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Predator identity and the nature and strength of food web interactions

2010· article· en· W2146768944 on OpenAlexafffund
Lee M. Henry, Jordan A. Bannerman, David R. Gillespie, Bernard D. Roitberg

Bibliographic record

VenueJournal of Animal Ecology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAgriculture and Agri-Food CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredatorPredationBiologyForagingTrophic levelAphidEcologyParasitoidFood webFunctional responseFood chainOptimal foraging theoryTrophic cascadeCommunityEcosystemHost (biology)Botany

Abstract

fetched live from OpenAlex

1. Most trophic interaction theory assumes that all predators are an abstract form of risk to which prey respond in a quantitatively similar manner. This conceptualization can be problematic because recent empirical work demonstrates that variation in the responses of prey to different predators can play a key role in structuring communities and regulating ecosystem function. 2. Predator identity - the species specific response of prey to a predator - has been proposed as an ultimate mechanism driving the relative contribution of indirect effects in food webs; however few studies have explicitly tested this hypothesis. 3. This study explores the impact of predator identity on direct consumptive (CE) and non-consumptive effects (NCEs), and on the relative contribution of indirect, density and trait-mediated effects in trophic cascades within host-parasitoid communities. 4. We systematically compared the individual, host-parasitoid-plant interactions of two actively foraging parasitoid species with disparate foraging styles, one aggressive and one furtive, a common aphid host and plant. Our results demonstrate that the degree of risk aversion by prey to each particular predator species (i.e. predator identity) is a key factor driving the nature and strength of direct and indirect transmission pathways. 5. Both parasitoid species, in general, had a negative impact on plants. The magnitude of the aphid anti-predator dispersal response was positively correlated with plant infestation and plant damage. The qualitative effect of predator-induced infestation of new plants superseded the quantitative effects of predator-mediated reductions in aphid numbers. 6. The greatest indirect impact on plants was generated by the aggressively foraging parasitoid, and the strength of the aphids anti-predator response (a NCE) antagonistically traded-off with CEs due to an increased investment in attempting to capture risk-sensitized prey. In contrast, the furtive parasitoid did not elicit a strong anti-predator response, had little indirect impact on plants, but generated very high CEs due to the advantage of ovipositing into a sedentary prey population. 7. Our data suggest the responses of prey to different predatory cues may be an important mechanism driving the relative contribution of transmission pathways in trophic cascades. We conclude that predator identity is a key factor influencing the nature and strength of food web interactions.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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 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

Citations34
Published2010
Admission routes2
Has abstractyes

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