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Record W2811257475 · doi:10.1111/jfb.13745

A holistic investigation of the ecological correlates of abundance and body size for the endangered White's seahorse <i>Hippocampus whitei</i>

2018· article· en· W2811257475 on OpenAlexafffund
Clayton G. Manning, Sarah J. Foster, David Harasti, Amanda C. J. Vincent

Bibliographic record

VenueJournal of Fish Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersNatural Sciences and Engineering Research Council of CanadaNSW Department of Primary Industries
KeywordsSeagrassBiologyPredationEcologyEndangered speciesHabitatSeahorseAbundance (ecology)PredatorPopulationThreatened speciesCritically endangeredDemography

Abstract

fetched live from OpenAlex

Analysing the associations between the endangered White's seahorse Hippocampus whitei and characteristics of its environment (including habitat, prey and predator variables) in an estuary in New South Wales, Australia, revealed that seahorses had a greater number of significant associations with environmental correlates within a single seagrass bed than among seagrass beds. Predator abundance was negatively correlated with H. whitei abundances among seven seagrass beds (200-6,000 m apart) and no ecological correlate was associated with H. whitei body size distributions. Within the seagrass bed with the greatest number of H. whitei, individuals preferentially selected locations that were deeper, had denser seagrass, more epiphytic prey types and fewer predators. Smaller H. whitei were associated with greater depths within the bed. In this study, each class of ecological correlate (habitat, prey, predators) was found to have at least one significant relationship with H. whitei, depending on the scale, demonstrating that all three are important to H. whitei populations. As such, future studies that evaluate animal populations may benefit from holistic approaches that consider each of these together. For animals that are experiencing dramatic population declines due to habitat destruction, as H. whitei has over the last decade, a better understanding of its relationship to its environment is important to inform conservation action.

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)0.001
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 score0.265
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.031
GPT teacher head0.247
Teacher spread0.216 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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