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Record W3171204665 · doi:10.1080/11956860.2021.1932293

Birds of the Land of Swallows: contribution of the main ecosystems of Cozumel Island to its avian diversity

2021· article· en· W3171204665 on OpenAlexvenueno aff
Ian MacGregor‐Fors, Miguel A. Gómez‐Martínez, Luis‐Bernardo Vázquez, M. Luisa Martínez

Bibliographic record

VenueEcoscience · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsMangroveGeographyBiodiversityEcologySpecies richnessEndemismThicketEcosystemArecaceaeAgroforestryBiologyHabitatPalm

Abstract

fetched live from OpenAlex

Caribbean islands are important hotspots for endemic species, concentrating high biodiversity on exceptionally small areas. Cozumel Island is not an exception, yet little published information exists on its bird diversity. In this study, we assessed the contribution of each major ecosystem of Cozumel Island (i.e., tropical forest, mangrove, palm thicket, and urban setting) to the island's avian diversity. Avian richness was highest in tropical forests, followed by mangroves, palm thickets, and urban setting. Bird densities were highest in urban settings, followed by tropical forests, mangroves, and palm thickets. Species composition similarity among ecosystems was low, with the most dissimilar ecosystem being the urban setting. Interestingly, we recorded the highest number of unique species in mangroves, followed by tropical forests, urban settings, and palm thickets. Tropical forests and mangroves of Cozumel Island are the main ecosystems harboring high avian diversity, with tropical forests housing high avian densities and endemics and mangroves including the most unique species. As expected, the contribution of urban settings to the avian diversity of Cozumel Island is limited and includes some highly abundant invasive species, of which the Eurasian Collared-Dove could represent a major ecological threat.

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 score0.026
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.215
Teacher spread0.199 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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