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Record W2970823884 · doi:10.15517/rbt.v67i2supl.37252

Effect of El Niño and La Niña on abundance of frugivorous and nectarivorous terrestrial birds in three tropical forests

2019· article· en· W2970823884 on OpenAlexfundno aff
Gilbert Barrantes, Luis Sandoval

Bibliographic record

VenueRevista de Biología Tropical · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersConsejo Nacional para Investigaciones Científicas y TecnológicasMinisterio de Ciencia y TecnologíaGovernment of OntarioUniversity of Windsor
KeywordsFrugivoreAbundance (ecology)EcologyBiologyRainforestEcosystemPopulationHabitat

Abstract

fetched live from OpenAlex

El Niño and La Niña climatic oscillations have dramatic effects on population dynamics and community structure of different animals. For marine birds, El Niño phenomenon drastically increases their mortality and reduces their reproductive success. In terrestrial ecosystems, the lack of long-term longitudinal data limits our understanding of the impact of El Niño and La Niña on bird populations and communities. We analyzed changes in abundance of frugivorous (large, medium, and small) and nectarivorous birds on three tropical forest types (lowland, premontane and montane) during El Niño, La Niña and neutral years using data from 16 Christmas’ Bird Counts in Costa Rica. Abundance of large and medium size frugivores increased during La Niña events, and the abundance of nectarivores during El Niño in the lowland forest, but neither of these events affected the abundance of small frugivores. In the montane forest, abundance of all four bird groups increased during El Niño, but decreased during La Niña events. Abundance of large, and small frugivores increased in the premontane forest during La Niña events, but other bird groups were not affected by La Niña. The abundance of small frugivores also increased during El Niño. We hypothesize that changes in abundance of frugivores and nectarivores during La Niña and El Niño events is probably correlated with fluctuations in food resources as it has been reported for other terrestrial tropical ecosystems.

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 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 score0.432

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 studies0.0000.001
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 head0.005
GPT teacher head0.248
Teacher spread0.242 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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