Recovery Potential Assessment for Fraser River Sockeye Salmon (Oncorhynchus nerka), Nine Designatable Units Part 2 : Biology, Habitat, Threats, Mitigations and Allowable Harm - Elements 1-11, 14, 16-18, 22
Bibliographic record
Abstract
Nine Fraser River Sockeye Salmon Designatable Units (DUs) were assessed as Threatened or Endangered by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC; 2017), and are currently under consideration for addition to Schedule 1 of the Species at Risk Act (SARA). This document is the second of two parts for the Recovery Potential Assessment (RPA) for these DUs. The first part of the RPA involved quantitative analysis of abundance data and generation of recovery targets, and estimating the probability of achieving these recovery targets under a range of modelled productivities and rates of en route mortality. This second part of the RPA provides an overview of biology and habitat requirements, an assessment of threats and factors potentially limiting recovery, an inventory of potential mitigation activities to increase survival and/or productivity, and a final discussion surrounding allowable harm. The major threats impacting these DUs were assessed in a multi-day workshop, held October 27th to 29th, 2020, with a range of subject-matter experts, and were identified to be climate change, geological events, natural systems modifications, fishing, pollution, and hatchery competition. These threats were subsequently reviewed during this peer-review process and revised according to group consensus. All nine DUs are faced with a unique and complex suite of threats and limiting factors depending on their geographic location, yet all DUs range from a High to Extreme level of threat risk. Based on the threats assessment, over the next three generations (2021-2032) it is expected that there will be a population level decline of 31-70% (High Risk) for DU10 Harrison (U/S)-L, DU16 Quesnel-S, DU21 Takla-Trembleur-S, and DU24 Widgeon-RT; a population level decline of 31-100% (High-Extreme Risk) for DU2 Bowron-ES, DU14 North Barriere-ES, DU17 Seton-L, DU22 Taseko-ES; and population level decline of 71% to 100% (Extreme Risk) for DU20 Takla-Trembleur-EStu. Alleviating the numerous and complex threats to these DUs will be difficult, especially as many of the threats are exacerbated by climate change. It will be critical to ensure that efforts are appropriately coordinated through effective governance to successfully mitigate the cumulative impacts of these diverse threats. Given the information presented in this RPA (Part 1 & 2), it is apparent that all sources of anthropogenic harm should be minimized to give these populations a chance to rebuild. It is our recommendation that the only activities allowed that cause mortality are those that are in support of the recovery, and in some cases survival of the DUs (i.e. DU20 Takla-Trembleur EStu, DU2 Bowron-ES), and all sources of anthropogenic harm should be reduced to the maximum extent possible.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".