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Environmental drivers of ophiuroid species richness on seamounts

2010· article· en· W2159748382 on OpenAlex
Timothy D. O’Hara, Derek P. Tittensor

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMarine Ecology · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsDalhousie University
FundersLIFE programmeCommonwealth Scientific and Industrial Research OrganisationMuséum National d'Histoire NaturelleAustralian Government
KeywordsSpecies richnessSeamountHabitatEcologyLatitudeRange (aeronautics)Generalized additive modelEnvironmental scienceBenthic zoneOceanographyLongitudeGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Benthic communities on seamounts are frequently characterised as being species rich, yet there is considerable variation in observed species richness. Although large‐scale patterns of species richness have been described from many marine and terrestrial habitats, their environmental drivers often remain poorly understood. We compared species richness of ophiuroids (brittle‐stars) on 60 seamounts throughout the South West Pacific Ocean, and used an information‐theoretic approach and generalized linear models to determine the relative importance of predictor variables. Due to high correlation among many environmental variables, we used a reduced set of predictors in an a priori model framework. Temperature was the only environmental predictor of any importance in these models over the bathymetric range of the study. Post‐hoc analyses of other potential environmental predictor variables showed that depth, calcite saturation state, temperature range, modelled current velocity and latitude all had some predictive value, but were also highly correlated with temperature or other environmental variables included in the a priori model. Longitude, large‐area species richness, habitat suitability for stony corals, and modelled POC flux did not have high predictive value. We hypothesise that temperature affects richness by constraining species distributions; in particular fewer species can tolerate the conditions on relatively warm shallow seamount summits.

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

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)0.0750.001

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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