Temporal change in the molluscan assemblages (bivalves and gastropods) of Frobisher Bay, Nunavut, Canada, over 50 years
Bibliographic record
Abstract
Long-term studies provide an effective way to assess the ecological impacts of decades-long environmental change in Arctic coastal benthic environments, but are rarely undertaken in the Canadian Arctic. In light of this, historical datasets can be compared with modern samples to examine temporal differences in benthic community structure. Frobisher Bay, Nunavut, provides a unique opportunity to use a historical census to examine the impacts that long-term environmental changes have had on the marine benthos. Between 1967 and 1976, and in 2016, infaunal samples were collected in inner Frobisher Bay and were compared to determine how the molluscan assemblages have changed between the two time periods. Molluscan assemblages in two regions of inner Frobisher Bay (Iqaluit and Cairn Island) were examined to minimize sampling discrepancies between the two time periods. A long-term increase in mean annual air temperature and a decline in the length of the ice cover season were observed. Both regions exhibited some change in sediment composition and quality as well as in molluscan assemblage between the two time periods, and species diversity indices also indicated some change between these time periods. Both the 1967–1976 and 2016 molluscan datasets provide a baseline for future long-term studies in a changing Arctic.
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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 | 0.001 | 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".