Ecosystem‐Based Fisheries Management for Social–Ecological Systems: Renewing the Focus in the United States with <i>Next Generation</i> Fishery Ecosystem Plans
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
Abstract Resource managers and policy makers have long recognized the importance of considering fisheries in the context of ecosystems; yet, movement towards widespread Ecosystem‐based Fisheries Management (EBFM) has been slow. A conceptual reframing of fisheries management is occurring globally, which envisions fisheries as systems with interacting biophysical and human subsystems. This broader view, along with a process for decision making, can facilitate implementation of EBFM. A pathway to achieve these broadened objectives of EBFM in the United States is a Fishery Ecosystem Plan (FEP). The first generation of FEPs was conceived in the late 1990s as voluntary guidance documents that Regional Fishery Management Councils could adopt to develop and guide their ecosystem‐based fisheries management decisions, but few of these FEPs took concrete steps to implement EBFM. Here, we emphasize the need for a new generation of FEPs that provide practical mechanisms for putting EBFM into practice in the United States. We argue that next‐generation FEPs can balance environmental, economic, and social objectives—the triple bottom line—to improve long‐term planning for fishery systems.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it