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Record W4297476904 · doi:10.3390/jzbg3040037

An Improvement in Enclosure Design Can Positively Impact Welfare, Reduce Aggressiveness and Stabilise Hierarchy in Captive Galapagos Giant Tortoises

2022· article· en· W4297476904 on OpenAlexaff
Léa Fieschi‐Méric, Charlotte Ellis, Francesca Servini, Benjamin Tapley, Christopher J. Michaels

Bibliographic record

VenueJournal of Zoological and Botanical Gardens · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsLaurentian University
Fundersnot available
KeywordsCaptivityEnclosureAgonistic behaviourAnimal welfareWelfareHabitatEcologyBiologyZoologyAggressionPsychologySocial psychologyEngineering

Abstract

fetched live from OpenAlex

The interest in the welfare of zoo animals, from both the public and the scientific community, has long been biased towards mammals. However, growing evidence of the complex behavioural repertoires of less charismatic animals, such as reptiles, reveals the necessity to better comply with their welfare needs in captivity. Here, we present the effects of an enclosure change towards a more natural habitat in captive Galapagos tortoises (Chelonoidis spp.) held at ZSL London Zoo. Using behavioural observations, we found that the tortoises habituated to their new enclosure in six days. This represents the first quantification of habituation latency to a new enclosure in a reptile model to our knowledge—which is important information to adapt policies governing animal moves. The tortoises expressed time budgets more similar to those of wild individuals after their transition to the new enclosure. Interestingly, the hierarchy between the individuals was inverted and more stable after this change in environment. The tortoises interacted less often, which led to a decrease in the frequency of agonistic encounters. We also found that higher ambient sound volume was associated with increased likelihood of interactions turning into fights. Taken together, our results demonstrate the potential of appropriate enclosure design to improve reptile welfare.

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)0.001
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 score0.812
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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