Trophic Level Stability-Inducing Effects of Predaceous Early Juvenile Fish in an Estuarine Mesocosm Study
Bibliographic record
Abstract
BACKGROUND: Classically, estuarine planktonic research has focussed largely on the physico-chemical drivers of community assemblages leaving a paucity of information on important biological interactions. METHODOLOGY/PRINCIPAL FINDINGS: Within the context of trophic cascades, various treatments using in situ mesocosms were established in a closed estuary to highlight the importance of predation in stabilizing estuarine plankton abundances. Through either the removal (filtration) or addition of certain planktonic groups, five different trophic systems were established. These treatments contained varied numbers of trophic levels and thus different "predators" at the top of the food chain. The abundances of zooplankton (copepod and polychaete), ciliate, micro-flagellate, nano-flagellate and bacteria were investigated in each treatment, over time. The reference treatment containing apex zooplanktivores (early juvenile mullet) and plankton at natural densities mimicked a natural, stable state of an estuary. Proportional variability (PV) and coefficient of variation (CV) of temporal abundances were calculated for each taxon and showed that apex predators in this experimental ecosystem, when compared to the other systems, induced stability. The presence of these predators therefore had consequences for multiple trophic levels, consistent with trophic cascade theory. CONCLUSIONS/SIGNIFICANCE: PV and CV proved useful indices for comparing stability. Apex predators exerted a stabilizing pressure through feeding on copepods and polychaetes which cascaded through the ciliates, micro-flagellates, nano-flagellates and bacteria. When compared with treatments without apex predators, the role of predation in structuring planktonic communities in closed estuaries was highlighted.
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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 | 0.000 |
| 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".