Macroinvertebrate traits in Arctic streams reveal latitudinal patterns in physiology and habits that are strongly linked to climate
Bibliographic record
Abstract
Introduction Arctic freshwater ecosystems are undergoing rapid environmental transformation because of climate change, which is predicted to produce fundamental alterations in river community structure and function. Methods We explored how climate change affects benthic invertebrate communities of Arctic streams by examining patterns of their biological traits along latitudinal and climatic gradients in eastern North America (Canada) and northwestern Europe (Sweden, Norway). Results Despite differences in taxonomic composition between continents, we identified similarities in the functional trait niche (FTN) of predominant macroinvertebrate taxonomic groups. Trait composition differed by latitude in eastern Canada, with a predominance of cold-tolerant taxa, tubular body shape, and cased and attached habits at the highest latitudes. Differences in trait composition were evident among ecoregions in Europe, with trait dominance at the highest latitudes that was comparable to North America. There was a similar increase in the relative abundance of cold tolerance and tubular body shape and a decrease in obligate shredders and trait richness with decreasing temperatures across both continents. Discussion These patterns are indicative of FTNs that include physiological traits and habits that are advantageous for the low temperatures, short ice-free period, and low riparian vegetation cover at the highest latitudes. We predict that climate change will lead to an increase in functional diversity at high latitudes, as organisms with trait modalities that are currently only found at lower latitudes move northward. However, this change in trait composition will be mediated by the effect of spatial connectivity on dispersal ability, with slower change occurring on Arctic islands. These findings can support modelling of future change in Arctic freshwater assemblages in response to ongoing climate change.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".