Intraspecific Variation in Ecophysiology of Three Dominant Prairie Grasses Used in Restoration: Cultivar Versus Non‐Cultivar Population Sources
Bibliographic record
Abstract
Dominant species play crucial roles in determining plant community structure and ecosystem function. Cultivars of the dominant prairie grasses are widely used in prairie restoration and are selected for characters such as high biomass production, increased reproductive output, and stress tolerance. Genetic differences exist between cultivar and non‐cultivar population sources of dominant tallgrass prairie species, which may have implications for plant performance in prairie restoration. We measured net photosynthesis (Anet), stomatal conductance (gs), and water use efficiency (WUE) in cultivar and non‐cultivar dominant tallgrass prairie speciesAndropogon gerardiiVitman,Sorghastrum nutans(L.) Nash, andSchizachyrium scoparium(Michx.) Nash in both a greenhouse experiment and an experimental tallgrass prairie restoration. We found indicators of enhanced physiological performance (higherAnet,gs,and/or WUE) in cultivar population sources of all three dominant grass species relative to non‐cultivars. ForA. gerardii, cultivars exhibited higherAnetand WUE than non‐cultivars. ForS. nutans, cultivars exhibited highergs,whereas non‐cultivars showed higher WUE. Lastly, cultivars ofS. scopariumshowed higher WUE than non‐cultivar population sources. Our results show that population selection of dominant species in restoration can have consequences for plant performance, which may have implications for competitive interactions that affect community structure (i.e. diversity) and ecosystem function (i.e. aboveground net primary production) during the reassembly of prairie systems.
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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 | 0.000 |
| 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 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".