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Record W4384914485 · doi:10.1071/mf22268

A deep dive into the ecology of Gamay (Botany Bay, Australia): current knowledge and future priorities for this highly modified coastal waterway

2023· article· en· W4384914485 on OpenAlexaff
Talia P. Stelling‐Wood, Paul E. Gribben, G.F. Birch, Melanie J. Bishop, C. Blount, David J. Booth, Culum Brown, Eleanor Bruce, Ana B. Bugnot, Maria Byrne, Robert G. Creese, Katherine A. Dafforn, John Dahlenburg, Martina A. Doblin, Thomas Fellowes, Ashley M. Fowler, Mitchell Gibbs, William Glamore, Tim M. Glasby, Amanda C. Hay, Brendan P. Kelaher, Nathan A. Knott, Anthony W. D. Larkum, Laura M. Parker, Ezequiel M. Marzinelli, Mariana Mayer‐Pinto, Bree Morgan, Shauna A. Murray, Matthew J. Rees, Pauline M. Ross, Moninya Roughan, Neil Saintilan, Elliot Scanes, Justin R. Seymour, Nina Schaefer, Iain M. Suthers, Matthew D. Taylor, Jane E. Williamson, Richard J. Whittington, Will F. Figueira

Bibliographic record

VenueMarine and Freshwater Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsStantec (Canada)
FundersIan Potter FoundationNSW Recreational Fishing Trust
KeywordsHabitatEcologyContext (archaeology)Traditional knowledgeGeographyRocky shoreEnvironmental resource managementBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Context Gamay is a coastal waterway of immense social, cultural and ecological value. Since European settlement, it has become a hub for industrialisation and human modification. There is growing desire for ecosystem-level management of urban waterways, but such efforts are often challenged by a lack of integrated knowledge. Aim and methods We systematically reviewed published literature and traditional ecological knowledge (TEK), and consulted scientists to produce a review of Gamay that synthesises published knowledge of Gamay’s aquatic ecosystem to identify knowledge gaps and future research opportunities. Key results We found 577 published resources on Gamay, of which over 70% focused on ecology. Intertidal rocky shores were the most studied habitat, focusing on invertebrate communities. Few studies considered multiple habitats or taxa. Studies investigating cumulative human impacts, long-term trends and habitat connectivity are lacking, and the broader ecological role of artificial substrate as habitat in Gamay is poorly understood. TEK of Gamay remains a significant knowledge gap. Habitat restoration has shown promising results and could provide opportunities to improve affected habitats in the future. Conclusion and implications This review highlights the extensive amount of knowledge that exists for Gamay, but also identifies key gaps that need to be filled for effective management.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.042
GPT teacher head0.321
Teacher spread0.279 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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