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Record W2023648518 · doi:10.1111/aje.12186

Wet and dry season diets of the Endangered<i>Lemur catta</i>(ring-tailed lemur) in two mountainous rocky outcrop forest fragments in south-central Madagascar

2014· article· en· W2023648518 on OpenAlexafffund
Lisa Gould, Denise N. Gabriel

Bibliographic record

VenueAfrican Journal of Ecology · 2014
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsQuest University CanadaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaPrimate Conservation
KeywordsLemur cattaLemurDry seasonEcologyBiologyEndangered speciesWet seasonGeographyForestryHabitat

Abstract

fetched live from OpenAlex

Lemur catta's ability to consume a wide variety of plant foods is a key to this species' survival in a time of ecological crisis across its geographic range. We examined seasonal diet variability of L. catta groups inhabiting two rocky outcrop fragments in south-central Madagascar: Anja Reserve and Tsaranoro Valley forest. Leaves and fruit of Melia azedarach were a keystone resource for Anja lemurs in wet and dry seasons. At Tsaranoro, L. catta relied on M. azedarach and Ficus spp. in dry season, but during the wet season, neither was a dominant food resource. Top food species at both sites differed markedly from those consumed by L. catta in other habitats. At Tsaranoro, a greater proportion of lemurs engaged in feeding during the dry season compared with wet season. We attribute this to resource scarcity during dry season, when greater feeding effort is needed to maintain energy requirements. Because M. azedarach is ubiquitous throughout Anja Reserve, producing fruit and leaves year-round, Anja lemurs can meet energy requirements with little seasonal adjustment in feeding activity. L. catta's IUCN status has been upgraded to Endangered, thus, greater insight into its diet flexibility and ability to survive on introduced plant species, can inform conservation plans in remaining wild habitats and ex situ programs.

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 score0.010
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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

Citations26
Published2014
Admission routes2
Has abstractyes

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