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Record W2165137364 · doi:10.1111/ele.12109

Microbial community responses to anthropogenically induced environmental change: towards a systems approach

2013· article· en· W2165137364 on OpenAlexaff
Andrew Bissett, Mark V. Brown, Steven D. Siciliano, Peter H. Thrall

Bibliographic record

VenueEcology Letters · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEcosystemEcologyEnvironmental changeBiotaEcosystem servicesEnvironmental resource managementSoil biologyBiogeochemical cycleEnvironmental scienceMicrobial population biologyClimate changeBiologySoil water

Abstract

fetched live from OpenAlex

The soil environment is essential to many ecosystem services which are primarily mediated by microbial communities. Soil physical and chemical conditions are altered on local and global scales by anthropogenic activity and which threatens the provision of many soil services. Despite the importance of soil biota for ecosystem function, we have limited ability to predict and manage soil microbial community responses to change. To better understand causal relationships between microbial community structure and ecological function, we argue for a systems approach to prediction and management of microbial response to environmental change. This necessitates moving beyond concepts of resilience, resistance and redundancy that assume single optimum stable states, to ones that better reflect the dynamic and interactive nature of microbial systems. We consider the response of three soil groups (ammonia oxidisers, denitrifiers, symbionts) to anthropogenic perturbation to motivate our discussion. We also present a network re-analysis of a saltmarsh microbial community which illustrates how such approaches can reveal ecologically important connections between functional groups. More generally, we suggest the need for integrative studies which consider how environmental variables moderate interactions between functional groups, how this moderation affects biogeochemical processes and how these feedbacks ultimately drive ecosystem services provided by soil biota.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.245
Teacher spread0.209 · 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 designTheoretical or conceptual
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

Citations334
Published2013
Admission routes1
Has abstractyes

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