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Record W7133287297

Assessing cumulative effects in support of policy development and regulatory decision-making

2022· other· en· W7133287297 on OpenAlexfundaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersFisheries and Oceans CanadaCanadian Wildlife FederationOntario Ministry of Natural Resources and ForestryUniversity of MinnesotaIndigenous and Northern Affairs CanadaMinistry of Natural Resources
KeywordsProcess (computing)Cumulative effectsFish <Actinopterygii>Plan (archaeology)Fish habitatSet (abstract data type)HabitatEcosystem management
DOInot available

Abstract

fetched live from OpenAlex

Consideration of Cumulative Effects (CE) requires an ecosystem-level perspective including knowledge of ecosystem integrity (composition, structure, and function), this advice should be interpreted in this context. How CE considerations fit into the Fish and Fish Habitat Protection Program’s (FFHPP) management cycle was reviewed with respect to two specific areas: 1) integrated planning and 2) fish and fish habitat decision-making, in addition this advisory meeting focused on freshwater ecosystems. IP should inform FFHPP decision-making and vice versa. This is essential to the consideration of CE by ensuring structured information flow between IP (e.g., state, thresholds, the conservation, protection, and restoration needs of systems, etc.) and changes to FFHPP decision-making depending on that state. Information from FFHPP to IP helps capture vital information on activities and cumulative effects and residual pressures. Integrated planning is generally considered a policy driven process to establish objectives that may include ecosystem, cultural, social, and economic components, DFO Science focus was on the ecosystem components required. The information requirements should be informed by the best available knowledge that includes a solid understanding of the status of fish and fish habitat in the area under consideration. CE considerations need assessment of past pressures (included in the status of above) as well as an assessment of the potential effects of current and foreseeable pressures on the fish and fish habitat. One of the main ways to consider CE in an Integrated Plan is to set objectives and targets that consider the relationships among fish, people, and the environment. These goals and targets can be policy based but should be measurable and based on the best available information. Objectives and targets of an IP should include agreed upon indicators with defined thresholds or ranges. Thresholds and ranges can be directly measured and could also be determined by modelling and scenario planning, or be based on Indigenous knowledge of relationships and natural conditions. Indicators should be specific, measurable, attainable, relevant, and time-based (SMART) as well as sensitive and responsive to anticipated management measures, in order to provide timely feedback such that management measures can be tested for effectiveness. CE within fish and fish habitat decision-making requires information about: (1) the proposed Work, Undertaking or Activity (WUA), (2) the species in the region, and (3) the habitats in the region. Specifically, there needs to be a clear determination of the ’zone of influence’ related to the WUA both from a spatial and temporal perspective. The expected pressures from the WUA needs to be understood and the current status of the habitat needs to be evaluated. Information on reference conditions (near pristine or prior to previous impacts) are important to document as accurately and comprehensively (e.g., broad spatial-temporal scales) as possible to predict the vulnerability of the fish and fish habitat to CE. Information on the species should include: presence/absence, life history characteristics/needs, general population status and sensitivity to the expected pressures for all species in the ‘zone of influence’. A trait based approach to consistently determine the expected presence of species in the ‘zone of influence’ was presented for data limited situations, it could also be used as a check in more data rich areas. Existing scientifically defensible methods (e.g., Habitat Ecosystem Assessment Tool-HEAT) and/or equivalency models can provide a means of determining the species within the ‘zone of influence’ and effects of proposed WUAs on habitat. Habitat information should include: the habitats present, the general habitat status and an evaluation of the habitat vulnerability (sensitivity and exposure) to the expected pressures within the ‘zone of influence’. Habitat sensitivity is defined based on a combination of resilience and resistance to a particular pressure and is separate from the exposure of the habitat to the pressure from a proposed WUA. In a CE context, current habitat sensitivity is influenced by exposure to previous pressures in the watershed, as sensitivity is an intrinsic property of the ecosystem that may vary depending on the habitat status. Outside of management and operational uncertainties regarding the WUA and the effectiveness of the measures (SAR 2014/015), it is understood that habitat and fish distributions are dynamic and can/will change due to natural and anthropogenic forces, this is one of the reasons a broader spatial and temporal scope is required for the consideration of CE. The knowledge and uncertainty associated with the impacts of activities on species and habitats are complicated in considerations of CE because of interactions between pressures (additive, antagonistic, and synergistic), non-linearities, thresholds and tipping points, on top of existing challenges of accurate measurement in ecological settings. A standardized approach to better understand the state of fish and fish habitat within the context of natural and anthropogenic spatial-temporal variation of the ecosystem is required to inform project reviews. This approach/database would ideally track projects across Canada as one means to measure the pressure footprint within watersheds resulting from anthropogenic activities. There is a need for a national geospatial database with available information on species, habitats, and the CE landscape so assessors can evaluate if the information they have is correct and sufficient. While this database may not contain all the needed information, it would provide a centralized access point that could allow planners, assessors, scientists and proponents to be working from shared resources.

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)0.211
metaresearch head score (Gemma)0.287
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2110.287
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0160.010
Science and technology studies0.0030.006
Scholarly communication0.0180.019
Open science0.0070.010
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.010
GPT teacher head0.281
Teacher spread0.271 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes2
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada→French-language works237,207→