DOI: 10.5061/dryad.zcrjdfnmc
title: Range-wide study in a sexually polymorphic wild strawberry reveals climatic and soil associations of sex ratio, sexual dimorphism, and sex chromosomes

description: The contemporary environment, which influences local resource pools and
 mate access, is rapidly changing in the Anthropocene, posing unique
 challenges for sexually polymorphic plants. A landscape scale
 understanding of climate and soil drivers of sex-specific factors can help
 predict how global change will impact these species. Using ~7,000
 herbarium and iNaturalist specimens we determine how sex ratio, sexual
 dimorphism, and sex chromosomes vary with geographic, climatic and soil
 gradients in Fragaria virginiana and whether these conform to
 predictions from theory. Sex ratio was hermaphrodite/male-biased and was
 driven more by soil attributes than climatological ones. Sex
 ratio-environment associations matched predictions for subdioecious
 species in the West but for gynodioecious species in the East. Climatic,
 not soil factors, affected sexual dimorphism in traits related to carbon
 acquisition but not mate access (petal size and flowering time). Greater
 sexual dimorphism was due to one sex being more responsive (females for
 leaf length and hermaphrodite/male for runnering while flowering) to
 precipitation or temperature. Sex chromosome variation was biased towards
 the ancestral type and frequencies varied with different environmental
 factors between East-West regions. A landscape-level perspective of
 environmental drivers of sex-specific factors provides insight into how
 anthropogenic disturbance may impact sexually polymorphic species.
description: Briefly, we downloaded digitized, imaged herbarium records of
 <em>Fragaria</em> <em>virginiana</em> from online
 herbarium databases (iDigBio, GBIF, the Consortium of Pacific Northwest
 Herbaria, and the Consortium of Intermountain Herbaria) and iNaturalist
 records. We filtered out all digital records which were missing
 geolocation coordinates (latitude, longitude) or a collection date. We
 scored imaged records for flower sex, flowering time (collection date),
 presence of collection-year runners, and measured petal and leaf length
 and width on a subset of herbarium records. We additionally used targeted
 primers to characterize the sex determining region (SDR) haplotypes on a
 subset of herbarium records, which we had sampled in-person and requested
 from specific herbaria. To associate sex ratio, petal/leaflet phenotype,
 flowering time (from collection date), runner presence and SDR haplotypes
 with spatial and climate variables we gathered data on elevation,
 temperature and precipitation (from the CRU time series dataset), and soil
 nitrogen and bulk density (from the SoilGrids dataset). Herbarium records
 were binned into east and west regions using a dividing meridian of 102° W
 (natural gap in the continent-wide range). Temperature and precipitation
 averages were estimated for the coldest (winter) and warmest (summer)
 months for each record, averaging the monthly temperature for the month of
 collection and the two preceeding months for 10 years prior to the
 collection year of the record (10-year pre-collection climatological
 means). Together these data were used to conduct the analyses presented in
 the linked manuscript.
description: # Range-wide study in Fragaria virginiana reveals climatic and soil
 drivers of sex ratio, sexual dimorphism, sex chromosomes as well as
 vulnerability to global change
 [https://doi.org/10.5061/dryad.zcrjdfnmc](https://doi.org/10.5061/dryad.zcrjdfnmc) * The contemporary environment, which influences local resource pools and mate access, is rapidly changing in the Anthropocene, posing unique challenges for sexually polymorphic plants. A landscape scale understanding of climate and soil drivers of sex-specific factors can help predict how global change will impact these species. * Using ~7,000 herbarium and iNaturalist specimens we determine how sex ratio, sexual dimorphism, and sex chromosomes vary with geographic, climatic and soil gradients in ***Fragaria virginiana*** and whether these conform to predictions from theory. * Sex ratio was hermaphrodite/male-biased and was driven more by soil attributes than climatological ones. Sex ratio-environment associations matched predictions for subdioecious species in the West but for gynodioecious species in the East. Climatic, not soil factors, affected sexual dimorphism in traits related to carbon acquisition but not mate access (petal size and flowering time).  Greater sexual dimorphism was due to one sex being more responsive (females for leaf length and hermaphrodite/male for runnering while flowering) to precipitation or temperature. Sex chromosome variation was biased towards the ancestral type and frequencies varied with different environmental factors between East-West regions. * A landscape-level perspective of environmental drivers of sex-specific factors  provides insight into how anthropogenic disturbance may impact sexually polymorphic species. ## Description of the data and file structure Data are organized into three data files that are used to conduct the analyses shown in the manuscript. All data files include standard collection and housekeeping metadata (sample IDs, collection date, database ID/catalog number and image URL) as well as spatial and environmental predictors (latitude, longitude, region, soil nitrogen, soil bulk density, winter temperature mean, summer temperature mean, winter precipitation mean and summer precipitation mean). We additionally include the shape file used to generate figures containing mapped records. 1. Cullen_etal_2024_MFscores_metadata_final_03-04-24_NA_Updated.csv contains all data used for analyses of sex ratio based on hermaphrodite/male or female scores, flowering time using collection date, and presence of runners. To conduct the runner analysis, the data is subsetted to only herbarium records using a line of code in the R script. Columns names and descriptions are as follows: | Column Name | Description | | :-------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | db\_sample\_id | Sample identification code formatted as DATABASE\_PROJECTNAME\_IDNUMBER (e.g., iDigBio\_FSH2022\_0001). | | database | The database that the record was downloaded from. | | catalog\_number | The museum catalog number associated with the sample. This column is blank for iNaturalist records. | | institutionCode | Code indicating the herbarium storing the record. This column is blank for iNaturalist records. | | access.URL | URL link to access digitized image of herbarium record or iNaturalist record. All images are maintained on servers that the authors of this manuscript are not responsible for, so we cannot guarantee availablilty of all images. | | inaturalist\_ID | Unique ID for in-house record keeping of iNaturalist records. This column is blank for herbarium records. | | record.type | Whether record was downloaded from an herbarium database or iNaturalist | | male\_fertility | Scored fertility of flower, recorded as sex (either Female \[not male fertile] or Male/Hermaphrodite \[male fertile]). | | m.f.binary | Sex score as binary for use in binomial GLMER. 0 = male/hermaphrodite, 1 = female. | | eventDate | Date in the form of  YYYY-MM-DD.  | | elevation | Elevation in meters. Elevation values estimated with package elevatr. | | col.year | Collection year of the record. | | collection\_doy | Collection day of year = flowering day of year. 365 day of year score (1 = January 1st, 365 = December 31st). Calculated from  | | lat | Latitude (decimal) | | lon | Longitude (decimal) | | longitude\_bins | Longitude bins = Region. Records were "binned" into regions east and west of 102°W. | | runners | Yes (Y) or No (N) as to whether plants had produced runners during the year they were collected. | | mean\_tmp\_coldest\_Q | Mean temperature of the coldest quarter = winter temperature (°C). Mean calculated for month of collection | | mean\_pre\_coldest\_Q | Mean precipitation of the coldest quarter = winter precipitation (mm/month) | | mean\_tmp\_warm\_Q | Mean temperature of the warmest quarter = summer temperature (°C) | | mean\_pre\_warm\_Q | Mean precipitation of the warmest quarter = summer precipitation (mm/month) | | bdodmean\_5\_15 | Bulk Density (of the fine earth fraction) in kg/dm^3 estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | | nitrogenmean\_5\_15 | Nitrogen concentration in g/kg estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | 2. Cullen_etal_2024_Petal-Leaflet_measures_metadata_final_03-04-24_NA_Updated.csv contains all data used for analyses of petal and leaflet length dimorphism. These data constitute a subset of the "Cullen_etal_2024_MFscores_metadata_final_03-04-24_NA_Updated.csv" dataset with the addition of petal and leaflet measurements, so all other columns can be identically interpreted. Columns names and descriptions are as follows: | Column Name | Description | | :-------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | db\_sample\_id | Sample identification code formatted as DATABASE\_PROJECTNAME\_IDNUMBER (e.g., iDigBio\_FSH2022\_0001). | | database | The database that the record was downloaded from. | | catalog\_number | The museum catalog number associated with the sample. This column is blank for iNaturalist records. | | institutionCode | Code indicating the herbarium storing the record. This column is blank for iNaturalist records. | | access.URL | URL link to access digitized image of herbarium record or iNaturalist record. All images are maintained on servers that the authors of this manuscript are not responsible for, so we cannot guarantee availablilty of all images. | | male\_fertility | Scored fertility of flower, recorded as sex (either Female \[not male fertile] or Male/Hermaphrodite \[male fertile]). | | m.f.binary | Sex score as binary for use in binomial GLMER. 0 = male/hermaphrodite, 1 = female. | | elevation | Elevation in meters. Elevation values estimated with package elevatr. | | eventDate | Date in the form of  YYYY-MM-DD.  | | col.year | Collection year of the record. | | lat | Latitude (decimal) | | lon | Longitude (decimal) | | longitude\_bins | Longitude bins = Region. Records were "binned" into regions east and west of 102°W. | | petal\_length | Length of petal from base to tip in mm. | | petal\_width | Width of petal at widest point, measured perpendicular to midvein in mm. | | leaflet\_length | Length of longest central leaflet from base to tip in mm. | | petal\_width | Width of longest central leaflet at widest point, measured perpendicular to midvein in mm. | | bdodmean\_5\_15 | Bulk Density (of the fine earth fraction) in kg/dm^3 estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | | nitrogenmean\_5\_15 | Nitrogen concentration in g/kg estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | | mean\_tmp\_coldest\_Q | Mean temperature of the coldest quarter = winter temperature (°C). Mean calculated for month of collection | | mean\_pre\_coldest\_Q | Mean precipitation of the coldest quarter = winter precipitation (mm/month) | | mean\_tmp\_warm\_Q | Mean temperature of the warmest quarter = summer temperature (°C) | | mean\_pre\_warm\_Q | Mean precipitation of the warmest quarter = summer precipitation (mm/month) | 3. Cullen_etal_2024_SDRhaplotypes_metadata_final_03-04-24_NA_Updated.csv contains all data used for analyses of sex determining region haplotypes. Columns names and descriptions are as follows: | Column Names | Description | | :-------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | pcr\_sample\_id | Sample identification code. Codes from Tennessen et al. 2018 follow different formatting. | | record.type | Whether sample tissue was obtained from an herbarium record, the National Clonal Germplasm Repository (NCGR), or was based on haplotyping from Tennessen et al., 2018. | | eventDate | Date in the form of  YYYY-MM-DD.  | | col.year | Collection year of the record. Derived from eventDate | | catalog\_number | catalog number from herbarium. Not all records had catalog numbers due to updating from catalog to barcode numbers. | | db\_sample\_id | ID of sample if it could be linked to the digital dataset. Many herbarium records were sampled in-person thus could not be directly linked to samples in the digital dataset. | | lat | Latitude (decimal) | | lon | Longitude (decimal) | | longitude\_bins | Longitude bins = Region. Records were "binned" into regions east and west of 102°W. | | elevation | Elevation in meters. Elevation values estimated with package elevatr. | | inferred\_SDR\_clade | SDR Haplotype (clade) as inferred from PCR assays. | | a.bg.binary | Binary SDR haplotypes grouped into either Alpha = 0, or Beta/Gamma = 1. Used in GLMER logistic regression. | | bdodmean\_5\_15 | Bulk Density (of the fine earth fraction) in kg/dm^3 estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | | nitrogenmean\_5\_15 | Nitrogen concentration in g/kg estimated for the 5-15cm depth range. More details of soil metrics at [https://www.isric.org/explore/soilgrids/faq-soilgrids](https://www.isric.org/explore/soilgrids/faq-soilgrids). | | mean\_tmp\_coldest\_Q | Mean temperature of the coldest quarter = winter temperature (°C). Mean calculated for month of collection | | mean\_pre\_coldest\_Q | Mean precipitation of the coldest quarter = winter precipitation (mm/month) | | mean\_tmp\_warm\_Q | Mean temperature of the warmest quarter = summer temperature (°C) | | mean\_pre\_warm\_Q | Mean precipitation of the warmest quarter = summer precipitation (mm/month) | Missing data code: NA 4. harvard_na_shp is a folder containing various shape files used to generate map figures and test for spatial autocorrelation. This folder cannot be renamed or it will throw an error when attempting to read the shape file (bound_p.shp) into R. Further descriptions of data collection and processing are described in the manuscript and associated supplementary information. ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Data was derived from the following sources: * Digitized images and associated collection records: * iDigBio * GBIF * Consortium of Intermountain Herbaria * Consortium of Pacific Northwest Herbaria * iNaturalist * Elevational data was derived from the elevatr package in R * Climate data (temperature and precipitation) was derived from the CRU TS database * Soil data was derived from the SoilGrids database ## Code/Software We coded analyses and figure generation in R. Raw data filtering and transformations were not included in this version of the script as they are lengthy and can be intuitively recreated using a working knowledge of the dplyr and tidyverse packages. We specifically include an R markdown file, used primarily for organizational purposes, NOT for producing knitted output (executing all code in the script and outputting the results to a word, pdf or html file). Model selection procedures can take several hours to run, thus we caution against running all of the code at once. Instead we suggest running code line-by-line only running the necessary pieces for your inquiry.