A meta‐analysis reveals global patterns of sediment effects on marine biodiversity
Bibliographic record
Abstract
Abstract Aim Sediment disturbances are important threats affecting marine biodiversity, but the variety of biological responses has not yet been synthesized. Here, we collate all available information to compare the extent of impacts across different taxonomic groups, habitat types and pathways of impact (light attenuation, suspended sediment and sedimentation). Location Global. Time period Data collected from 1979 to 2017. Major taxa studied Corals, fishes, seagrasses, sponges, macroalgae, ascidians, bryozoans, crustaceans, echinoderms, molluscs and polychaetes. Methods We used meta‐analyses to evaluate the effects of sediments across 842 observations found in 110 publications. We also evaluated some of the biological and methodological factors that could explain the variable effects observed in different studies. Results We found a significant negative effect of sediments on behavioural responses of species, reproduction and recruitment processes, the morphology of organisms, physiology, community abundance and diversity, and species interactions. In contrast, the overall effect on the abundance of individual species was statistically non‐significant and there was a strong positive effect on abundance for sponge and polychaete species. Many individual studies described physiological effects on coral reefs, but the effects on the diversity of soft‐bottom and coral reef communities were particularly detrimental. Phototrophic species were generally more negatively impacted by sediments than heterotrophs, driven by strong physiological responses in crustose coralline algae and seagrasses. Additionally, species with limited mobility were more vulnerable to sediment disturbances than highly mobile species. Sedimentation alone triggered more consistently negative effects on most biological responses than light depletion and suspended sediments. We found evidence for increased impacts on community diversity when more than one pathway of impact was present, indicating that these disturbances can disrupt whole ecosystems. Main conclusions Our meta‐analysis provided, for the first time, strong quantitative support of negative effects of sediments on marine biodiversity. Taxonomic groups, habitat types and life‐history characteristics were most influential in determining the biological responses to sediment disturbances, highlighting the importance of an ecosystem‐based approach when fully accounting for the impacts of sediments.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".