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Record W1573335867 · doi:10.1111/jzo.12168

Red flour beetles balance thermoregulation and food acquisition via density‐dependent habitat selection

2014· article· en· W1573335867 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Zoology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsEctothermHabitatIdeal free distributionBiologyEcologyEcological trapSelection (genetic algorithm)PopulationAbundance (ecology)

Abstract

fetched live from OpenAlex

Abstract Theories of habitat selection assume that habitat selection patterns are based on the fitness consequences of selecting a particular habitat, and predict that individuals should be distributed between habitats so that each individual obtains the same fitness. The predictions are relatively simple when habitat suitability is based upon the quantity of depletable resources, such as food, in a habitat: individuals should be distributed between habitats in proportion to the depletable resources in those habitats. Yet, non‐depletable resources can also be important in habitat selection. For example, ectotherms must obtain heat from the environment, which causes them to select habitats based, at least partly, upon thermal quality. Non‐depletable resources can cause habitat selection that is independent of density and may modify the value of depletable resources. We used red flour beetles Tribolium castaneum to test the hypothesis that habitat selection by ectotherms depends upon both food abundance and temperature. We determined the thermal preference of red flour beetles. We then conducted habitat selection experiments with beetles when habitats were set at their preferred temperature and 10°C below their preferred temperature. We simultaneously manipulated food abundance in both habitats, and varied population density. We also examined the fitness effects of habitat selection by measuring oviposition rates of beetles. Beetles selected the habitat within their preferred temperature when food was equal between habitats and when food was higher in that habitat across all population densities. Beetles showed equal preference for high‐ and low‐temperature habitats when food was higher in the low‐temperature habitat across all population densities. Fecundity was always higher at the preferred temperature of beetles, regardless of food abundance or population density. Temperature is clearly an important factor in habitat selection of ectotherms and should be considered whenever thermal differences exist between habitats.

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 score0.892
Threshold uncertainty score0.103

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)0.0000.000

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 head0.007
GPT teacher head0.194
Teacher spread0.186 · 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