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Record W2926332191 · doi:10.1016/j.jenvman.2019.02.130

Temperature sensitivity of soil organic matter decomposition after forest fire in Canadian permafrost region

2019· article· en· W2926332191 on OpenAlexaboutno aff
Heidi Aaltonen, Marjo Palviainen, Xuan Zhou, Egle Köster, Frank Berninger, Jukka Pumpanen, Kajar Köster

Bibliographic record

VenueJournal of Environmental Management · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsPermafrostEnvironmental scienceQ10Ecological successionSoil respirationEcosystemSubarctic climateSoil organic matterSoil carbonOrganic matterChronosequenceSoil waterHydrology (agriculture)Soil scienceEcologyGeologyRespirationOceanography

Abstract

fetched live from OpenAlex

Climate warming in arctic/subarctic ecosystems will result in increased frequency of forest fires, elevated soil temperatures and thawing of permafrost, which have implications for soil organic matter (SOM) decomposition rates, the CO2 emissions and globally significant soil C stocks in this region. It is still unclear how decomposability and temperature sensitivity of SOM varies in different depths and different stages of succession following forest fire in permafrost regions and studies on long term effects of forest fires in these areas are lacking. To study this question, we took soil samples from 5, 10 and 30 cm depths from forest stands in Northwest Canada, underlain by permafrost, that were burnt by wildfire 3, 25 and over 100 years ago. We measured heterotrophic soil respiration at 1, 7, 13 and 19 °C. Fire had a significant effect on the active layer depth, and it increased the temperature sensitivity (Q10) of respiration in the surface (5 cm) and in the deepest soil layer (30 cm) in the 3-year-old area compared to the 25- and more than 100-year-old areas. Also the metabolic quotient (qCO2) of soil microbes was increased after fire. Though fires may facilitate the SOM decomposition by increasing active layer depth, they also decreased SOM quality, which may limit the rate of decomposition. After fire all of these changes reverted back to original levels with forest succession.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.993

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)0.0080.000

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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.

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

Citations51
Published2019
Admission routes1
Has abstractyes

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