MétaCan
Menu
← Back to cohort

Climate change impacts on CO2 and CH4 exchange in an Arctic polygonal tundra depend on changes in vegetation and drainage

2020· article· en· W3091172891 on OpenAlexaff
R. F. Grant

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTundraAdenylate kinaseChemistryAnimal scienceBiologyEcologyArcticBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Model projections of CO2 and CH4 exchange in Arctic tundra during the next century diverge widely. In this modelling study, we used ecosys to examine how climate change will affect CO2 and CH4 exchange through its effects on net primary productivity (NPP), heterotrophic respiration (Rh) and thereby on net ecosystem productivity (NEP) in landform features (troughs, rims, centers) of a coastal polygonal tundra landscape at Barrow AK. The model was shown to simulate diurnal and seasonal variation in CO2 and CH4 fluxes associated with those in air and soil temperatures (Ta and Ts) and soil water contents (q) under current climate in 2014 and 2015. During RCP 8.5 climate change from 2015 to 2085, rising Ta, atmospheric CO2 concentrations (Ca) and precipitation (P) increased NPP from 50 – 150 g C m-2 y-1, consistent with current biometric estimates, to 200 – 250 g C m-2 y-1, depending on feature elevation. Concurrent increases in Rh were slightly smaller, so that net CO2 exchange rose from values of -25 (net emission) to +50 (net uptake) g C m-2 y-1 to ones of -10 to +65 g C m-2 y-1, again depending on feature elevation. Large increases in Rh with thawing permafrost were not modelled. Increases in net CO2 uptake were largely offset by increases in CH4 emissions from 0 – 6 g C m-2 y-1 to 1 – 20 g C m-2 y-1, depending on feature elevation, reducing gains in NEP. Increases in CH4 emissions with climate change were mostly attributed to increases in Ta, but also to increases in Ca and P. These increases in net CO2 uptake and CH4 emissions were modelled with hydrological boundary conditions that were assumed not to change with climate. Both these increases were smaller if boundary conditions were gradually altered to increase landscape drainage during model runs with climate change. The model was then applied to the entire permafrost zone of North America to project RCP 8.5 climate change effects on active layer depth and ecosystem productivity by 2100.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.542

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.267
Teacher spread0.198 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicClimate change and permafrost→French-language works237,207→