Consequences of plant–soil feedbacks in invasion
Bibliographic record
Abstract
Summary Plant species can influence soil biota, which in turn can influence the relative performance of plant species. These plant–soil feedbacks ( PSF s) have been hypothesized to affect many community‐level dynamics including species coexistence, dominance and invasion. The importance of PSF s in exotic species invasion, although widely hypothesized, has been difficult to determine because invader establishment necessarily precedes invader‐mediated PSF s. Here, we combine a spatial simulation model of invasion that incorporates PSF s with a meta‐analysis that synthesizes published case studies describing feedbacks between pairs of native and exotic species. While our spatial model confirmed the link between positive soil feedbacks (‘home’ advantage) for exotic species and exotic species spread, results were dependent on the initial abundance of the exotic species and the equivalence of dispersal and life history characteristics between exotic and native species. The meta‐analysis of 52 native–exotic pairwise feedback comparisons in 22 studies synthesized measures of native and exotic performance in soils conditioned by native and exotic species. The analysis indicated that the growth responses of native species were often greater in soil conditioned by native species than in soil conditioned exotic species (a ‘home’ advantage). The growth responses of exotic species were variable and not consistently related to species soil‐conditioning effects. Synthesis . Overlaying empirical estimates of pairwise PSF s with spatial simulations, we conclude that the empirically measured PSF s between native and exotic plant species are often not consistent with predictions of the spread of exotic species and mono‐dominance. This is particularly the case when exotic species are initially rare and share similar dispersal and average fitness characteristics with native species. However, disturbance and other processes that increase the abundance of exotic species as well as the inclusion of species dispersal and life history differences can interact with PSF effects to explain the spread of invasive 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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".