Tallgrass prairie restoration: implications of increased atmospheric nitrogen deposition when site preparation minimizes adventive grasses
Bibliographic record
Abstract
Abstract Site preparation designed to exhaust the soil seedbank of adventive species can improve the success of tallgrass prairie restoration. Despite these efforts, increased rates of atmospheric nitrogen (N) deposition over the next century could potentially promote the growth of nitrophilic, adventive species in tallgrass restoration projects. We used a field experiment to examine how N addition affected species composition and plant productivity over the first 3 years of a tallgrass prairie restoration that was preceded by the planting of glyphosate‐resistant crops and multiple applications of glyphosate to exhaust the pre‐existing seedbank. We predicted that N addition would increase the percent cover of adventive plant species not included in the original seeding. Contrary to our prediction, only the cover of native species increased with N addition; native non‐leguminous forbs increased substantially, with Conyza canadensis (a weedy native species not part of the restoration seed mix) exploiting the combination of high N and bare ground in the first year, and non‐leguminous forbs (in particular Monarda fistulosa ) and native C 3 grasses, all of which were seeded, increasing with N addition by the third year. Native legumes was the only functional group that exhibited lower cover in N addition plots than in control plots. There was no significant response by native C 4 grasses to N addition, and adventive grasses remained mostly absent from the plots. Overall, our results suggest that site pre‐treatment with herbicide may continue to be effective in minimizing adventive grasses in restored tallgrass prairie, despite future increases in atmospheric N deposition.
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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) | 0.000 | 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".