Reviewing Interspecies Interactions as a Driving Force Affecting the Community Structure in Lakes via Cyanotoxins
Bibliographic record
Abstract
The escalating occurrence of toxic cyanobacterial blooms worldwide is a matter of concern. Global warming and eutrophication play a major role in the regularity of cyanobacterial blooms, which has noticeably shifted towards the predomination of toxic populations. Therefore, understanding the effects of cyanobacterial toxins in aquatic ecosystems and their advantages to the producers are of growing interest. In this paper, the current literature is critically reviewed to provide further insights into the ecological contribution of cyanotoxins in the variation of the lake community diversity and structure through interspecies interplay. The most commonly detected and studied cyanobacterial toxins, namely the microcystins, anatoxins, saxitoxins, cylindrospermopsins and β-N-methylamino-L-alanine, and their ecotoxicity on various trophic levels are discussed. This work addresses the environmental characterization of pure toxins, toxin-containing crude extracts and filtrates of single and mixed cultures in interspecies interactions by inducing different physiological and metabolic responses. More data on these interactions under natural conditions and laboratory-based studies using direct co-cultivation approaches will provide more substantial information on the consequences of cyanotoxins in the natural ecosystem. This review is beneficial for understanding cyanotoxin-mediated interspecies interactions, developing bloom mitigation technologies and robustly assessing the hazards posed by toxin-producing cyanobacteria to humans and other organisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".