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Record W4327938281 · doi:10.1111/jbi.14599

Functional diversity patterns of reef fish, corals and algae in the Brazilian biogeographical province

2023· article· en· W4327938281 on OpenAlexaff
André Luís Luza, Anaide W. Aued, Diego R. Barneche, Murilo S. Dias, Carlos Eduardo Leite Ferreira, Sergio R. Floeter, Ronaldo B. Francini‐Filho, Guilherme Ortigara Longo, Juan P. Quimbayo, Mariana G. Bender

Bibliographic record

VenueJournal of Biogeography · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMemorial University of Newfoundland
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsSpecies richnessEcologyBiologyTaxonReefCoral reefAlgaeCoral reef fish

Abstract

fetched live from OpenAlex

Abstract Aim Functional diversity encapsulates whole‐community responses to environmental gradients mediated by species traits. Under trait convergence, similar responses may cause distantly related taxa to exhibit spatially correlated functional diversity. We investigated whether similar responses of reef fish, coral and algal functional richness and disparity to the environment produce spatially correlated functional diversity patterns. Location Brazilian marine biogeographical province. Taxon Reef fish, corals, algae. Methods We analysed data from 40 coastal and oceanic sites distributed across 27 degrees of latitude in the Brazilian province. Using traits, we measured functional richness (FRic) and disparity (Rao's Q ) and calculated Pearson's correlation () between pairs of metrics and taxa. We used Bayesian multivariate linear models to model taxa functional richness and disparity relative to sea surface temperature (SST), turbidity, salinity, species richness and region, and to estimate the residual correlation () between metrics after accounting for these variables. Results The best fitted model contained SST, species richness and region, and explained about 56% of the variation in FRic and Rao's Q across taxa. Yet, FRic and Rao's Q of fish, algae and corals responded differently to environmental variables. Functional diversity metrics were less correlated between algae and corals than compared to fish. Observed correlations of FRic and Rao's Q were low to intermediate across taxa (average = 0.14), and residual correlations were even lower (average = 0.02). Main conclusions SST, species richness and region had a widespread role in determining spatially congruent functional diversity offish, algae and corals across Brazilian reefs, despite their fundamentally different evolutionary histories. Low residual spatial correlations suggest that other mechanisms might also contribute to functional diversity patterns of reef taxa independently. Given the role of SST, species richness and region, the functional structure of these reefs might be compromised by climate change, pollution and overfishing.

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)0.001
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 score0.004
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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