Dispersal limitation and climate-related environmental gradients structure microcrustacean composition in freshwater lakes, Ellesmere Island, Canada
Bibliographic record
Abstract
Dramatic environmental change is expected in the Arctic, yet little is known about the occurrence and community composition of microcrustaceans in Arctic lakes and how this will be influenced by future environmental change. We sampled and calculated relative abundances of microcrustacean species in 54 lakes on Ellesmere Island, Canada. New species records on Ellesmere Island included Daphnia umbra , Tachidius discipes , and Artemeopsis stefanssoni . Daphnia middendorffiana/tenebrosa was the most common taxon and often dominated microcrustacean assemblages, likely a result of its pigmentation, which offers resistance to ultraviolet radiation. Species richness was positively associated with nutrients, dissolved organic carbon (DOC), temperature, calcium, and conductivity and negatively affected by elevation. In contrast to most findings in temperate systems, we detected a negative relationship between species richness and surface area. Community composition was influenced by DOC, nutrients, and elevation but was also related to spatial variables, suggesting that spatial gradients in environmental conditions and dispersal are important drivers of differences among sites. Arctic ecosystems are expected to change rapidly in the coming years because of climate change and ozone thinning, and we expect that associated changes in DOC, temperature, and nutrients will affect microcrustacean species richness and distribution throughout the landscape.
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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 | 0.002 | 0.001 |
| 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".