Vegetative growth drives the negative effects of an invasive species on resident community diversity and is not limited by plant–soil feedbacks: A temporal assessment
Bibliographic record
Abstract
Abstract Many pathways of invasion have been posited, but ecologists lack an experimental framework to identify which mechanisms are dominant in a given invasion scenario. Plant–soil feedbacks (PSFs) are one such mechanism that tend to initially facilitate, but over time attenuate, invasive species' impacts on plant diversity and ecosystem function. PSFs are typically measured under greenhouse conditions and are often assumed to have significant effects under field conditions that change over time. However, direct tests of PSFs effects in natural settings and their change over time are rare. Here we compare the role of PSFs with the effects of biomass in limiting the dominance of an invasive species and impacts on resident species diversity. We characterized the effects of the invader Bromus inermis (Leyss.) on native plant communities over time and measured changes in its conspecific PSFs and vegetative growth to understand their integrated effects on community diversity. To do so, we combined data from a 6‐year field study documenting the rate and impacts of invasion with a short‐term greenhouse experiment quantifying PSF as a function of time since invasion in the field. We found that the nature and strength of B. inermis PSFs did not change over time and were not mediated by soil microbial communities. Though PSFs impacted B. inermis reproduction, they did not sufficiently limit vegetative growth to diminish the negative impacts of B. inermis biomass on native species. B. inermis experienced the full strength of its negative PSFs immediately upon invasion, but they were ineffective at reducing B. inermis vigor to facilitate the recovery of the native plant community. We recommend that conservation efforts focus on limiting B. inermis vegetative growth to facilitate community recovery.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".