Plant invasion is associated with higher plant–soil nutrient concentrations in nutrient‐poor environments
Bibliographic record
Abstract
Plant invasion is an emerging driver of global change worldwide. We aimed to disentangle its impacts on plant-soil nutrient concentrations. We conducted a meta-analysis of 215 peer-reviewed articles and 1233 observations. Invasive plant species had globally higher N and P concentrations in photosynthetic tissues but not in foliar litter, in comparison with their native competitors. Invasive plants were also associated with higher soil C and N stocks and N, P, and K availabilities. The differences in N and P concentrations in photosynthetic tissues and in soil total C and N, soil N, P, and K availabilities between invasive and native species decreased when the environment was richer in nutrient resources. The results thus suggested higher nutrient resorption efficiencies in invasive than in native species in nutrient-poor environments. There were differences in soil total N concentrations but not in total P concentrations, indicating that the differences associated to invasive plants were related with biological processes, not with geochemical processes. The results suggest that invasiveness is not only a driver of changes in ecosystem species composition but that it is also associated with significant changes in plant-soil elemental composition and stoichiometry.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".