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Record W2288913696

Freshwater fisheries ecology

2016· book· en· W2288913696 on OpenAlexaboutno aff
John F. Craig

Bibliographic record

VenueWiley eBooks · 2016
Typebook
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFisheries managementFisheryFreshwater fishGeographyFreshwater ecosystemOverexploitationEcologyEcosystemBiologyFish <Actinopterygii>Fishing
DOInot available

Abstract

fetched live from OpenAlex

Preface List of contributors Acknowledgements Section 1. Freshwater Fisheries Ecology 1.1. Introduction J. F Craig Section 2. Freshwater ecosystems 2.1. Introduction J. F. Craig 2.2. The dynamics of rivers in relation to fishes and fisheries G. Petts, M.-P. Gosselin and J. Gray 2.3. The dynamics of lakes in relation to fishes and fisheries B. Moss 2.4. The physico-chemical characteristics, biota and fisheries of estuaries I.C. Potter, R.M. Warwick, N.G. Hall and J.R. Tweedley Section 3. Freshwater resources 3.1. Introduction J. F. Craig 3.2. Northern North America W. Tonn, H. Swanson, C. Paszkowski, J. Hanisch and L. Chavarie 3.3. Fennoscandian freshwater fishes: diversity, use, threats and management B. Jonsson and N. Jonsson 3.4. Fishery and freshwater ecosystems of Russia: status, trends, research, management and priorities Y. Yu. Dgebuadze 3.5. Fishery of the Laurentian Great Lakes T. E. Lauer 3.6. Canadian freshwater fishes, fisheries and their management, south of 60 N J. R. Post, N. Mandrak and M. Burridge 3.7. Freshwater fisheries of the United States T. E. Lauer and M. Pyron 3.8. Fisheries in the densely populated landscapes of western Europe I. J Winfield and D. Gerdeaux 3.9. Freshwater resources and fisheries in Slovakia A. Novomeska and V. Kovae 3.10. Freshwater resources and fisheries in Hungary A. Specziar and T. Eros 3.11. Freshwater resources and fisheries in the Czech Republic P. Horky 3.12. Problems and challenges of fish stock management in fresh waters of Poland Z. Kaczkowski and J. Grabowska 3.13. Nature and status of freshwater fisheries in Belarus V. Semenchenko, V. Rizevski and I. Ermolaeva 3.14. Current state of freshwater fisheries in China Y. Zhao, R. E. Gozlan and C. Zhang 3.15. Japanese inland fisheries and aquaculture: status and trends O. Katano, H. Hakoyama and S.-i. S. Matsuzaki 3.16. Fisheries in subtropical and temperate regions of Africa O. L.F. Weyl and P. D. Cowley 3.17. Freshwater fisheries resources in subtropical America R. Miranda 3.18. Iberian inland fisheries C. Antunes, F. Cobo and M. J. Araujo 3.19. Nature and status of freshwater and estuarine fisheries in Italy and western Balkans P. G. O. Bianco and V. Ketmaier 3.20. Fisheries ecology of Greece I. D. Leonardos 3.21. The ecology of inland fisheries of Turkey S. V. Yerli 3.22. Fishery ecology in South American river basins M. Barletta, V. E. Cussac, A. A. Agostinho, C. Baigun, E. K. Okada, A. Cattella, N. F. Fontoura, P. S. Pompeu, L. F. Jimenez-Segura, V. S. Batista, C. A. Lasso, D. Taphorn and N. N. Fabre 3.23. Inland fisheries of tropical Africa B. E. Marshall 3.24. Fisheries of the rivers of south-east Asia R. L. Welcomme, I. G. Baird, D. Dudgeon, A. Halls, D. Lamberts and Md G. Mustafa 3.25. Asian upland fishes and fisheries A. I. Payne 3.26. Fishes and fisheries of Asian inland lacustrine waters U. S. Amarasinghe and S. S. De Silva 3.27. Freshwater fisheries of Australasia D. J. Jellyman, P. C. Gehrke and J. H. Harris Section 4. Fishing operations 4.1. Introduction J.F. Craig 4.2. Aboriginal freshwater fisheries as resilient social-ecological systems M. E. Lam 4.3. Commercial inland capture fisheries D. M. Bartley, G. de Graaf and J. Valbo-Jorgensen 4.4. Recreational fisheries in inland waters S. J. Cooke, R. Arlinghaus, B. M. Johnson and I. G. Cowx Section 5. Fisheries management 5.1. Fisheries governance and management R. Welcomme 5.2. Assessment and modelling in freshwater fisheries T. J. Pitcher 5.3. Social benefits from inland fisheries: implications for a people-centred response to management and governance challenges R. Arthur, R. Friend and C. Bene 5.4. A human rights-based approach to securing livelihoods depending on inland fisheries N. Franz, C. Fuentevilla, L. Westlund and R. Willmann 5.5. The optimal fishing pattern J. Kolding, R. Law, M. Plank, P. A. M. van Zwieten Section 6. Fisheries development 6.1. Introduction J. F. Craig 6.2. Environmental assessment for fisheries N. Milner 6.3. Management of freshwater fisheries: addressing habitat, people and fishes R. Arlinghaus, K. Lorenzen, B. M. Johnson, S. J. Cooke and I. G. Cowx 6.4. Aquaculture M. C. M. Beveridge and R. E. Brummett 6.5. Ecological implications of genetically modified (GM) fishes in freshwater fisheries, with a focus on salmonids L. F. Sundstrom and R. H. Devlin 6.6. Sustainable freshwater fisheries: the search for workable solutions R. E. Gozlan and J. R. Britton Section 7. The effects of perturbations on fisheries 7.1. Introduction J. F. Craig 7.2. Harvest-induced phenotypic change in inland fisheries L. J. Chapman and D. M.T. Sharpe 7.3. Climate change and freshwater fisheries C. Harrod 7.4. Toxicology N. Bury 7.5. Impoundments, barriers, and abstractions: impact on fishes and fisheries, mitigation, and future directions P. S. Kemp 7.6. Role and impact of non-native species on inland fisheries: the Janus syndrome R. E. Gozlan 7.7. Eutrophication and freshwater fisheries I. J. Winfield 7.8. Aquaculture and the environment M. C. M. Beveridge and R. E. Brummett Section 8. Tools and future developments in freshwater fisheries 8.1. Introduction J. F. Craig 8.2. A list of suggested research areas in freshwater fisheries ecology J. F. Craig 8.3. Molecular ecology and stock identification E. A. S. Adamson and D. A. Hurwood 8.4. Recruitment T.A. Johnston , N.P. Lester and B.J. Shuter Subject index Country index Fish species index Author index

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.391
Threshold uncertainty score0.868

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3910.138

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 head0.008
GPT teacher head0.187
Teacher spread0.178 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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