaAcademy of FinlandOffice of ScienceOtto A. Malm LahjoitusrahastoNordenskiöld-samfundetArcticNetU.S. Department of EnergyVetenskapsrådetQueen's UniversityEuropean CommissionNational Research CouncilOffice of Polar ProgramsUniversité LavalPolar Knowledge CanadaSocietas pro Fauna et Flora FennicaMinistère des Forêts, de la Faune et des ParcsDanmarks Frie ForskningsfondNational Science FoundationNational Aeronautics and Space AdministrationGoogleFP7 Ideas: European Research CouncilNatural Resources Canada
KeywordsTundraBiomeRemote sensingDominance (genetics)Environmental scienceVegetation (pathology)Biomass (ecology)ArcticArctic vegetationPhysical geographyEcologyGeographyEcosystemBiology

Abstract

fetched live from OpenAlex

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 R 2 ≈ 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. • Plant biomass was mapped across the Arctic at the highest resolution (30 m) to date. • Broad patterns of plant biomass were consistent with coarser-resolution maps. • Fine scale plant biomass distribution was shaped by topography and disturbance. • Plant biomass increased with growing season temperatures across the Arctic biome. • These new plant biomass maps can inform ecological monitoring and modeling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.239
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2025
Admission routes2
Has abstractyes

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