Science Response : Science review of standardized monitoring and success criteria reports
Bibliographic record
Abstract
In 2011, Fisheries and Oceans Canada (DFO) Fish and Fish Habitat Protection Program (FFHPP) requested science advice on developing cost-effective and science-based monitoring programs as part of habitat offsetting plans, to determine the effectiveness of habitat offsetting projects. Three hierarchical levels of monitoring were briefly described (compliance, functional, and effectiveness monitoring), but for that advice process the focus was on effectiveness monitoring (DFO 2012). The science advice on effectiveness monitoring was deemed applicable to projects with offsetting measures that warrant detailed monitoring (e.g., typically projects expected to have a large impact on fish and fish habitat, or high uncertainty in outcome). A technical report (Smokorowski et al. 2015) was produced following the 2012 advice and focused on developing the design and metrics for comprehensive effectiveness monitoring. In 2018, a follow-up science advisory process was held to focus on ‘functional monitoring’, recognizing that not all projects warrant full-fledged effectiveness monitoring, but that understanding the performance of the constructed habitats requires more than determining if the proponent has complied with conditions set out in an authorization under the Fisheries Act. The resulting Science Advisory Report (DFO 2019a) provided operational guidance on functional monitoring, exploring when it might be appropriate to implement, and providing monitoring design and indicator options to move towards standardization. Since then, there has been no DFO science advisory process to recommend requirements for compliance monitoring. The type of monitoring to be implemented and resulting level of effort depends on the goals/objectives of the monitoring, the scale of the potential impact, the relative understanding of the performance of specific types of constructed habitats, and corresponding indicators or surrogate metrics chosen. While science advice exists for the selection of monitoring approaches and design, none of the products from these past Canadian Science Advisory Secretariat (CSAS) processes were prescriptive enough to provide specific guidelines (i.e., step-by-step instructions) to implement an effective, standardized monitoring program. Currently, FFHPP Ontario and Prairie Region (O&P Region) does not have standardized monitoring protocols and no standardized physical, chemical, or biotic collection techniques for both proponents and DFO to use in monitoring most habitat offsets. Recently, DFO FFHPP O&P Region contracted the development of proposed standardized monitoring approaches for several types of offsets or restorations, including lake construction, restoration/relocation/construction of watercourses to enhance or construct fish habitat (channel construction), aquatic habitat works which modify watercourses and lakes to enhance or construct fish habitat. Also included were supporting physical, chemical, and biotic collection techniques. These contracts followed-up from previous monitoring-related CSAS processes to specifically produce standardized monitoring protocols. Prior to incorporating these protocols into operational activities, DFO FFHPP had requested DFO Science review them and provide advice on the contractor-proposed, standardized monitoring programs/approaches for the aforementioned offset activities. All standardized monitoring programs/approaches are proposed for application in freshwaters, but inclusion of marine versions of similar protocols could be considered for future work. The objective of this review was to assess whether the proposed standardized monitoring approaches for lake construction, channel construction, aquatic habitat works, and supporting biota collection techniques are scientifically sound, to help FFHPP build consistency in their monitoring and data requirements for their program and proponents. More specifically, the objectives were to: 1. Assess the quality and adequacy of information presented so that it is in line with previous advice, and determine if any relevant information was missing in the approaches; 2. Determine if appropriate study design, indicators and metrics, methods, sampling intensity, and best scientific practices in monitoring were used; 3. Determine if the monitoring approaches, including study design, data collection, metrics, and data accessibility, were structured in a manner for DFO Science to conduct a meta-analysis of the results in the future so monitoring protocols can be reassessed and to evaluate the ‘success’ of constructed habitats, and; 4. If necessary, recommend additional or alternative monitoring measures and approaches. This Science Response Report results from the regional peer review of November 21-24, 2022, on the Science Review of a Standardized Monitoring and Success Criteria Report for Lake Construction; Channel Creation and Aquatic Habitat Works.
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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 | 0.257 | 0.631 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.036 | 0.026 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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".