Freshwater bloom‐forming cyanobacteria and anthropogenic change
Bibliographic record
Abstract
This lecture (∼ 45‐55 slides) will be aimed at senior undergraduate students and graduate students in aquatic sciences with little background in phycology. This lecture could be used in a Aquatic Ecology or Sciences (Limnology) course, an Ecology course, a Phycology course, Environmental Science. Cyanobacteria that may lead to blooms encompass a wide range of different functional groups. We will present: 1) the evolutionary history of cyanobacteria (2‐3 slides) (this helps explain some of their present‐day traits) 2) basic biology and physiological/ecological traits of planktonic cyanobacteria that are most often associated with visible biomass accumulations (“blooms”) in freshwater/brackish systems of various regions of the world. Traits to be considered include: capacity for N fixation, nutrient uptake and storage (C, N, P), siderochromes, buoyancy regulation (gas vacuoles, mucilage), life cycles, growth rates vs. loss rates (resistance to grazing), allelopathy (negative vs. positive biotic interactions) Functional groups. Planktonic genera may also produce toxins, contributing to harmful algal blooms. (∼12‐14 slides). 3) Cyanotoxins: the principal types of toxins produced and their effects (persistence) will be compared, along with theories as to the biological function of these compounds. (∼ 6 slides) 4) Specific case studies of blooms types under different climates: e.g. scum‐forming, metalimnetic, dispersed (∼6) 5) The factors that appear to explain and control cyanobacterial dominance will be presented, including nutrient effects, temperature, and food chain changes. These factors vary across temporal and spatial scales. Evidence for eutrophication and climate change in mediating directly or indirectly the frequency and severity of freshwater cyanobacterial blooms will be considered (∼8‐10). 6) Research avenues Controversial or unresolved topics: e.g. invasiveness?, cosmopolitan or geographically restricted (e.g. endemism? in hot spring taxa), toxin concerns and bioaccumulation), nitrogen fixation (“pretenders”), nutrient stoichiometry. Unexplored diversity at different levels (molecular, chemical, taxonomic), techniques for controlling cyanobacteria blooms, the future for cyanobacteria under climate change scenarios (∼4) 7) General references, web resourcess and primary articles. (∼2) 8) Questions and potential experiments for instructors and students will be provided at the end of the lecture (supplementary slides).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".