Climate change and harmful benthic microalgae
Bibliographic record
Abstract
Sea surface temperatures in the world's oceans are projected to warm by 0.4-1.4 °C by mid twenty-first century causing many tropical and sub-tropical harmful dinoflagellate genera like Gambierdiscus, Fukuyoa and Ostreopsis (benthic harmful algal bloom species, BHABs) to exhibit higher growth rates over much of their current geographic range, resulting in higher population densities. The primary exception to this trend will be in the tropics where temperatures exceed species-specific upper thermal tolerances (30-31 °C) beyond which growth slows significantly. As surface waters warm, migration to deeper habitats is expected to provide refuge. Range extensions of several degrees of latitude also are anticipated, but only where species-specific habitat requirements can be met (e.g., temperature, suitable substrate, low turbulence, light, salinity, pH). The current understanding of habitat requirements that determine species distributions are reviewed to provide fuller understanding of how individual species will respond to climate change from the present to 2055 while addressing the paucity of information on environmental factors controlling small-scale distribution in localized habitats. Based on the available information, we hypothesized how complex environmental interactions can influence abundance and potential range extensions of BHAB species in different biogeographic regions and identify sentinel sites appropriate for long-term monitoring programs to detect range extensions and reduce human health risks.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".