Thirty years of change and the future of Alaskan fisheries: Shifts in fishing participation and diversification in response to environmental, regulatory and economic pressures
Bibliographic record
Abstract
Abstract Heterogeneity in human responses and decision‐making can contribute to the resilience of social–ecological systems in the face of environmental, political and economic pressures. In fishery systems worldwide, the ability of harvesters to maintain a diverse portfolio of fishing strategies is important for building adaptive capacity. We used a case‐study approach to examine the complexity of factors that inhibit or promote diversification in fisheries of Alaska, one of the major fishing regions of the world. Through a combination of harvest records and literature review, we explored shifts in participation and portfolio diversity in Alaskan fisheries over three decades. The four case‐studies examined the responses of fishers, fleets and communities to multiple, intersecting pressures, including biological declines, market and price dynamics, fishery privatization and the 1989 Exxon Valdez oil spill. These cases illustrate how stressors acting at multiple scales can encourage or constrain opportunities for diversification, and that these opportunities may be spread inequitably across participants. Overall, we found evidence for reduced participation and increasing specialization in Alaskan commercial fisheries. While numerous factors explain these trends, policies like individual quota systems and the increasing cost of entry into fisheries are forcing consolidation at local to regional scales. A portfolio approach to managing fisheries that reduces barriers to diversification and includes broad representation of resource users and communities in management may help to maintain opportunity and choice for fishers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".