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Record W4407397873 · doi:10.1111/conl.13080

Mismatch Between Global Importance of Peatlands and the Extent of Their Protection

2025· article· en· W4407397873 on OpenAlexaffabout
Kemen Austin, Paul R. Elsen, Eurídice N. Honorio Coronado, Alfred DeGemmis, Angela Gallego‐Sala, Lorna I. Harris, Heidi E. Kretser, Joe R. Melton, Daniel Murdiyarso, Sigit D. Sasmito, Erin Swails, Arief Wijaya, R. Scott Winton, Daniel J. Zarin

Bibliographic record

VenueConservation Letters · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsEnvironment and Climate Change CanadaWildlife Conservation Society Canada
FundersEuropean Research CouncilNatural Environment Research CouncilEuropean CommissionSight Research UK
KeywordsPeatEnvironmental scienceEnvironmental resource managementBusinessEnvironmental protectionNatural resource economicsEcologyBiologyEconomics

Abstract

fetched live from OpenAlex

ABSTRACT Global peatlands store more carbon than all the world's forests biomass on just 3% of the planet's land surface. Failure to address mounting threats to peatland ecosystems will jeopardize critical climate targets and exacerbate biodiversity loss. Our analysis reveals that 17% of peatlands are protected globally—substantially less than many other high‐value ecosystems. Just 11% percent of boreal and 27% of temperate and tropical peatlands are protected, while Indigenous peoples' lands encompass at least another one‐quarter of peatlands globally. Peatlands in protected areas and Indigenous peoples' lands generally face lower human pressure than outside those areas. Yet, almost half of temperate and tropical peatlands in protected areas still experience medium to high human pressure. Country submissions of Nationally Determined Contributions under the Paris Agreement and National Biodiversity Strategy and Action Plans under the Kunming–Montreal Global Biodiversity Framework could help catalyze actions and secure funding for peatland conservation, including support for the Indigenous stewardship that is critical to protect many of the world's highest priority peatland areas.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.146

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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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 designObservational
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

Citations15
Published2025
Admission routes2
Has abstractyes

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