Ecoregions as predictors of lotic assemblages of blackflies (Diptera: Simuliidae)
Bibliographic record
Abstract
Local ecological attributes of streams are known to have strong influences on community membership for many aquatic insects. Differences in aquatic insect assemblages, therefore, should be clearly detectable across large scale ecological “units”, such as ecoregions. Many studies of aquatic invertebrates however, have suffered from a lack of species level identifications. In addition, many previous studies that examined the influence of ecoregion on aquatic assemblages have the implicit assumption that members of different taxa are responding in the same manner. Our study, therefore, was restricted to an ecologically (lotic) and functionally (mostly filter‐feeding) homogenous group, the Simuliidae. In the current study, we examine the relationship between species assemblages of preimaginal blackflies and the landscape through which their stream habitats flow. Accordingly, the larval simuliid faunas from South Carolina, USA, are compared among three ecoregions established a priori: Blue Ridge Mountains, Piedmont, and Sandhills. Using discriminant function analysis, we show that each ecoregion produces a distinct stream habitat; factors responsible for regionalization are quantified. We also show that streams can be assigned correctly to ecoregion of origin 85% of the time on the basis of the simuliid assemblage. We suggest that our results can be interpreted most readily by considering the distribution of individual species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".