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Record W2576652718 · doi:10.1371/journal.pone.0168943

The Paucity of Frugivores in Madagascar May Not Be Due to Unpredictable Temperatures or Fruit Resources

2017· article· en· W2576652718 on OpenAlexaff
Sarah Federman, Miranda Sinnott‐Armstrong, Andrea L. Baden, Colin A. Chapman, Douglas C. Daly, Alison R. Richard, Kim Valenta, Michael J. Donoghue

Bibliographic record

VenuePLoS ONE · 2017
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
FundersConservation InternationalNational Science Foundation
KeywordsFrugivorePhenologyEcologyPredictabilityNational parkBiotaSeed dispersalTropical climateResource (disambiguation)TropicsBiologyClimate changeBiological dispersalHabitatDemography

Abstract

fetched live from OpenAlex

The evolution of ecological idiosyncrasies in Madagascar has often been attributed to selective pressures stemming from extreme unpredictability in climate and resource availability compared to other tropical areas. With the exception of rainfall, few studies have investigated these assumptions. To assess the hypothesis that Madagascar's paucity of frugivores is due to unreliability in fruiting resources, we use statistical modeling to analyze phenology datasets and their environmental correlates from two tropical wet forests, the Réserve Naturelle Intégrale Betampona in Madagascar, and Kibale National Park in Uganda. At each site we found that temperature is a good environmental predictor of fruit availability. We found no evidence of a significant difference in the predictability of fruit availability between the two sites, although the shorter duration of phenological monitoring at Betampona (two years, versus 15 years at Kibale) limits our ability to infer long-term patterns. Comparisons of long-term temperature data from each site (15 years from Kibale and 14 from Betampona) indicate that temperature is more predictable at Betampona than at Kibale. However, there does appear to be a difference between the two sites in the total fruit availability at any given time, with fruit being generally less abundant at Betampona. Our results appear contrary to the prevailing hypothesis of a selective force imposed by unpredictable resource availability or temperature, and we suggest other possible explanations for Madagascar's unique biota.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.326
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.

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

Citations24
Published2017
Admission routes1
Has abstractyes

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