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Record W4300563348 · doi:10.47886/9781934874110.ch31

Pacific Salmon: Ecology and Management of Western Alaska’s Populations

2009· book-chapter· en· W4300563348 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2009
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFisherySubsistence agricultureFisheries managementOncorhynchusEscapementGeographyStock (firearms)Fish stockFish <Actinopterygii>FishingBiologyAgricultureArchaeology

Abstract

fetched live from OpenAlex

&lt;em&gt;Abstract.&lt;/em&gt;—The most abundant salmon of the Yukon River is chum salmon &lt;em&gt;Oncorhynchus keta, &lt;/em&gt;which make annual spawning runs from the Bering Sea up the Yukon River, traversing more than 1300 river miles across Alaska into Yukon Territory in Canada. Genetically distinct summer and fall runs exist and these runs are differentiated into stocks by timing of migration and by spawning river. The fall-run stocks are harvested from mid-July through early October and most Yukon River fisheries occur on a mixture of populations or stocks. This paper provides descriptions of fall chum salmon life history, the Yukon River fishery and its management, changes in stock abundance over time, and harvest. Six fisheries occur for fall-run chum salmon: subsistence, personal use, aboriginal, domestic, sport, and commercial. Subsistence fisheries in Alaska are comparable to aboriginal fisheries in Canada, as are personal use, sport, and domestic fisheries. The fisheries use a variety of gear including gillnets and fish wheels. Jurisdictionally, management requires cooperation among state, federal, and international organizations during both the ocean and river phases of the salmon life history. The goal of management is to regulate the harvest of commercial and traditional-use fisheries to provide an adequate number of fish for spawning (escapement) to ensure the reproduction of the next generation, and to sustain Alaskan and Canadian fisheries. Subsistence and aboriginal fisheries have priority over other fisheries in allocation of harvest. Regulations are used to control how many fish are caught through restrictions on effort, fishing efficiency, and the scheduling of where, when, and how long fishery openings will be allowed. Over the period 1974–2008, the largest runs of fall chum salmon occurred in 1975, 1995, and 2005 (&gt; 1.47 million fish) and smallest runs occurred in 1999, 2000, and 2001 &lt; 334,000 fish). Odd-year runs tend to be larger than even-year runs. The run failures of 1998–2002 were followed by increased run numbers in 2003–2008. Primary variables that influence the total run of fall chum salmon are the spawning success of previous generations, natural variability in marine and freshwater survival due to climatic and oceanographic processes, and fishery harvests in both marine and freshwater. Salmon escapement numbers typically emulated total run estimates. Every river monitored had low estimated escapements from 1998–2002. From 1974–2008, total harvest of fall chum salmon in Alaska (average 291,982 fish) exceeded Canadian harvests (average 20,314 fish) by an order of magnitude. Some lessons learned from management of this fishery are offered that may be applicable to other fisheries: stakeholder involvement is critical to effective harvest management; rapid, effective information sharing is a requirement for fast-paced, in-season decision-making; limited entry alone did not control harvest; and some things that make management difficult just cannot be changed!

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.016
GPT teacher head0.218
Teacher spread0.202 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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