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Record W3083009341 · doi:10.1111/cobi.13630

Trends in seabird breeding populations across the Great Barrier Reef

2020· article· en· W3083009341 on OpenAlexfundno aff
Bradley K. Woodworth, Richard A. Fuller, Graham Hemson, Andrew McDougall, Bradley C. Congdon, Matthew Low

Bibliographic record

VenueConservation Biology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaSvenska Forskningsrådet Formas
KeywordsSeabirdGreat barrier reefGeographyFisheryReefEcologyBiology

Abstract

fetched live from OpenAlex

The Great Barrier Reef is an iconic ecosystem, known globally for its rich marine biodiversity that includes many thousands of tropical breeding seabirds. Despite indications of localized declines in some seabird species from as early as the mid-1990s, trends in seabird populations across the reef have never been quantified. With a long history of human impact and ongoing environmental change, seabirds are likely sentinels in this important ecosystem. Using 4 decades of monitoring data, we estimated site-specific trends for 9 seabird species from 32 islands and cays across the reef. Trends varied markedly among species and sites, but probable declines occurred at 45% of the 86 species-by-site combinations analyzed compared with increases at 14%. For 5 species, we combined site-specific trends into a multisite trend in scaled abundance, which revealed probable declines of Common Noddy (Anous stolidus), Sooty Tern (Onychoprion fuscatus), and Masked Booby (Sula dactylatra), but no long-term changes in the 2 most widely distributed species, Greater Crested Tern (Thalasseus bergii) and Brown Booby (Sula leucogaster). For Brown Booby, long-term stability largely resulted from increases at a single large colony on East Fairfax Island that offset declines at most other sites. Although growth of the Brown Booby population on East Fairfax points to the likely success of habitat restoration on the island, it also highlights a general vulnerability wherein large numbers of some species are concentrated at a small number of key sites. Identifying drivers of variation in population change across species and sites while ensuring long-term protection of key sites will be essential to securing the future of seabirds on the reef.

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 score0.021
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.077
GPT teacher head0.317
Teacher spread0.239 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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