Irrigation Requirements for Seed Production of Five Lomatium Species in a Semiarid Environment
Bibliographic record
Abstract
Seeds of native plants are needed for rangeland restoration in the Intermountain West. Many of these plants are rarely cultivated and relatively little is known about the cultural practices required for their seed production. Irrigation trials were conducted for five perennial Lomatium species over multiple years. Lomatium species grown at the Oregon State University Malheur Experiment Station, Ontario, OR received 0, 100, or 200 mm of irrigation per year. Seed yield responses to irrigation were evaluated by linear and quadratic regression. In general, seed yields from the three species grown for 10 years responded linearly or quadratically to irrigation. To improve the accuracy of estimated irrigation water requirements, regressions were also run on seed yield responses to irrigation plus precipitation during the previous spring; spring and winter; and spring, winter, and fall. Over multiple years, Lomatium dissectum (Nutt.) Mathias & Constance and L. triternatum (Pursh) J.M. Coult. & Rose seed yields were best estimated by a quadratic response to irrigation plus spring precipitation with highest yields at 243 and 255 mm, respectively. Lomatium grayi (J.M. Coult. & Rose) J.M. Coult. & Rose seed yields were best estimated by a quadratic response to irrigation plus precipitation during the fall, winter, and spring with highest yields at 358 mm. Two of the Lomatium species were grown for the last 6 years. The seed yields of L. nudicaule (Pursh) J.M. Coult. & Rose did not respond to irrigation. Seed yields of Lomatium suksdorfii (S. Watson) J.M. Coult. & Rose responded linearly to irrigation in 2015.
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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".