Mesopredator-mediated trophic cascade can break persistent phytoplankton blooms in coastal waters
Bibliographic record
Abstract
Abstract Managing eutrophied systems only bottom-up (nutrient decreases) can be economically and ecologically challenging. Top-down controls (consumption) were sometimes found to effectively control phytoplankton blooms. However, mechanistic insights, especially on possible trophic cascades, are less understood in brackish, species-poor coastal waters, where large cladocera are absent. In this study, we set-up large mesocosms for three consecutive years during growth season. One set of mesocosms was controlled by mesopredator (gobies and shrimp), whereas the other mesocosms had no such mesopredator present. The results were standardized to monitoring data of the ecosystem to denote possible differences between treatments and the system. We found that mesopredator mesocosms showed lower turbidity, phytoplankton biomass, and nutrients compared to no-mesopredator mesocosms and the ecosystem. This decrease allowed macrophytes to colonize water depths only sparsely colonized in the ecosystem. Rotifer biomass increased in mesopredator mesocosms compared to the ecosystem and no-mesopredator mesocosms. Likewise, copepod biomass that potentially grazes upon rotifers and other microzooplankton decreased in mesopredator mesocosms. No-mesopredator mesocosms were colonized by an omnivorous mesograzer ( Gammarus tigrinus ), potentially creating additional pressure on macrophytes and increasing grazing-mediated nutrient release. Zooplankton was not able to control the non-nutrient limited phytoplankton. We propose a new mechanism, where a higher mesopredator density will increase grazing on phytoplankton by promoting microzooplankton capable of grazing on picophytoplankton. This proposed mechanism would contrast with freshwater systems, where a decrease of zooplanktivorous fish would promote larger phytoplankton grazer like cladocera. Biomanipulation in such species-poor eutrophic coastal waters may be more successful, due to less trophic pathways that can cause complex top-down controls. Stocking eutrophic coastal waters with gobies and shrimps may be an alternative biomanipulative approach rather than selectively remove large piscivorous or omnivorous fish from eutrophic coastal waters.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".