A bioeconomic optimization approach for rebuilding marine communities: British Columbia case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SUMMARY Many marine ecosystems are depleted of living resources as a result of long-term overexploitation. Restoration plans should perhaps consider the entire ecosystem as opposed to single species, yet there is currently no suitable framework available for the design and comparison of whole-ecosystem restoration trajectories. This paper presents a novel addition to Ecopath with Ecosim's policy search routine, the ‘specific biomass’ objective function, which allows gaming scenarios to be run using selective fishing as a tool to rebuild depleted marine ecosystems or modify them into a preferred state. In this paper, restoration scenarios aimed to restore an ecosystem in Northern British Columbia to a state similar to the historic ecosystem of 1950 AD. Restoration plans that achieve restoration quickly tend to require a large sacrifice in fishery profits, while slower plans allow for continued harvest benefits. A convex relationship between profit and recovered biodiversity suggests that there may be an optimal rate of restoration. Cost-benefit analysis demonstrates that conservative restoration plans can offer a rate of return superior to bank interest when viewed as an investment in natural capital. Increasing the selectivity of fishing gear improves the economic outlook.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it