Identifying the fitness consequences of sex in complex natural environments
Cite this dataset
Rushworth, Catherine; Brandvain, Yaniv; Mitchell-Olds, Thomas (2020). Identifying the fitness consequences of sex in complex natural environments [Dataset]. Dryad. https://doi.org/10.5061/dryad.n5tb2rbt9
Abstract
Methods
Three datasets are included. The pollen viability dataset was collected in the greenhouse using methods outlined in the manuscript (buds collected at Stage 12 and stained for viability, followed by assessment of 100 grains of pollen visible on the slide). The field data was collected via field censuses conducted by a team of trained researchers. Plants were censused for maximum plant height, survival through the first winter and through a second winter, fruit number, and estimated total herbivory. Seeds were estimated from average seed set per genotype per garden and used to calculate the maximum number of seeds in the first growing season (see raw seed numbers in Rushworthetal_seedcounts). Plant width was measured at planting to include as a covariate.
Herbivory (or "plant damage") data has been manipulated. A small constant was added to each value and then this new value was log-transformed. The log-transformed value and the original value are in the dataset.
Usage notes
Any missing values indicate that a plant either did not survive to census or that herbivory was not possible to census in a particular way (for example, that all leaves were missing at the time of first census, in which case leaf herbivory could not be measured). No other data values should be missing.
Datasets have been uploaded as Excel documents so that a second tab could be included to explain the header names in each dataset. Please note that to use the R script, these datasets will need to be converted to csv files. All outlier removal, etc. is indicated in the accompanying R script.
Please feel free to contact the corresponding author with any questions.
Funding
National Science Foundation, Award: DEB-1311269
National Institute of General Medical Sciences, Award: R01 GM086496