Effects of trawling disturbances on temporal and spatial structure of benthic soft-sediment assemblages in Gullmarsfjorden, Sweden
Bibliographic record
Abstract
Hypotheses on the effects of shrimp trawling on large benthic macrofauna in a previously protected Swedish fjord were tested in a manipulative experiment.Three trawled sites and three untrawled (control) sites were sampled 1-4 months before, and 8-12 months after, experimental trawling on a weekly basis.Multivariate analyses indicate large temporal changes in assemblages of benthic fauna at both types of sites.The Bray-Curtis dissimilarity measure was used to test the hypothesis that changes in assemblages through time at trawled sites were different from those at untrawled sites.Although changes in average assemblages (centroids) from the start to the end of the experiment were larger at trawled sites, there were marked differences among sites, and differences between trawled and untrawled sites were not significant.There were, however, differences in temporal and spatial variability in structure of benthic assemblages.Variability at untrawled sites tended to be smaller.Thus, spatial and temporal variability in the structure of assemblages after one year of trawling was larger at the trawled sites than at the untrawled sites.Trawling with this particular type of gear at the experimental frequency for approximately one year appears to cause relatively subtle changes in the overall structure of assemblages of large macrofauna compared with changes caused by other factors.Furthermore, the results suggest that tests of hypotheses of changed patterns of variability may be sensitive to detecting effects of impacts of disturbance from trawling.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".