Among-taxon congruence in biodiversity patterns: can stream insect diversity be predicted using single taxonomic groups?
Bibliographic record
Abstract
The utility of single taxonomic groups as indicators of biodiversity variation in other taxa has recently gained increasing attention, but such studies on stream organisms are lacking. We studied the diversity patterns of mayflies, stoneflies, caddisflies, and chironomid midges across 110 headwater streams in Finland. Specifically, we examined if species richness and assemblage composition showed similar variation among the taxonomic groups across environmental gradients and if a single taxon could be used as a predictor of diversity in the other groups. Species richness and composition in different taxa exhibited slightly different relationships to environmental gradients, leading to low degrees of concordance. The diversity of mayflies and chironomids showed strongest relationships with stream acidity and water colour, whereas stoneflies and caddisflies exhibited more complex correlations with geographical location and local environmental variables. The overall assemblage composition, however, exhibited significant among-taxon congruence, as shown by Mantel tests. However, even these correlations remained rather low, thus limiting their potential for conservation purposes. Overall, our results do not support the use of single taxonomic groups as indicators of insect biodiversity in headwater stream ecosystems. Alternative approaches for lotic biodiversity assessment (e.g., morphospecies, higher-taxon richness, and environmental diversity) should thus be examined in future studies.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".