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Record W2004622093 · doi:10.1073/pnas.1319618111

Effects of differential habitat warming on complex communities

2014· article· en· W2004622093 on OpenAlexafffund
Tyler D. Tunney, Kevin S. McCann, Nigel P. Lester, Brian J. Shuter

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of TorontoMinistry of Natural Resources and ForestryUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHabitatClimate changeEcosystemApex predatorEnvironmental scienceEcologyFood webBorealGlobal warmingPredatorBiologyPredation

Abstract

fetched live from OpenAlex

Food webs unfold across a mosaic of micro and macro habitats, with each habitat coupled by mobile consumers that behave in response to local environmental conditions. Despite this fundamental characteristic of nature, research on how climate change will affect whole ecosystems has overlooked (i) that climate warming will generally affect habitats differently and (ii) that mobile consumers may respond to this differential change in a manner that may fundamentally alter the energy pathways that sustain ecosystems. This reasoning suggests a powerful, but largely unexplored, avenue for studying the impacts of climate change on ecosystem functioning. Here, we use lake ecosystems to show that predictable behavioral adjustments to local temperature differentials govern a fundamental structural shift across 54 food webs. Data show that the trophic pathways from basal resources to a cold-adapted predator shift toward greater reliance on a cold-water refuge habitat, and food chain length increases, as air temperatures rise. Notably, cold-adapted predator behavior may substantially drive this decoupling effect across the climatic range in our study independent of warmer-adapted species responses (for example, changes in near-shore species abundance and predator absence). Such modifications reflect a flexible food web architecture that requires more attention from climate change research. The trophic pathway restructuring documented here is expected to alter biomass accumulation, through the regulation of energy fluxes to predators, and thus potentially threatens ecosystem sustainability in times of rapid environmental change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.538

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.272
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations118
Published2014
Admission routes2
Has abstractyes

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