Differential responses of native and exotic plant species to an invasive grass are driven by variation in biotic and abiotic factors
Bibliographic record
Abstract
Abstract Questions The impact of invasive species on community structure and function varies, yet it is difficult to predict. Different hypotheses have been proposed to predict invasive species establishment and impact on resident communities, based on characteristics of the resident community and/or environmental conditions. Invasive species, however, interact with both native and exotic species. The interaction with exotic species is important, as it can result in secondary invasion or greater impact on native species. Smooth brome (Bromus inermis Leyss.) is a widely planted forage crop, but also a harmful invasive species in North American grasslands, yet little is known about the variability of its impact on resident communities. We ask (1) whether smooth brome has a consistent impact on community structure and function; (2) which biotic and abiotic conditions are associated with smooth brome's impact on resident communities; and (3) whether smooth brome has a similar impact on native and exotic species, and which biotic or abiotic conditions drive the interaction of smooth brome with native and exotic species. Location Eight grasslands throughout Alberta, Canada. Methods We used space‐for‐time substitutions to quantify smooth brome's impact on different aspects of community structure and function, and whether it varies depending on species richness, productivity, temperature, precipitation and variation in precipitation. Results Smooth brome had a consistent negative impact on community structure and function. However, the strength of the effect depended on aspects of the local community. Smooth brome impacts on species richness were higher in species‐rich areas, while impact on resident species biomass was larger in productive, warmer and more variable sites. In most sites the negative effect of smooth brome on species richness was higher for native species, compared to exotics. Impact on native and exotic species richness was larger in species‐rich and more variable sites, respectively. Conclusions Understanding and predicting smooth brome's impact on community structure and function can help managers prescribe management plans to reduce negative impacts of smooth brome on native communities. Predicting the interaction of smooth brome with exotic species may be just as important when planning management strategies, to avoid secondary invasion and/or the accumulation of exotic 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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".