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Precipitation explains Wood Thrush (Hylocichla mustelina) occupancy patterns in Northern Costa Rica

2024· article· en· W4392504391 on OpenAlexaff
Natalie V. Sánchez, Katherine Bonilla Badilla, César A. Estevo

Bibliographic record

VenueRevista de Biología Tropical · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsUniversity of AlbertaUniversity of Windsor
FundersGuanacaste Dry Forest Conservation FundU.S. Fish and Wildlife ServiceForest Conservation Fund
KeywordsOccupancyThrushPrecipitationGeographyEcologyEnvironmental scienceFisheryBiologyMeteorology

Abstract

fetched live from OpenAlex

Introduction: The Wood Thrush is a migratory bird that has experienced dramatic declines in its populations in recent decades. This species overwinters in forest fragments with intermediate levels of habitat modification in Central America. However, more studies detailing the use of remnant forests through time are needed to elucidate the threats this species faces in the wintering grounds. Objective: To understand the effects of environmental and forest structure variables on the occupancy of Wood Thrush in Northern Costa Rica. Methods: The study area was the Área de Conservación Guanacaste (ACG), located in Northern Costa Rica, in December 2016, and during the 2018-2019 migration season. We estimated Wood Thrush occupancy and detection probability in four locations of ACG (dry forest, cloud forest, and two locations in the wet forest) using single-season occupancy models. We also estimated Wood Thrush occupancy and probability of persistence in different months in three vegetation types (open area, secondary forest, and old-growth forest) in the wet forest of ACG using a multi-season occupancy model approach. Results: Wood Thrush occupancy was best described by precipitation in the four locations of the ACG; the probability of occupancy increased with precipitation. The average occupancy of Wood Thrushes varied with vegetation type: open area with shrubs and forest edge (0.69 ± 0.09), secondary forest (0.46 ± 0.1), and old-growth forest (0.61 ± 0.1). Wood Thrush probability of persistence responded partially to changes in precipitation, with an unexpected increase in persistence when the rainfall continued decreasing in the season. Conclusion: Wood Thrush occupancy was best predicted by changes in precipitation considering a larger spatial scale. Its probability of persistence partially varied with precipitation. An increase in persistence closer to Spring migration might be explained by the start of the breeding season of resident birds, potentially reducing territorial conflicts and conserving energy before migration. The long-term protection of wet forests in Northern Costa Rica is of paramount importance for the conservation of Wood Thrushes in their wintering grounds.

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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 score0.034
Threshold uncertainty score0.832

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)0.0010.001

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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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