Environmental contributions to the evolution of trait differences in <i>Geum triflorum</i> : Implications for restoration
Bibliographic record
Abstract
PREMISE: How the environment influences the distribution of trait variation across a species' range has important implications for seed transfer during restoration. Evolution across environments could influence fitness when individuals are transferred into new environments. Here, we evaluate the role the environment has had on the distribution of genetic variance for traits important to adaptation. METHODS: In a common garden experiment, we quantified trait differentiation for populations of Geum triflorum sourced from three distinct ecoregions and evaluated the ability of climate to predict trait variation. Populations were sourced from the Manitoba and Great Lake alvar ecoregions that experience predictable extremes in seasonal water availability and the prairie ecoregion which exhibits unpredictable changes in water availability. RESULTS: Plants sourced from alvar ecoregions exhibited smaller but more stomata and greater intrinsic water-use efficiency relative to prairie plant populations, supporting the evolution of ecotypic differences. Estimates of standing genetic variance and heritable genetic variation for quantitative traits suggest alvar populations have greater adaptive potential. However, low evolvability suggests all populations likely have limited capacity to evolve in response to environmental change. CONCLUSIONS: These results highlight the importance of the environment in influencing the evolution and distribution of genetic differences across populations used as seed sources for restoration. Additionally, these data may inform recommendations for seed transfer across novel environments and our expectations of populations' adaptive potential.
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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".