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Record W4405927776 · doi:10.3390/ani15010053

Social Relationships of Captive Bachelor Przewalski’s Horses and Their Effect on Daily Activity and Space Use

2024· article· en· W4405927776 on OpenAlexaff
Anastasiia Nykonenko, Yevhen Moturnak, Philip D. McLoughlin

Bibliographic record

VenueAnimals · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCaptivityWelfareEquusSocial groupBiologyDemographyGeographyEcologyPsychologySocial psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

), daily time allocation and space use may be influenced by social structure and, in turn, reflect welfare. Here, we identify social relationships, time budgets, and spatial distribution of a group of nine older (aged 6-21 years) male Przewalski's horses living in a non-breeding (bachelor) group. We conducted our work at the Askania-Nova Biosphere Reserve, over 65 h of observation in summer, 2015. Horses formed stronger social bonds with individuals of similar gregariousness and dominance levels. Social-network analysis identified three distinct subgroups with significant differences in locomotion, social behaviour, and foraging. However, resting and vigilance behaviour remained similar across the subgroups. Behavioural synchrony across all activities was higher within subgroups than between. Space use was also affected by subgroup membership, with some horses overusing or underusing critical resource areas like hay and water. These findings suggest opportunities to improve welfare by adjusting space and resource distribution, particularly for more submissive individuals. Our approach may also aid in selecting reintroduction candidates by considering social characteristics alongside health, genetic, and other factors.

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 score0.033
Threshold uncertainty score0.233

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 head0.032
GPT teacher head0.254
Teacher spread0.222 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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