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Record W2259396992 · doi:10.1093/conphys/cov031

Manipulating glucocorticoids in wild animals: basic and applied perspectives

2015· article· en· W2259396992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConservation Physiology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsDalhousie UniversityUniversity of OttawaCarleton UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyStressorEcologyAbundance (ecology)PopulationDiversity (politics)TaxonEvolutionary biologyZoologyNeuroscienceDemography

Abstract

fetched live from OpenAlex

One of the most comprehensively studied responses to stressors in vertebrates is the endogenous production and regulation of glucocorticoids (GCs). Extensive laboratory research using experimental elevation of GCs in model species is instrumental in learning about stressor-induced physiological and behavioural mechanisms; however, such studies fail to inform our understanding of ecological and evolutionary processes in the wild. We reviewed emerging research that has used GC manipulations in wild vertebrates to assess GC-mediated effects on survival, physiology, behaviour, reproduction and offspring quality. Within and across taxa, exogenous manipulation of GCs increased, decreased or had no effect on traits examined in the reviewed studies. The notable diversity in responses to GC manipulation could be associated with variation in experimental methods, inherent differences among species, morphs, sexes and age classes, and the ecological conditions in which responses were measured. In their current form, results from experimental studies may be applied to animal conservation on a case-by-case basis in contexts such as threshold-based management. We discuss ways to integrate mechanistic explanations for changes in animal abundance in altered environments with functional applications that inform conservation practitioners of which species and traits may be most responsive to environmental change or human disturbance. Experimental GC manipulation holds promise for determining mechanisms underlying fitness impairment and population declines. Future work in this area should examine multiple life-history traits, with consideration of individual variation and, most importantly, validation of GC manipulations within naturally occurring and physiologically relevant ranges.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.130

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 head0.061
GPT teacher head0.255
Teacher spread0.194 · 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