Seabed Habitat Determines Fish and Macroinvertebrate Community Associations in a Subarctic Marine Coastal Nursery
Bibliographic record
Abstract
Abstract Fish exhibit habitat‐specific distributions in heterogeneous landscapes. Many sampling techniques are limited to specific seabed types and have limited utility in comparisons of fish abundance among multiple habitats. We measured the relative abundance and the composition of fish communities in four naturally occurring coastal marine seabed types (sand–pebble, cobble, bedrock, and eelgrass) and one anthropogenic habitat type (wharf) in Newman Sound, Newfoundland, Canada, by using baited video cameras. Fish and macroinvertebrate communities were significantly different among habitat types. Winter Flounder Pseudopleuronectes americanus, Atlantic Cod Gadus morhua, and Shorthorn Sculpin Myoxocephalus scorpius were significantly more abundant over sand–pebble substrate compared with bedrock and wharf sites. Cunners Tautogolabrus adspersus and Greenland Cod Gadus macrocephalus ogac were most abundant at wharf sites. Atlantic rock crabs Cancer irroratus and American lobsters Homarus americanus avoided sand–pebble seabeds, and American lobsters were almost exclusive to bedrock sites. Cunners, Winter Flounder, and Atlantic Cod were more abundant in summer, whereas Greenland Cod and Atlantic rock crabs were more abundant during autumn months. In paired comparisons of eelgrass habitats, the community sampled by two methods was different. Relative abundance estimates from baited video cameras matched beach seine estimates for abundant predatory species (e.g., Cunner, Greenland Cod, and Atlantic rock crab), but other species, including age‐0 Greenland Cod, Shorthorn Sculpin, and White Hake Urophycis tenuis, were better represented in beach seine samples. We demonstrated substrate preferences by common coastal marine fish and crab species, which have proven difficult to enumerate via active sampling techniques in the past. Our findings will facilitate comparative studies for these species among habitat components. For species that are well sampled by using baited video cameras, this technique will advance our ability to plan for their management in the nearshore.
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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 | 0.000 |
| 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".