Science on the use of timing windows as a mitigation measure
Bibliographic record
Abstract
Timing windows refer to a mitigation measure that defines low-risk periods for harm to fish and fish habitat from works, undertaking and activities (WUAs). The Fisheries and Oceans Canada Fish and Fish Habitat Protection Program (FFHPP) has requested scientific advice on the use of timing windows. To address this request, this document is structured around three main objectives outlined in the terms of reference. First, a literature search was conducted, and found that there is a paucity of peer reviewed scientific research connected to timing windows, and that literature on timing windows is dominated by material on dredging activities. An in-depth treatment of rationale, effectiveness, and frameworks for timing windows is provided. Canadian timing window use, rationale, and considerations varies among provinces and territories, but spawning is often cited as the fish life process targeted for protection. Second, a conceptual model outlines a set of rationale and considerations for the creation or modification of timing windows focusing on (1) the timing and vulnerability of fish life processes, (2) the characteristics of WUAs and associated pressures, and (3) the characteristics of habitat and environmental conditions. Importantly, life processes vary in their vulnerability to WUAs, but characteristics such as well-defined and predictable timing were identified among the factors that make some more suitable to mitigation with timing windows than others. Further considerations for migration, spawning, feeding, natal, rearing and refuge use are also presented. Characteristics of WUA pressures, including timing and persistence, were also identified as key factors for timing windows to consider. The interaction of pressures with fish habitat will be influenced by characteristics of the habitat and the environmental context. Protecting habitat processes with timing windows will depend on the process predictability, the mechanisms that regulate the WUA pressure and the habitat process, and the degree of overlap and strength of the pressure during exposure. Finally, we present a three-tiered approach to evaluate the effectiveness of timing windows to reduce the risk of exposure of fish life or habitat processes, the effects of pressures on the exposed process, and risk at the population level. Studies at each tier can inform comparisons of how risk varies through time, which is a key consideration when choosing among timing window options. This document advances the state of knowledge on the use of timing windows and on evaluating their effectiveness. The information presented can be used by FFHPP in the development of a science-based timing window framework to guide their creation and modification, to aid practitioners to identify potential risks of WUAs outside of established windows, and to inform their adaptation to changing environmental conditions.
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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 | 0.037 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".