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Record W2019869019 · doi:10.1111/oik.02207

Density‐dependent, central‐place foraging in a grazing herbivore: competition and tradeoffs in time allocation near water

2015· article· en· W2019869019 on OpenAlexaffabout
David Rozen‐Rechels, Floris M. van Beest, Emmanuelle Richard, Antonio Uzal, Sarah A. Medill, Philip D. McLoughlin

Bibliographic record

VenueOikos · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsForagingHerbivoreGrazingCompetition (biology)EcologyDensity dependenceBiology

Abstract

fetched live from OpenAlex

Optimal foraging theory addresses one of the core challenges of ecology: predicting the distribution and abundance of species. Tests of hypotheses of optimal foraging, however, often focus on a single conceptual model rather than drawing upon the collective body of theory, precluding generalization. Here we demonstrate links between two established theoretical frameworks predicting animal movements and resource use: central‐place foraging and density‐dependent habitat selection. Our goal is to better understand how the nature of critical, centrally placed resources like water (or minerals, breathing holes, breeding sites, etc.) might govern selection for food (energy) resources obtained elsewhere – a common situation for animals living in natural conditions. We empirically test our predictions using movement data from a large herbivore distributed along a gradient of water availability (feral horses, Sable Island, Canada, 2008–2013). Horses occupying western Sable Island obtain freshwater at ponds while in the east horses must drink at self‐excavated wells (holes). We studied the implications of differential access to water (time needed for a horse to obtain water) on selection for vegetation associations. Consistent with predictions of density‐dependent habitat selection, horses were reduced to using poorer‐quality habitat (heathland) more than expected close to water (where densities were relatively high), but were free to select for higher‐quality grasslands farther from water. Importantly, central‐place foraging was clearly influenced by the type of water‐source used (ponds vs. holes, the latter with greater time constraints on access). Horses with more freedom to travel (those using ponds) selected for grasslands at greater distances and continued to select grasslands at higher densities, whereas horses using water holes showed very strong density‐dependence in how habitat could be selected. Knowledge of more than one theoretical framework may be required to explain observed variation in foraging behavior of animals where multiple constraints simultaneously influence resource selection.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.303

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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 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

Citations47
Published2015
Admission routes2
Has abstractyes

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