Same Space, Different Standards: A Review of Cumulative Effects Assessment Practice for Marine Mammals
Bibliographic record
Abstract
Marine mammals are vulnerable to a variety of acute and chronic anthropogenic stressors, potentially experiencing these in isolation, successively and/or simultaneously. Formal assessment of the likely impact(s) of the cumulative effects of multiple stressors on a defined population is carried out through a Cumulative Effects Assessment (CEA), which is a mandatory component of the Environmental Impact Assessment (EIA) process in many countries. However, for marine mammals, the information required to feed into CEA, such as thresholds for disturbance, frequency of multiple (and simultaneous) exposures, interactions between stressors, and individual variation in response, is extremely limited, though our understanding is slowly improving. The gaps in knowledge make it challenging to effectively quantify and subsequently assess the risk of individual and population consequences of multiple disturbances in the form of a CEA. To assess the current state of practice for assessing cumulative effects on marine mammals within UK waters, 93 CEAs were reviewed across eleven maritime industries. An objective framework of thirteen evaluative criteria was used to score each assessment on a scale of 13-52 (weak - strong). Scores varied significantly by industry. On average, the aquaculture industry produced the lowest scoring CEAs, whilst the large offshore windfarm industry (≥ 20 turbines) scored highest, according to the scoring criteria used. There was a significant increase in scores over the sample period (2009-2019), though this was mostly attributed to five industries (cable, large and small offshore wind farms, tidal and wave energy). There was inconsistency in the language used to define and describe cumulative effects and a lack of routinely applied methodology. We use the findings presented here, along with a wider review of the literature, to provide recommendations and discussion points aimed at supporting the standardisation and improvement of CEA practice. Although this research focused on how marine mammals were considered within UK CEAs, recommendations made are broadly applicable to assessments conducted for other receptors, countries and/or environments. Adoption of these proposals would help to ensure a more consistent approach, and would aid decision-makers and practitioners in mitigating any potential impacts, to ensure conservation objectives of marine mammal populations are not compromised.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".