Indirect effects of parasites in invasions
Bibliographic record
Abstract
Summary Introduced species disrupt native communities and biodiversity worldwide. Parasitic infections (and at times, their absence) are thought to be a key component in the success and impact of biological invasions by plants and animals. They can facilitate or limit invasions, and positively or negatively impact native species. Parasites have not only direct effects on their hosts, but also indirect effects on the species with which their hosts interact. Indirect effects include density‐mediated effects (resulting from parasite‐induced reduction in host reproduction and survival) as well as trait‐mediated indirect effects (resulting from parasite‐induced changes in host phenotype, behaviour or life history). These effects are not mutually exclusive but often interact. The importance of these indirect interactions for invasion success, and the extent to which these effects ramify throughout communities and influence ecosystems undergoing biological invasion provide the focus of our review. Examples from the animal and plant literature illustrate the importance of parasites in mediating both competitive and consumer–resource interactions between native and invasive species. Parasites are involved in indirect interactions at all trophic levels. Furthermore, the indirect effects of parasitic infection are important at a range of biological scales from within a host to the whole ecosystem in determining invasion success and impact. To understand the importance of parasitic infection in invasion success and in the outcomes for invaded communities requires an interdisciplinary approach by ecologists and parasitologists, across animal and plant systems. Future research should develop a framework integrating community ecology, evolution and immunology to better understand and manage the spread of invasive species and their diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".