Traditional ecological knowledge and local observations of Capelin (Mallotus villosus) in Darnley Bay, NT
Bibliographic record
Abstract
Capelin are an important fish species in marine habitats because they serve as a prey source for marine mammals, predatory fish, and sea birds in sub-Arctic waters and in parts of the Arctic. In the Beaufort Sea, Capelin are less abundant than in southern waters and have been observed at a limited number of locations, primarily outside of the Mackenzie River Delta. However, warming temperatures and reduction of sea ice are expected to facilitate an increase in presence and abundance of Capelin in the Canadian Arctic. By observing specific locations that have supported multiple spawning events, we can better understand the reproductive ecology of Capelin in a warming Arctic and how their interactions with other species may change in the future. There are few reports in the scientific literature of Capelin in the Canadian Arctic. Recent observations and knowledge of aquatic biota over the long-term, however, are acquired by Indigenous peoples and are usually achieved and transferred orally across generations. This traditional ecological knowledge (TEK) provides a valuable information source that has been minimally documented for Capelin. Additionally, local observations of this species in recent years provide valuable information which can be used to identify ecological change. Capelin have been observed spawning in Darnley Bay, NT for multiple years by community members of Paulatuk, Northwest Territories (NT). The objective of this study is to document historic observations of Capelin made by the community members of Paulatuk and determine: 1) How long capelin have been observed in Darnley Bay; 2) Where in the bay they have been observed; 3) If capelin are present in the diet of subsistence species (i.e., Arctic Char); and, 4) If Capelin were ever harvested for consumption. Environmental information, spawning characteristics, and food web interactions gathered from TEK will extend the current understanding of this species’ ecology and is a tangible example of how local and traditional knowledge can be used to establish baseline distribution and ecology of species in remote locations. Together, TEK and increased scientific knowledge will increase understanding of Capelin biology and allow for predicting shifts in food web dynamics as climate changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".