Shade responses of five grasses native to southwestern U.S. <i>Pinus ponderosa</i> forests
Bibliographic record
Abstract
Recent increases in Pinus ponderosa Dougl. ex Laws. forest density in the southwestern United States have severely reduced understory herbaceous biomass and altered understory species composition. To examine whether changes in graminoid species composition are caused by increased shading, we studied the effects of shade on leaf gas exchange, biomass, and reproductive characteristics of five grass species native to Arizona P. ponderosa forests in a greenhouse study. Blepharoneuron tricholepis (Nash) Torr., Koeleria cristata (L.) Pers., Festuca arizonica Vasey, Muhlenbergia montana(Nutt.) Hitchc., and Sitanion hystrix (Nutt.) J.G. Smith were grown under three light levels representative of photosynthetic photon flux densities and red/far-red ratios that occur beneath P. ponderosa canopies. In general, all species grew better under unshaded conditions, but all survived and flowered even under the dense shade treatment. Reduction of net assimilation rate by shading was the strongest during early reproductive shoot growth for all species except K. cristata, whose assimilation rate was unaffected by shading. Biomass allocation and reproductive responses to shading varied among species. Biomass of S. hystrix was the least affected by shading of all species, and it showed no response in biomass allocation to reproduction but increased height and weight of individual flower stalks under shade. Overall, S. hystrix and K. cristata, species that occur in dense P. ponderosa stands, were least affected by experimental shading, which suggests that shade is a contributing factor to the distribution of grass species in Arizona P. ponderosa forests.
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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".