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Record W7133286028

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

2023· other· en· W7133286028 on OpenAlexaboutno aff
Daniel Doutaz, Ann-Marie Huang, Scott Decker, Tanya Vivian

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsThreatened speciesEndangered speciesLimitingPopulationWildlifeHarmHabitat
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.020
GPT teacher head0.274
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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