Disentangling the influence of abiotic variables and a non‐native predator on freshwater community structure
Bibliographic record
Abstract
Cause‐and‐effect interpretations of the apparent impacts of biological invasions are confounded by the coincident occurrence of non‐native species and changes to abiotic factors. Native community structure and function can vary greatly in space and time, owing to abiotic variables that could potentially be affected by non‐native species. Here, we sought to determine the relative importance of abiotic variables and an invasive predatory fish, the Eurasian round goby ( Neogobius melanostomus ), on local macroinvertebrate assemblages and benthic algal production in the St. Lawrence River. We used structural equation modeling to evaluate the strength of interaction pathways between hypothesized biotic and abiotic factors driving trophic cascades. Our results indicate that biotic interactions with the round goby drive changes in the abundances of native grazers and non‐native dreissenid mussels in the St. Lawrence River. However, the directionality of these effects contradicts previous studies of round goby impacts that emphasized top‐down control. We found positive correlations between round goby density and prey (dreissenid and grazer) densities, suggesting complex interactions between round gobies and benthic communities, including strong bottom‐up forces. Together with previous studies, our results suggest that, although the interactions between round gobies and benthic communities remain strong, the direction of these interactions varies over space and time. Our results highlight the importance of disentangling the respective roles of biotic interactions and abiotic factors, in order to properly assess the impacts of non‐native species as well as the spatiotemporal variability of such impacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".