Local Values and Data Empower Culturally Guided Ecosystem-Based Fisheries Management of the Wuikinuxv Bear–Salmon–Human System
Bibliographic record
Abstract
Abstract Despite numerous examples of ecosystem-based fisheries management (EBFM) addressing tradeoffs between ecological and commercial fishery interests, local social and cultural concerns are less frequently considered. We illustrate how Indigenous fishery harvest goals and data from locally driven wildlife research can inform EBFM, guided by cultural values of respect for and reciprocity with wildlife. Grizzly bears Ursus arctos horribilis hold particular importance for the Wuikinuxv First Nation in Rivers Inlet, British Columbia, where people and bears have coexisted as consumers of Sockeye Salmon Oncorhynchus nerka for millennia. The region’s valuable commercial fishery, active since the late 1800s, has been closed since the Sockeye Salmon population collapsed in the mid-1990s, but the Wuikinuxv maintain a modest food, social, and ceremonial (FSC) harvest. To address questions about balancing the needs of fishers and ecosystem recipients, we quantified tradeoffs between long-term maximum sustainable fishery yield and ecosystem benefits (for which bear density served as a proxy). We fitted age-structured state-space spawner–recruitment models and estimated relationships among spawner abundance, long-term fishery yields, and relative bear densities in time periods before and after the population collapse. We found that predicted maximum postcollapse bear density was 74% of maximum precollapse densities. We estimated a 94% decline in Sockeye Salmon equilibrium population size (from ˜3,115,000 to 200,000), resulting in a commensurate decline in maximum sustainable fishery yield. Despite this, we showed that Wuikinuxv FSC harvest goals are compatible with an EBFM target that seeks also to sustain relatively high bear densities, whereby relative fishery yield and bear density are reduced about 10% from their respective maxima, assuming that current Sockeye Salmon productivity and carrying capacity remain similar for the foreseeable future, although these estimates are highly uncertain. Collectively, our findings illustrate how EBFM can apply interdisciplinary approaches that draw not only on fisheries ecology but also local values to design sustainable harvest strategies for diverse beneficiaries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".