An invasive benthic fish magnifies trophic cascades and alters pelagic communities in an experimental freshwater system
Bibliographic record
Abstract
Most studies of the consequences of nonnative fish introductions address only direct effects rather than cascading effects on lower trophic levels or other ecosystem compartments. These trophic cascades have not been studied in comparison to the effects of a functionally similar native species nor with consideration of bottom-up forces (e.g., nutrient supply). The Round Goby (Neogobius melanostomus) is an invasive benthic predator that can deplete local populations of grazers, potentially generating substantive increases in benthic algal biomass. Here, we tested, with a factorial experimental design, the influence of Round Gobies on the relative strength of top-down and bottom-up forces in benthic communities by manipulating consumer type (Round Goby or native Logperch (Percina caprodes), snails only, or controls where snails and fish were absent), nutrient addition, and the presence of an invasive suspension feeder (Quagga Mussel [Dreissena bugensis]) in freshwater mesocosms. We also investigated how these perturbations affect phytoplankton and zooplankton communities. We observed stronger top-down forces in the presence of Round Gobies vs native Logperch, and these forces resulted in reduced grazer abundance and a concomitant increase in benthic algal abundance. However, when Quagga Mussels were present, bottom-up forces dominated. Round Gobies had a significantly greater positive effect on phytoplankton than did native Logperch. Our results highlight the importance of measuring top-down and bottom-up forces in comparison with a trophically similar native species to elucidate the ramifying effects of a nonnative predator on food webs.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".