Decision support framework for the conservation translocation of SARA-listed freshwater fishes and mussels
Bibliographic record
Abstract
Conservation translocations are identified in many management plans and recovery strategies as potential tools for improving the survival or recovery of freshwater fish and mussel species listed under the Species at Risk Act (SARA). This document provides a general science-based decision support framework to help inform the potential use of conservation translocations in recovery planning. Conservation translocations include supplementation, reintroduction, mitigation translocation, and assisted colonization. They have been defined here as the act of intentionally moving individuals of a species with the aim of improving survival or recovery of a focal species. Increasing population recruitment, establishing a population, or rescuing a population from immediate extirpation are the three primary mechanisms by which conservation translocations may achieve improved survival or recovery of SARA-listed species. The decision support framework considers the potential ecological benefits to the focal species and the ability to achieve those benefits, relative to the ecological risks to the source and recipient populations of the focal species, as well as broader ecosystem components and processes. The five step decision support framework consists of: Identification of objectives; Assessing the probability of achieving the means and fundamental objectives; Assessing the ecological risks; Compiling and weighing scientific evidence to inform the decision; and, Implementing and monitoring the effects. Conservation translocations can pose ecological risks to the focal species and broader ecosystem components in both the source and recipient habitats that include: The loss of population persistence; Loss or alteration of genetic variation; Changes in community and ecosystem dynamics; and, The potential for transmitting disease. Increased knowledge of population characteristics, species ecology, species habitat requirements and availability, community composition, and potential threats in, or to, the source and recipient locations reduces uncertainty and risk about the outcomes of conservation translocation. The science-based rationale for initiating conservation translocations should be informed by the potential ecological benefits and risks to SARA-listed freshwater fishes and mussels, relative to the risks to other ecosystem components. Given the uncertainties and limited implementation in Canada, when conservation translocations are pursued they should be considered in a long-term experimental context and will require adaptability in implementation and robust monitoring to detect both intended and unintended outcomes, and modify or discontinue the translocation program, if needed. Context-specific protocols that consider the focal species and ecosystems under consideration must be established prior to implementing and monitoring conservation translocations, and remain flexible and adaptable both within the short-term and long-term for the duration of the program. This advice focuses on the ecological considerations for conservation translocations; given the experimental nature of these projects, a socio-economic analysis would also be required before implementation.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".