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Record W1978362604 · doi:10.1071/mf11205

Climate-change induced tropicalisation of marine communities in Western Australia

2012· article· en· W1978362604 on OpenAlexafffund
William W. L. Cheung, Jessica J. Meeuwig, Ming Feng, Euan S. Harvey, Vicky W. Y. Lam, Tim Langlois, Dirk Slawinski, Chaojiao Sun, Daniel Pauly

Bibliographic record

VenueMarine and Freshwater Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsDepartment of Environment and ConservationUniversity of British Columbia
FundersUniversity of British ColumbiaNational Oceanic and Atmospheric AdministrationCommonwealth Scientific and Industrial Research Organisation
KeywordsClimate changeDominance (genetics)Range (aeronautics)OceanographyEcologyGeographyTrophic levelTemperate climateFishingInvertebrateLatitudeMarine protected areaSpecies distributionEnvironmental scienceFisheryBiologyHabitatGeology

Abstract

fetched live from OpenAlex

A major observed and predicted impact of climate change on marine species is the poleward shift in their distributions and the resulting changes in community structure. Here, we used a Dynamic Bioclimate Envelope Model to project range shift of exploited marine fishes and invertebrates in Western Australia. We combined published data and expert knowledge to predict current species distributions for 30 tropical, sub-tropical and temperate species that occur along the coast of Western Australia. Using outputs from both a Regional Oceanographic Model and a Global Circulation Model, we simulated change in the distribution of each species. Our study shows that under the SRES (Special Report for Emission Scenarios) A1B scenario, the median rate of distribution shift is around 19 km decade–1 towards higher latitudes and 9 m deeper decade–1 by 2055 relative to 2005. As a result, species gains and losses are expected along the south coast and north coast of Western Australia, respectively. Also, the coast of Western Australia is expected to experience a ‘tropicalisation’ of the marine community in the future, with increasing dominance of warmer-water species. Such changes in species assemblages may have large ecological and socio-economic implications through shifts in fishing grounds and unexpected trophic effects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.135
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.220
GPT teacher head0.367
Teacher spread0.146 · 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 source (direct Gemma or distilled Codex), 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

Citations114
Published2012
Admission routes2
Has abstractyes

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