Mapping and Characterizing Benthic Habitats in Northern Labrador: Insights for Marine Conservation and Indigenous Resource Management
Bibliographic record
Abstract
In the face of rapid climate change impacting Canada’s northern coastlines, northern fish, benthic ecosystems, and ecosystem services are being heavily impacted. The ongoing environmental pressures continue to influence the social, cultural, and physiological well-being of Labrador Inuit who are intrinsically linked with the marine environment. Collaborating closely with the Nunatsiavut Government, this research presents a detailed map of benthic faunal assemblages in an understudied northern inshore system, providing essential information on benthic habitats and incorporating community-identified fishing locations for ogak (Greenland cod). A total of 75 drop-camera transects unveiled 44,809 organisms belonging to 50 morphotaxa, clustered into three distinct faunal assemblages. Fishing locations were represented in two of three assemblages which were heterogeneous and composed mainly of pebbles, boulders, and rhodolith beds. The unrepresented assemblage was homogeneous and composed entirely of fine sediments. Numerous benthic taxa, potentially sensitive to environmental disturbances, were identified, including tube-dwelling anemones, large sea squirts, erect bryozoans, and extensive rhodolith beds. Insufficient data on benthic species and their associated habitats limit our comprehension of species distributions, abundances, and functional roles in northern waters, creating obstacles for effective self-governance. This research identifies the distribution and structure of benthic habitats in a culturally and economically important region of the Labrador coast, feeding directly into conservation and management strategies of marine habitats under the pressures of climate change in Nunatsiavut.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".