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Record W2295284841 · doi:10.1890/15-1638.1

Trophic interactions determine the effects of drought on an aquatic ecosystem

2016· article· en· W2295284841 on OpenAlexaff
Sarah L. Amundrud, Diane S. Srivastava

Bibliographic record

VenueEcology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTrophic cascadeEcologyTrophic levelFood webEcosystemPredationMicrocosmBiologyStressorApex predatorCommunity

Abstract

fetched live from OpenAlex

Species interactions can be important mediators of community and ecosystem responses to environmental stressors. However, we still lack a mechanistic understanding of the indirect ecological effects of stress that arise via altered species interactions. To understand how species interactions will be altered by environmental stressors, we need to know if the species that are vulnerable to such stressors also have large impacts on the ecosystem. As predators often exhibit certain traits that are linked to a high vulnerability to stress (e.g., large body size, long generation time), as well as having large effects on communities (e.g., top-down trophic effects), predators may be particularly likely to mediate ecological effects of environmental stress. Other functional groups, like facilitators, are known to have large impacts on communities, but their vulnerability to perturbations remains undocumented. Here, we use aquatic insect communities in bromeliads to examine the indirect effects of an important stressor (drought) on community and ecosystem responses. In a microcosm experiment, we manipulated predatory and facilitative taxa under a range of experimental droughts, and quantified effects on community structure and ecosystem function. Drought, by adversely affecting the top predator, had indirect cascading effects on the entire food web, altering community composition and decomposition. We identified the likely pathway of how drought cascaded through the food web from the top-down as drought -->predator --> shredder --> decomposition. This stress-induced cascade depended on predators exhibiting both a strong vulnerability to drought and large impacts on prey (especially shredders), as well as shredders exhibiting high functional importance as decomposers.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.998

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)0.0230.002

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 head0.014
GPT teacher head0.247
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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

Citations48
Published2016
Admission routes1
Has abstractyes

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