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Record W2130822107 · doi:10.1890/es12-00379.1

How functional response and productivity modulate intraguild predation

2013· article· en· W2130822107 on OpenAlex
Arnaud Sentis, Jean‐Louis Hemptinne, Jacques Brodeur

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEcosphere · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIntraguild predationPredationFunctional responseEcologyPredatorMesocosmBiologyProductivityEcosystemEconomics

Abstract

fetched live from OpenAlex

Numerous models have been developed to predict the effect of environmental productivity on the coexistence of prey and predators within the three‐species module of intraguild predation. Theoretical models have mainly used Holling Type I and Type II functional response, the latter typically best describing the functional response of a predator. However, no empirical study has simultaneously examined the form of the functional response and the effect of prey density on intraguild interactions. This is surprising considering that the strength of the functional response is crucially important for the stability of simple predator‐prey systems and the persistence, sustainability and biodiversity of communities. In this study, we first developed a linear and a nonlinear functional response model for intraguild predators and next used a plant–aphid–predator mesocosm to parameterize the models and test their predictions at different prey densities. As expected, the assumptions of the linear model are not supported by empirical results which lead to systemic overestimation of the predation rate and the intensity of intraguild predation. On the other hand, the predictions of the nonlinear functional response model fit very well with experimental observations mainly because key behavioral characteristics such as handling time are integrated in this model. The nonlinear model is thus a good predictor of intraguild predation and allows a better understanding of how environmental productivity and predator behavior influence the occurrence and outcome of multiple predator 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.571

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)0.0010.000

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 head0.027
GPT teacher head0.165
Teacher spread0.137 · 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