Progress In Assessing Good Environmental Status In Deep-Sea Benthic Ecosystems: D1, D3, D6 And D10
Bibliographic record
Abstract
ATLAS work package 3 presentation at ATLAS 3rd General Assembly The assessment of Good Environmental Status (GES) is a cornerstone in the Marine Strategy Framework Directive (MSFD). In May 2017 a new commission decision was published (COMMISSION DECISION (EU) 2017/848 of 17 May 2017 that laid down criteria and methodological standards on GES of marine waters and specifications along with standardised methods for monitoring and assessment, repealing Decision 2010/477/EU). To explore how better to assess GES in the deep-sea is an important aspect tackled within ATLAS (WP3) and substantial progress has been made over the last year in developing indicators and thresholds to assess GES in the ATLAS Case Studies (including areas beyond national jurisdictions). GES assessment within ATLAS focuses on four out of eleven descriptors (D) included in the MSFD: D1 (Biological diversity is maintained. The quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climatic conditions), D3 (Populations of all commercially exploited fish and shellfish are within safe biological limits, exhibiting a population age and size distribution that is indicative of a healthy stock), D6 (Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected) and D10 (Properties and quantities of marine litter do not cause harm to the coastal and marine environment). The first step taken in assessing GES in the deep-sea was the selection of suitable GES indicators already included in the NEAT (Nested Environmental status Assessment Tool) Data Base generated in the EU project DEVOTES (http://www.devotes-project.eu/neat/); the second step was the addition of specific GES indicators for deep-sea ecosystems; the third step, that is currently ongoing, is the establishment of threshold values for the selected indicators. This is based on a comprehensive review of the scientific literature (more than 290 papers have been included already in a database) that has been carried out in order to extract quantitative information for the deep-sea benthic habitats and ecosystems to have a basis for the threshold selection. Next steps will be to apply the methodology described to selected ATLAS case studies, namely by assessing GES using the new data collected and the NEAT approach.
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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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".