Components of Science-based Framework for Assessing the Impact of Development Activities under Section 73 of Canada’s Species at Risk Act
Bibliographic record
Abstract
Under Section 73(3) of Canada’s Species at Risk Act, the competent minister may not authorize an activity that jeopardizes the survival or recovery of a SARA-listed species. Since 2004, the concept of jeopardizing survival and recovery has received considerable attention from DFO’s Science Sector in the form of allowable harm advice; however, allowable harm is a species, not project-specific concept, and to date has not typically incorporated habitat effects, which are expected with development projects in and around aquatic ecosystems. Here, an overview of allowable harm advice is presented as it relates to interpreting Section 73(3). Components of a science-based framework to assess the impact of development activities under Section 73(3) are then presented. The three components are: 1) the ability to relate individual projects to changes in habitat condition; 2) relationships between habitat condition and species vital rates, including considerations for behavioural and sub-lethal effects; and, 3) the relationship between population growth rate and vital rates, explored through elasticity analysis for 143 COSEWIC-assessed species (fishes, freshwater mussels, marine mammals, marine turtles) across five population states (crashing, declining, stable, growing, booming). These components are combined to estimate changes to a species’ population growth rate resulting from a single development activity, and thus also provide an accounting framework to evaluate harm from all activities in a permitting period. The components will require future work to inform taxa-specific functional responses, especially concerning relationships between habitat and vital rates, and sub-lethal effects. Further work is also required to determine the ability to achieve measurable gains in vital rates and populations through offsetting measures, if applied. If adopted into a decision support tool, this body of work would ensure that project decisions around Section 73(3) can be made in a rigorous, transparent, and nationally consistent manner.
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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 | 0.025 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.024 | 0.013 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".