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Record W2086521671 · doi:10.1155/2013/602845

Influences of Movement Behavior on Animal Distributions at Edges of Homogeneous Patches

2013· article· en· W2086521671 on OpenAlexafffund
Hilary C. Young, Tyler G. Reid, Lea A. Randall, Leanna E. Lachowsky, Danusha J. Foster, Chris J. Pengelly, Tanya Latty, Mary L. Reid

Bibliographic record

VenueInternational Journal of Zoology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsStantec (Canada)CochraneUniversity of TorontoToronto ZooCanada Research ChairsSNC-Lavalin (Canada)University of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsEnhanced Data Rates for GSM EvolutionMovement (music)OccupancyHabitatEcologyBiological systemDistribution (mathematics)HomogeneousBiologyGeometryStatistical physicsComputer scienceMathematicsPhysicsArtificial intelligenceMathematical analysis

Abstract

fetched live from OpenAlex

We propose that changes in movement behavior may be a proximate mechanism that influences the accumulation of animals at habitat edges. We tested this idea with a combination of empirical and simulation experiments in a resource-free landscape. The movements of individual flour beetles, Tribolium confusum , were tracked across a paper arena edged with invisible tape until beetles crossed the edge. Movement behavior (step lengths and turn angles) and cumulative occupancy were analyzed according to distance from the edge. We found that beetles took smaller steps with larger turn angles near edges than in the center of the arena and that beetle distribution was highly biased towards the edge of the arena. We then tested two agent-based simulation models for each beetle: an edge-independent model and an edge-dependent model. Both models predicted less time spent at the edge than was observed. The proportion of time spent at edges depended on the propensity to cross the edge, which could not be explained by beetle body size or energetic condition. The distribution of animals with respect to habitat edges depends on many factors, but we suggest that proximate mechanisms such as movement behavior should be explicitly considered when interpreting animal distributions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.998

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)0.0020.000

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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.

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

Citations9
Published2013
Admission routes2
Has abstractyes

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