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Reliable Method for Assessing Seed Germination, Dormancy, and Mortality under Field Conditions
Published on: November 6, 2016
Selection on early survival does not explain germination rate clines in Mimulus cardinalis
Christopher D Muir1,2, Courtney L Van Den Elzen1,3, Amy L Angert1,4
1Department of Botany, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Phenotypic clines in germination rate may not be driven by local adaptation. Southern populations of scarlet monkeyflower exhibited higher survival, but not due to faster germination, suggesting nonadaptive forces shape this trait.
Area of Science:
- Evolutionary Biology
- Quantitative Genetics
- Plant Ecology
Background:
- Phenotypic traits often vary along environmental gradients, forming clines.
- Local adaptation can generate these clines, but nonadaptive processes are also possible.
- Quantifying genetic variance in traits like germination rate has been challenging.
Purpose of the Study:
- To test if a germination rate cline in Mimulus cardinalis is a signature of local adaptation.
- To investigate the covariation between germination rate and early survival as a fitness component.
- To develop a novel statistical model for estimating genetic variance in germination rate.
Main Methods:
- Employed quantitative genetics and reciprocal transplant experiments.
- Measured genotypic and population-level covariation between germination rate and early survival.
- Developed and utilized a discrete log-normal model for genetic variance estimation.
Main Results:
- Found no evidence that genetic variation in germination rate influenced early survival.
- Southern populations, in both transplant gardens, showed earlier germination and higher survival rates.
- Higher early survival in southern populations was not attributable to faster germination.
Conclusions:
- The observed phenotypic cline in germination rate is likely driven by nonadaptive forces.
- Local adaptation may not be the primary driver of this specific germination cline.
- Further research is needed to explore selection at other life stages and apply the statistical framework to other traits.
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