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Record W1840064980 · doi:10.1111/ecog.01667

Microbial biogeography of permafrost thaw ponds across the changing northern landscape

2015· article· en· W1840064980 on OpenAlexafffundabout
Jérôme Comte, Adam Monier, Sophie Crévecoeur, Connie Lovejoy, Warwick F. Vincent

Bibliographic record

VenueEcography · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaMaterials and Energy Research CenterFonds de recherche du Québec – Nature et technologiesArcticNet
KeywordsPermafrostEcologyBiological dispersalSubarctic climateEnvironmental scienceEcosystemClimate changeBeta diversityMetacommunityPhysical geographyGeographyBiodiversityBiology

Abstract

fetched live from OpenAlex

Microbial diversity varies at multiple spatial scales, but little is known about how climate change may influence this variation. Here we assessed the free‐living bacterioplankton composition of thaw ponds over a north‐south gradient of permafrost degradation in the eastern Canadian subarctic. Three nested spatial scales were compared: 1) among ponds within individual valleys 2) between two valleys within each landscape type, and 3) between landscape types (southern sporadic versus northern discontinuous permafrost). As a reference point, we sampled rock‐basin lakes whose formation was not related to permafrost thawing. β‐diversity was low at the smallest scale despite marked differences in limnological properties among neighboring ponds. β‐diversity was high among valleys, associated with greater environmental heterogeneity. The largest differences were between landscape types and appeared to reflect the concomitant effects of environmental filtering and dispersal limitation. Raup–Crick β‐diversity indicated that community assembly was driven by both stochastic (random extinction, dispersal, ecological drift) and deterministic (environmental filtering) processes. Communities sampled in the most degraded valley appeared primarily assembled through stochastic processes, while environmental filtering played a greater role at the other valleys. These results imply that climate warming and ongoing permafrost degradation will influence microbial community assembly, which in turn is likely to affect the functioning of thaw pond ecosystems.

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 score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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

Citations64
Published2015
Admission routes3
Has abstractyes

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