Microbial ecology of biological invasions
Bibliographic record
Abstract
Invasive microbes, plants and animals are a major threat to the composition and functioning of ecosystems; however, the mechanistic basis of why exotic species can be so abundant and disruptive is not well understood. Most studies have focused on invasive plants and animals, although few have considered the effects of invasive microbes, or interactions of invasive plant and animal species with microbial communities. Here, we review effects of invasive plants on soil microbial communities and discuss consequences for plant performance, plant community structure and ecosystem processes. In addition, we briefly discuss effects of invasive soil microbes on plant communities, which has been less well studied, and effects of invasive animals on soil decomposers and ecosystem functioning. We do this by considering each of three important functional groups of microbes, namely soil microbial parasites and pathogens, mutualistic symbionts and decomposers. We conclude that invasive plants, pathogenic and symbiotic soil microbes will have strongest effects on the abundance of individual species, community diversity and ecosystem functioning. Invasive decomposer microbes probably have little impact, because of limited specificity and great functional redundancy. However, invasive plants and animals can have major effects on microbial decomposition in soil. We propose that understanding, predicting and counteracting consequences of enhanced global homogenization of natural communities through introducing exotic plants, animals and microbes will require future studies on how pathogenic, symbiotic and decomposer soil microbes interact, how they are influenced by higher trophic level organisms and how their combined effects are influencing the composition and functioning of ecosystems.
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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) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".