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Record W2895949802 · doi:10.5194/tc-13-647-2019

Large carbon cycle sensitivities to climate across a permafrost thaw gradient in subarctic Sweden

2019· article· en· W2895949802 on OpenAlexaff
Kuang‐Yu Chang, W. J. Riley, Patrick Crill, R. F. Grant, Virginia I. Rich, S. R. Saleska

Bibliographic record

Venue˜The œcryosphere · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Alberta
FundersBiological and Environmental ResearchVetenskapsrådetPolarforskningssekretariatetU.S. Department of Energy
KeywordsPermafrostSubarctic climateEnvironmental scienceBogPeatBiogeochemical cycleRadiative forcingCarbon cycleClimate changeActive layerWater tableSoil carbonClimatologyBlack spruceAtmospheric sciencesEcosystemGeologyTaigaSoil scienceEcologyGroundwaterSoil waterOceanographyChemistry

Abstract

fetched live from OpenAlex

Permafrost peatlands store large amounts of carbon potentially vulnerable to decomposition. However, the fate of that carbon in a changing climate remains uncertain in models due to complex interactions among hydrological, biogeochemical, microbial, and plant processes. In this study, we estimated effects of climate forcing biases present in global climate reanalysis products on carbon cycle predictions at a thawing permafrost peatland in subarctic Sweden. The analysis was conducted with a comprehensive biogeochemical model ( ecosys ) across a permafrost thaw gradient encompassing intact permafrost palsa with an ice core and a shallow active layer, partly thawed bog with a deeper active layer and a variable water table, and fen with a water table close to the surface, each with distinct vegetation and microbiota. Using in situ observations to correct local cold and wet biases found in the Global Soil Wetness Project Phase 3 (GSWP3) climate reanalysis forcing, we demonstrate good model performance by comparing predicted and observed carbon dioxide (CO 2 ) and methane (CH 4 ) exchanges, thaw depth, and water table depth. The simulations driven by the bias-corrected climate suggest that the three peatland types currently accumulate carbon from the atmosphere, although the bog and fen sites can have annual positive radiative forcing impacts due to their higher CH 4 emissions. Our simulations indicate that projected precipitation increases could accelerate CH 4 emissions from the palsa area, even without further degradation of palsa permafrost. The GSWP3 cold and wet biases for this site significantly alter simulation results and lead to erroneous active layer depth (ALD) and carbon budget estimates. Biases in simulated CO 2 and CH 4 exchanges from biased climate forcing are as large as those among the thaw stages themselves at a landscape scale across the examined permafrost thaw gradient. Future studies should thus not only focus on changes in carbon budget associated with morphological changes in thawing permafrost, but also recognize the effects of climate forcing uncertainty on carbon cycling.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations29
Published2019
Admission routes1
Has abstractyes

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