Landscape heterogeneity and the biodiversity of Arctic stream communities: a habitat template analysis
Bibliographic record
Abstract
We predicted that substratum freezing and instability are major determinants of the variability of stream community structure in Arctic Alaska. Their effects were conceptualized as a two-dimensional habitat template that was assessed using a natural experiment based on five stream types (mountain-spring, tundra-spring, tundra, mountain, glacier). Detrended correspondence analysis (DCA) indicated distinct macroinvertebrate assemblages for each stream type. The contribution of functional feeding groups to assemblage biomass varied systematically among stream types, indicating that structure and function are linked. Assemblage position within a DCA biplot was used to assess factors controlling its structure. Springs separated from other stream types along a gradient of nutrient concentration and freezing probability. Glacier and mountain streams separated from springs and tundra streams along a gradient of substratum instability and freezing probability. Owing to differences in sources of discharge to streams, the effects of nutrients and substratum stability could not be separated from freezing. Although many factors likely contribute to the variability of Arctic stream communities, the major determinants may be conceptualized as a template structured by gradients in (i) nutrient supply and substratum freezing and (ii) substratum instability and substratum freezing. This template provides a basis for predicting the response of Arctic stream communities to 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".