Growth chamber reciprocal transplant dataset
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Phenotypic plasticity can alter traits that are crucial to population establishment in a new environment, before adaptation can occur. How often phenotypic plasticity enables subsequent adaptive evolution is unknown, and examples of the phenomenon are limited. We investigated the hypothesis of plasticity-mediated persistence as a means of colonization of agricultural fields in one of the worldâs worst weeds, Raphanus raphanistrum ssp. raphanistrum. Using non-weedy native populations of the same species and subspecies as a comparison, we tested for plasticity-mediated persistence in a growth chamber reciprocal transplant experiment. We identified traits with genetic differentiation between the weedy and native ecotypes as well as phenotypic plasticity between growth chamber environments. We found that most traits were both plastic and differentiated between ecotypes, with the majority plastic and differentiated in the same direction. This suggests that phenotypic plasticity may have enab..., , , # Growth Chamber Reciprocal Transplant Dataset
[https://doi.org/10.5061/dryad.4mw6m90kb](https://doi.org/10.5061/dryad.4mw6m90kb)
This dataset contains the phenotypic data collected from plants grown in the growth chamber reciprocal transplant experiment, as well as the conditions in the growth chambers.
## Description of the data and file structure
The dataset contains three sheets: \"Chamber Conditions\", \"Main Data\", and \"Leaf Data\" (although much of the information in \"Leaf Data\" has been incorporated into \"Main data\")
### Chamber Conditions
This sheet contains the temperature and day length set points for each chamber each week. All temperature and day length information from the two weather stations used (LGER and KBTL) were collected from [www.wunderground.com](http://www.wunderground.com).
Variables:
* Granada, Spain (LGER) -Â the dates from which we collected temperature and day length information from the Grenada, Spain weather station (LGER) to simulate in the Winter An...
创建时间:
2024-07-20



