Effect of Planting Season, Bunchgrass Species, and Neighbor Control on the Success of Transplants for Grassland Restoration
Bibliographic record
Abstract
Abstract Constraints to grassland and open forest restoration (e.g., poor seed sources, yearly variation in establishment, and the persistence of weeds) necessitate the development of innovative methods to restore bunchgrass communities. We assessed the use of two native bunchgrass transplants, Bluebunch wheatgrass ( Pseudoroegneria spicata ) and Spreading needlegrass ( Achnatherum richardsonii ), for restoration within thinned montane forest communities of southeastern British Columbia, Canada. Fall and spring plantings were examined, either with or without glyphosate treatments to Pinegrass ( Calamagrostis rubescens ) neighbors. Calamagrostis rubescens is abundant in grassland affected by tree encroachment and may limit transplant establishment. Bunchgrass survival was positively associated ( p < 0.05) with transplant size. Although P. spicata survival was greater ( p < 0.01) with fall (81%) than with spring (44%) planting, survival of A. richardsonii was greater ( p < 0.01) when planted in the spring (68 vs. 23%). Reduction of C. rubescens led to a relatively small but significant increase ( p < 0.05) in bunchgrass survival by 7%. The summer after planting, changes in transplant tiller number varied by bunchgrass species, planting season, and treatment of neighboring C. rubescens . Removal of neighboring C. rubescens generally increased the number of tillers (or reduced tiller loss) but only within fall‐planted A. richardsonii and spring‐planted P. spicata . Both A. richardsonii and P. spicata transplants have potential for understory restoration within thinned montane forests, particularly using larger individuals, although to maximize survival, these species should be planted in the spring and fall, respectively. Reduction of C. rubescens may also enhance transplant survival and in some cases growth.
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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".