Predicted shifts in suitable habitat of interacting benthic species in a warmer and invaded Canadian Arctic
Bibliographic record
Abstract
Climate change and related expanding shipping activity are predicted to increase the risk of aquatic invasive species arriving in the Arctic. The goal of this study was to predict the distribution of an interconnected set of native and non-native primary producers and primary and secondary consumers in this changing context. Groups of species were selected to represent a benthic coastal Arctic food web in Hudson Bay, including kelps and eelgrass as primary producers (Alaria esculenta, Agarum clathratum, Saccharina latissima, Laminaria solidungula, and Zostera marina), amphipods as primary consumers (Gammarus oceanicus and G. setosus), and fish as secondary consumers (sculpins Gymnacanthus tricuspis, Myoxocephalus scorpius, M. scorpioides, and M. quadricornis). Ensemble models were used to predict the distribution of these native and several analogue non-native species (species known to be invasive elsewhere that can be considered analogues to Hudson Bay species): Dumontia contorta, Undaria pinnatifida, Sargassum muticum, and Codium fragile (primary producers); Gammarus tigrinus (primary consumer); and Artediellus atlanticus and A. uncinatus (secondary consumers). Predicted habitat suitability of trophic groups and analogue non-native species were overlaid under current and future climate change scenarios to assess areas of change through time. The predicted direction of potential distribution shifts varies by species identity (species composition) but not trophic group. Overall trophic relationships and roles in the ecosystem are likely to be maintained over time because while some species are predicted to decrease their potential ranges (e.g., M. quadricornis), others in the same trophic groups are predicted to increase (e.g., M. scorpius). Overlap (or lack thereof) between native and analogue non-native species pairs are expected to vary through time enabling novel interactions (e.g., competition) in space and time. This approach will help to identify current and future high-risk areas for trophic level changes and interactions with invasive species in response to global warming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".