Future HAB science: Directions and challenges in a changing climate
Bibliographic record
Abstract
There is increasing concern that accelerating environmental change attributed to human-induced warming of the planet may substantially alter the patterns, distribution and intensity of Harmful Algal Blooms (HABs). Changes in temperature, ocean acidification, precipitation, nutrient stress or availability, and the physical structure of the water column all influence the productivity, composition, and global range of phytoplankton assemblages, but large uncertainty remains about how integration of these climate drivers might shape future HABs. Presented here are the collective deliberations from a symposium on HABs and climate change where the research challenges to understanding potential linkages between HABs and climate were considered, along with new research directions to better define these linkages. In addition to the likely effects of physical (temperature, salinity, stratification, light, changing storm intensity), chemical (nutrients, ocean acidification), and biological (grazer) drivers on microalgae (senso lato), symposium participants explored more broadly the subjects of cyanobacterial HABs, benthic HABs, HAB effects on fisheries, HAB modelling challenges, and the contributions that molecular approaches can bring to HAB studies. There was consensus that alongside traditional research, HAB scientists must set new courses of research and practices to deliver the conceptual and quantitative advances required to forecast future HAB trends. These different practices encompass laboratory and field studies, long-term observational programs, retrospectives, as well as the study of socioeconomic drivers and linkages with aquaculture and fisheries. In anticipation of growing HAB problems, research on potential mitigation strategies should be a priority. It is recommended that a substantial portion of HAB research among laboratories be directed collectively at a small sub-set of HAB species and questions in order to fast-track advances in our understanding. Climate-driven changes in coastal oceanographic and ecological systems are becoming substantial, in some cases exacerbated by localized human activities. That, combined with the slow pace of decreasing global carbon emissions, signals the urgency for HAB scientists to accelerate efforts across disciplines to provide society with the necessary insights regarding future HAB trends.
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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 | 0.026 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".