Density Responses of Subarctic Coastal Marine Fish and Crabs to Artificial Reefs
Bibliographic record
Abstract
Abstract Structurally complex habitats provide refuge from predators and higher invertebrate prey density—and therefore have higher densities of young fish—than do noncomplex (or barren) sea floors. Artificial reefs are used worldwide to increase seabed complexity in an attempt to increase fish and invertebrate densities and biomass. We employed small‐scale tetrahedral reefs to test three hypotheses: (1) that increased habitat complexity increases the density of individual demersal and epibenthic fish and crab species; (2) that association of affected species will be stronger during the day than at night; and (3) that the density of affected species will attenuate with distance from reefs. We deployed reefs with transects in Newman Sound, Newfoundland, Canada. Each reef transect was paired with a control transect and additional distant control transects along the 15‐m isobath. We estimated the densities of prevalent fish and crab species by means of scuba diving during the autumn of 1999 and summer of 2000. We observed a total of 722 fish and 362 crabs during this study. The densities of cunners Tautogolabrus adspersus in both years and winter flounder Pseudopleuronectes americanus and toad crabs Hyas araneus in 1999 significantly increased near artificial reefs during the day. Atlantic cod Gadus morhua and Greenland cod G. ogac showed some association with artificial reefs but not significantly so due to low daytime observations. For those species that showed an association with reefs, densities attenuated to baseline levels within 20 m from the reefs. None of the species examined were significantly associated with artificial reefs during the night. Yellowtail flounder Limanda ferruginea and rock crabs Cancer irroratus did not associate with reefs at any time.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".