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Record W1977961299 · doi:10.1098/rstb.2014.0112

Competing pressures on populations: long-term dynamics of food availability, food quality, disease, stress and animal abundance

2015· article· en· W1977961299 on OpenAlexafffund
Colin A. Chapman, Valérie A. M. Schoof, Tyler R. Bonnell, Jan F. Gogarten, Sophie Calmé

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2015
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversité de SherbrookeUniversity of LethbridgeMcGill University
FundersFogarty International CenterCanadian Institutes of Health Research
KeywordsBiologyAbundance (ecology)EcologyPopulationSocialityEndangered speciesBiomass (ecology)HabitatDemography

Abstract

fetched live from OpenAlex

Despite strong links between sociality and fitness that ultimately affect the size of animal populations, the particular social and ecological factors that lead to endangerment are not well understood. Here, we synthesize approximately 25 years of data and present new analyses that highlight dynamics in forest composition, food availability, the nutritional quality of food, disease, physiological stress and population size of endangered folivorous red colobus monkeys (Procolobus rufomitratus). There is a decline in the quality of leaves 15 and 30 years following two previous studies in an undisturbed area of forest. The consumption of a low-quality diet in one month was associated with higher glucocorticoid levels in the subsequent month and stress levels in groups living in degraded forest fragments where diet was poor was more than twice those in forest groups. In contrast, forest composition has changed and when red colobus food availability was weighted by the protein-to-fibre ratio, which we have shown positively predicts folivore biomass, there was an increase in the availability of high-quality trees. Despite these changing social and ecological factors, the abundance of red colobus has remained stable, possibly through a combination of increasing group size and behavioural flexibility.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.938

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 studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.197
GPT teacher head0.384
Teacher spread0.188 · 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

Citations52
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePhilosophical Transactions of the Royal Society B Biological SciencesSame topicPrimate Behavior and EcologyFrench-language works237,207