Is management of an invasive grass<i>Agropyron cristatum</i>contingent on environmental variation?
Bibliographic record
Abstract
Summary The control of invasive species is a challenge heightened by the dependency of management outcomes on environmental variation. This is especially true for plants invading semi‐arid habitats, where growing season precipitation varies greatly among years. Agropyron cristatum is an invasive grass widely introduced in the Great Plains of North America. We studied its demographic responses to management using field experiments and matrix population models. Plants were clipped to simulate grazing, treated with herbicide or left unmanaged, at three levels of water availability, for 2 years. Growth rates (λ) were high in unmanaged populations. Clipped populations were mainly stable, whereas λ for herbicide‐treated populations varied greatly with water availability and between years. Low λ in clipped and herbicide‐treated populations was mainly the result of low seed production, and these populations were the most sensitive to water availability. Clipped populations produced no seeds in the second year, indicating a cumulative negative effect of defoliation. In general, seed production, germination and juvenile survival all increased with water supply, suggesting that invasion may increase under wet conditions. Population projections revealed a steady increase in population size for unmanaged populations, whereas clipped populations were more stable. Herbicide‐treated populations mainly decreased. Life‐cycle stages associated with recruitment contributed the most to the rapid growth of unmanaged populations, whilst the persistence of managed populations relied on the survival of established tussocks. Synthesis and applications. These results demonstrate strong management effects on A. cristatum invasion in spite of significant population responses to water availability. Management can therefore have large effects on the invasion of native grasslands regardless of among‐year variability in precipitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".