Cyanobacteria in the Anthropocene: Synanthropism forged in an era of global change
Bibliographic record
Abstract
The Anthropocene has driven a transformative era where human activities exert unprecedented influence on Earth's biosphere. Consequently, synanthropic organisms, adept at thriving in human-modified environments, have emerged. While well studied in terrestrial ecosystems, the presence and ecological importance of synanthropic species in aquatic ecosystems, specifically among cyanobacteria, are less understood. Cyanobacteria blooms, notorious for their detrimental effects on ecosystems and human health, are increasing in frequency and intensity globally. In this perspective, we explore the evidence supporting this rise of cyanobacteria blooms, emphasizing the roles of human-induced eutrophication and climate change on select cyanobacteria genera. Cyanobacteria are not a monolith, with certain genera showing an observable increase within anthropogenically modified environments. We propose the establishment of a new sub-branch of phycology that explicitly investigates the ecology and physiology of synanthropic cyanobacteria. Understanding the intricate interactions between synanthropic species and human populations is imperative for managing human-altered ecosystems and conserving freshwater resources, particularly in the face of increasing global water insecurity. PRACTITIONER POINTS: The rise in cyanobacteria blooms is driven by a small subset of human-adapted genera-synanthropic cyanobacteria. Research is needed to characterize synanthropic cyanobacteria, which will aid in developing tailored management approaches. A paradigm shift from domesticating to "rewilding" landscapes and modifying behaviors to facilitate cohabitation are solutions to reducing 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 | 0.002 | 0.002 |
| 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 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".