Data and analyses for: Fire effects on plant reproductive fitness vary among individuals reflecting pollination-dependent mechanisms

Here are the analyses and data for the manuscript:   

"Fire effects on plant reproductive fitness vary among individuals reflecting pollination-dependent mechanisms" published in American Journal of Botany
Data Files:
These ascii comma-separated-values files contain data for each study species.

echinacea.csv 
contains data 350 Echinacea angustifolia individuals observed across 1996-2016, fields include:

year: year the observations were taken (numeric)

unit: west or east, indicates the placement of each individual plant in either the east or west management unit of the prairie preserve. (character)

burn: burn status = 0 if no burn occurred in that year, = 1 if a burn occurred (binary)

synchrony: Augspurger's 1983 index of individual flowering synchrony ranges from 0 to 1 with 0 indicating total asynchrony of flowering time with all other flowering individuals in the mating scene and 1 indicating total synchrony with all other flowering individuals in the mating scene (numeric)

hdCt: count of flowering heads per individual plant (numeric)

hdAcheneCt: count of fruits per flowering head (numeric)

seedSetSampleCt: count of randomly sampled fruits to be x-rayed (numeric)

seedSetSampleFull: count of full fruits from x-ray images of a random sample of achenes  from each individual plant (numeric)

fl: flowering status, the entire column = 1 because every individual in the dataset flowered

liatris.csv and solidago.csv 
contain data 223 Liatris aspera individuals and 231 Solidago speciosa individuals, respectively, observed across 2016-2018. Fields include:

year: year the observations were taken (numeric)

unit: west or east, indicates the placement of each individual plant in either the east or west management unit of the prairie preserve. (character)

burn: burn status = 0 if no burn occurred in that year, = 1 if a burn occurred (binary)

sync: Augspurger's 1983 index of individual flowering synchrony ranges from 0 to 1 with 0 indicating total asynchrony of flowering time with all other flowering individuals in the mating scene and 1 indicating total synchrony with all other flowering individuals in the mating scene (numeric)

stemCt: count of flowering stems per individual plant (numeric)

hdCt: count of flowering heads per individual plant (numeric)

hdAcheneCt: count of fruits per individual plant (numeric)

seedSetSampleCt: count of randomly sampled fruits to be x-rayed (numeric)

seedSetSampleFull: count of full achenes from x-ray images of a random sample of achenes  from each individual plant. Counts were obtained from randomized x-ray images that were counted twice and the average was taken of the two  counts, hence some counts are not perfect integers (numeric)

root: flowering status, the entire column = 1 because every individual in the dataset flowered

Analysis Files:
These files are knitted PDFs from R scripts that together produce all analyses including information for tables and drafts of figures included in the manuscript. Figure 1 in the manuscript is a conceptual figure generated using Adobe Illustrator.

These analyses were generated using R version 4.2.1 and load the following packages:

aster: Geyer CJ (2021). _aster: Aster Models_. R package version 1.1-2, https://CRAN.R-project.org/package=aster.

tidyverse:  Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” _Journal of Open Source Software_, *4*(43), 1686. doi:10.21105/joss.01686. R package version 1.3.2.

echinaceaAnalysis.pdf reads in echinacea.csv and models full dataset from 1996-2016.

liatris2018AnalysisModelSelection.pdf reads in liatris.csv and models 2018 data. The best model from 2018 is selected in this script and then applied to the 2016 and 2017 data in the file liatris2016_2017Analysis.pdf.  

liatris2016_2017Analysis.pdf reads in liatris.csv and generates >250 datasets with simulated values of fruit counts in 2016 and 2017. It then applies the 'best' model selected in liatris2018AnalysisModelSelection.pdf to these simulated datasets. 

solidago2018AnalysisModelSelection.pdf reads in solidago.csv and models 2018 data. The best model from 2018 is selected in this script and then applied to the 2016 and 2017 data in the file solidago2016_2017Analysis.pdf.  

solidago2016_2017Analysis.pdf reads in solidago.csv and generates 250 datasets with simulated values of fruit counts in 2016 and 2017. It then applies the 'best' model selected in solidago2018AnalysisModelSelection.pdf to these simulated datasets.