<i>Didymosphenia</i> <i>geminata</i> in two Alberta headwater rivers: an emerging invasive species that challenges conventional views on algal bloom development
Bibliographic record
Abstract
The diatom Didymosphenia geminata (Bacillariophyceae) has garnered increased attention as a nuisance and invasive species in freshwater systems. Historically described as rare yet cosmopolitan, a suspected new variant of D. geminata has the capacity to inundate kilometres of river bottom during a bloom. Unlike most other bloom-forming algae, D. geminata proliferates under high water quality (i.e., low turbidity and low nutrient) conditions. To inform management strategies, the environmental factors and conditions that promote bloom events must be ascertained. Our study of the Bow and Red Deer rivers in southern Alberta, Canada, provides supporting evidence that the mean flow regime is associated with bloom development, based on a significant negative relationship detected between D. geminata biomass and mean discharge (r 2 = 0.30). While flow regulation by dams can create the stable flow environment preferred by D. geminata, our results indicate that flow regime (rather than just proximity to dam outflows) is the likely mechanism, in addition to other environmental factors, such as water clarity, temperature, pH, conductivity, and total phosphorus. We discuss the formidable challenges to D. geminata management, particularly along unregulated river reaches, yet also recognize the unique research opportunities that this organism poses for the growing field of invasion biology.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".