Invasive Fishes Interact With Temperature to Reshape Community Size Structure Across Climatic Zones
Bibliographic record
Abstract
The body size spectrum (or individual size distribution) is a simple yet widely recognized approach that links individual and population traits to community structure and ecosystem functions, making it a valuable indicator of anthropogenic effects. However, the assessment of size spectra in the context of biological invasions remains poorly explored. We investigated the impacts of non-native (NN) fish invasions on the size structure of 667 lacustrine fish communities across climatic regions (temperate, tropical, and subtropical systems) and the roles of trophic position and temperature in modulating these effects. We found that fish communities under higher invasion pressure exhibit flatter, or less negative, size spectrum exponents. Also, NN species from lower trophic levels can have greater impacts than piscivorous NNs by reshaping size spectra and reducing the overall biomass of native communities. We also observed that piscivore NNs and NNs from lower trophic levels interacted positively with temperature to drive the size spectrum exponent and total biomass of the native communities, respectively. These results can be explained by two main mechanisms: (i) NN piscivores primarily act through size-selective predation (top-down control), which may be intensified particularly on small prey in warmer lakes, and (ii) NN fish from lower trophic levels primarily act through competition, hence reducing the numerical abundance of small-sized native fish, which may be more vulnerable in colder and less productive lakes. These mechanisms are leading to flatter size spectrum exponents mainly at higher temperatures and to a decline in the total biomass of the native community, mainly at lower temperatures, effectively reversing the expected temperature-size rule pattern. By disentangling the trophic and temperature-dependent mechanisms through which NN fishes affect size structure, this study strengthens our ability to anticipate the impact of biological invasions on freshwater communities and their ecosystem functions and services under global change.
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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) | 0.000 | 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".