Grenadier abundance examined at varying spatial scales in deep waters off Newfoundland, Canada, with special focus on the influence of corals
Bibliographic record
Abstract
There is a growing body of research examining the effects of corals on fish communities, species abundances, and biodiversity. Yet, few studies have quantitatively examined what factors are influencing the distribution of individual fish species. In general, many researchers believe they know what influences the distribution of grenadiers on large spatial scales, but numerous studies have shown the distributions of organisms are often determined by various factors that change in relative importance when viewed at differing scales. Our study used video collected from three deep canyons off Newfoundland, Canada (North west Atlantic) to examine how the factors apparently influencing the distribution of four grenadiers (Macrouridae: Coryphaenoides rupestris, Coryphaenoides carapinus, Nezumia bairdii , and Macrourus berglax ) change when assessed at varying spatial scales. We paid special attention to the influence of deep-water corals found in the study area (large gorgonians/antipatharians, small gorgonians, sea pens, soft corals, and cup corals). The factors that influenced grenadier presence and/or abundance (and the magnitude of this effect) varied as different sampling resolutions were examined. We found C. rupestris abundance was positively related to cup coral abundance in transects longer than 10 m, likely as a result of similar habitat preferences between both taxa. When significant relationships between depth and C. rupestris presence and/or abundance were found, they were always negative. Depth was a significant predictor of C. carapinus abundance in transects longer than 10 m. Very few predictors of M. berglax abundance or presence could be found. Depth and the number of small gorgonians were consistent predictors of N. bairdii abundance.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".