Review: The recruitment biology and ecology of large and small crabgrass in turfgrass: Implications for management in the context of a cosmetic pesticide ban
Bibliographic record
Abstract
Turner, F. A., Jordan, K. S. and Van Acker, R. C. 2012. Review: The recruitment biology and ecology of large and small crabgrass in turfgrass: Implications for management in the context of a cosmetic pesticide ban. Can. J. Plant Sci. 92: 829-845. Large and small crabgrass (Digitaria sanguinalis and Digitaria ischaemum, respectively) are problem weeds within turfgrass. As seedling recruitment shapes the demography of annual weeds, it is important to assess the recruitment biology and ecology of crabgrass species to determine how these aspects may be impacted by various management techniques. This, in addition to an assessment of large and small crabgrass' response to cultural management techniques in turfgrass, is the objective of this review. Turfgrass management either directly or indirectly affects the crabgrass recruitment microclimate by impacting the soil, topography, resources or plant cover, which in turn affects the degree and timing of crabgrass recruitment. Due to the increasing number and scale of cosmetic use pesticide bans in Canada this topic is particularly relevant. Crabgrass experiences a dormancy period of several weeks prior to being able to germinate. Microsite conditions of temperature and moisture have the greatest influence on dormancy breaking and germination; however, other factors such as light have shown some effect on recruitment. There is also evidence that factors such as seed scarification or treatment with nitrogenous compounds can increase recruitment. In turfgrass, common cultural practices, such as mowing, irrigation, and fertilization, can affect the recruitment of crabgrass. By pairing knowledge of the effects of microsite conditions on crabgrass recruitment with management that favours turfgrass vigour, better management practices to deter crabgrass infestation can be recommended. There are large gaps in research pertaining to the effects of cultural management techniques on crabgrass recruitment. Research to date has failed to make critical links between knowledge of these species' recruitment biology and ecology and how this is affected or can be applied through herbicide alternative management. This review recommends that regional assessments of crabgrass populations are necessary to determine the most appropriate management strategies. This type of research would have the potential to guide ideal application timings for existing and developing alternative herbicides as well as recommendations for the best cultural management practices to deter crabgrass infestation in turf.
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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 | 0.001 | 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) | 0.000 | 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".