Data from: Regional diversity reverses the negative impacts of an alien predator on local species-poor communities
Bibliographic record
Abstract
Species diversity is often an implicit source of biological insurance for communities against the impacts of novel perturbations, such as the introduction of an invasive species. High environmental heterogeneity (e.g., a mountainous gradient) is expected to beget greater regional species diversity and variation in functional traits related to environmental tolerances. Thus, heterogeneous metacommunities are expected to provide more tolerant colonists that buffer stressed local communities in the absence of dispersal limitation. We tested the hypothesis that importation of a regional zooplankton pool assembled from a diverse array of lakes and ponds lessens the impacts of a novel predator on local species-poor alpine communities by increasing response diversity (i.e., diversity of tolerances to environmental change) as mediated by variation in functional traits related to predator evasion. We also tested if impacts varied with temperature, as warming may modify (e.g., dampen or amplify) invasion effects. An eight-week factorial experiment ([fishless vs. introduced Oncorhynchus mykiss (rainbow trout)] x [ambient temperature vs. heated] x [local vs. local + regional species pool]) was conducted using thirty-two 1000 L mesocosms. Associations between experimental treatments and species functional traits were tested by RLQ and fourth-corner analyses. Although the introduced predator suppressed local species richness and community biomass, colonization by several montane zooplankters reversed these negative effects, resulting in increased species diversity and production. Invasion resistance was unaffected by higher temperatures, which failed to elicit any significance impacts on the community. We discovered that the smaller body sizes of imported species drove functional overcompensation (i.e., increased production) in invaded communities. The observed ecological surprise showed how regionally sourced biodiversity from a highly heterogeneous landscape can offset, and even reverse, the local negative impacts of an invasive species. Further, prey body size was found to be a key species trait mediating the ecological impacts of the aquatic invasive predator. Our study highlights the novel application of a functional approach to understanding the impacts of biological invasions, using species traits that pertain directly to potential responses to exotic species.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".