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Record W2153036997 · doi:10.1093/beheco/arl055

Short-term behavioral consequences of territory relocation in a Caribbean damselfish, Stegastes diencaeus

2006· article· en· W2153036997 on OpenAlexaff
Peter T. McDougall, Donald L. Kramer

Bibliographic record

VenueBehavioral Ecology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDamselfishRelocationBiological dispersalPhilopatryAgonistic behaviourBiologyEcologyRange (aeronautics)HabitatPomacentridaeHome rangeTerritorialityBurrowFisheryCoral reef fishAggressionDemographyPopulation

Abstract

fetched live from OpenAlex

Home-range relocation occurs during natal and breeding dispersal, ontogenetic habitat shifts, and the maintenance of resource- or density-dependent patterns of distribution. Relocating animals are expected to change their behavior to compensate for limited familiarity with the new home range and with neighboring conspecifics; such changes may indicate some of the costs of relocation. Little is known, however, about the magnitude and duration of the changes or about the types of behavior affected. We investigated the short-term (2 day) behavioral changes associated with relocation in the highly territorial longfin damselfish, Stegastes diencaeus. We compared the behavior of newcomers settling into experimentally created vacancies in an established neighborhood with that of the original residents of the same territories. The greatest difference was an increase in the rate of agonistic interactions. Newcomers also used smaller territories, moved more, and fed less. Neighboring damselfishes were less aggressive toward neighbors that expanded into vacant territories than toward “strangers” that relocated from elsewhere. The behavior of newcomers approached that of original residents within 2 days but territory size did not. These observations suggest that relocating a territory increases energy expenditure and decreases energy intake. Such costs could explain the philopatry of reef fish when alternative locations are of uncertain quality or are only slightly better. Nevertheless, they are unlikely to outweigh the long-term benefits of obtaining a superior territory—especially for individuals from adjacent territories.

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 score0.126
Threshold uncertainty score0.981

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 head0.020
GPT teacher head0.268
Teacher spread0.248 · 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

Citations32
Published2006
Admission routes1
Has abstractyes

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