DOI: 10.5061/dryad.tb2rbp00h
title: A greenhouse experiment partially supports inferences of ecogeographic isolation from niche models of Clarkia sister species

description: Premise: Ecogeographic isolation, or geographic isolation caused by
 ecological divergence, is thought to be of primary importance in
 speciation, yet is difficult to demonstrate and quantify. To determine
 whether distributions are limited by divergent adaptation or historical
 contingency, the gold standard is to reciprocally transplant taxa between
 their geographic ranges. Alternatively, ecogeographic isolation is
 inferred from species distribution models and niche divergence tests based
 on widely available environmental and occurrence data. Methods: We test
 for ecogeographic isolation between two sister species of California
 annual wildflowers, Clarkia concinna and C. breweri, with a hybrid
 approach. We use niche models to predict water availability as the major
 axis of ecological divergence and then test that with a greenhouse
 experiment. Specifically, we manipulate water availability in field soils
 for two populations of each species and predict higher fitness in
 conditions representing home habitats to those representing the
 environment of each’s sister species. Key Results: Water availability and
 soil representing C. concinna generally increased both species’ fitness.
 Thus, water and soil may indeed limit C. concinna from colonizing the
 range of C. breweri, but not vice versa. We suggest that the competitive
 environment and pollinator availability, which are not directly captured
 with either approach, may be key biotic factors correlated with climate
 that contribute to unexplained ecogeographic isolation for C. breweri.
 Conclusions: Ours is a valuable approach to assessing ecogeographic
 isolation, in that it balances feasibility with model validation, and our
 results have implications for species distribution modeling efforts geared
 towards predicting climate change responses.
description: README File Manifest.txt lists and describes
 all the files. File Name:
 CCCB_Fitness.csv contains the results from our greenhouse
 reciprocal transplant experiment. The number of variables has been reduced
 to just what we used for our study.
 CCCB_Fitness_metadata.csv contains explanations for each variable
 name in CCCB_Fitness.csv. Greenhouse_GLM_Fig5_6.R is
 the R code used in creating the zero-inflated and conditional generalized
 linear mixed models, as well as the graphs for Figure 5, Figure 6 and
 Supplemental Figure XX.
 Bioclim_Figure2b_WilcoxonTests.R is the R script used to create
 box plots of the values associated with each of the BioClim variables with
 &gt;10% percent contributions to our species distribution
 models. c.c_occurence_data_cleaned.csv is the
 occurrence data for Clarkia concinna used in conjunction with BioClim
 data. c.b _occurence_data_cleaned.csv is the occurrence
 data for Clarkia breweri used in conjunction with the BioClim
 data. SDM_PctContribution_Graph_Fig2a.R is the R code
 used to create Figure 2a.
 Env_Var_CCCB_allbioclimplussoil_REDUCED.csv is the data used in
 SDM_PctContribution_Graph_Fig2a.R to create Figure 2a from our species
 distribution model percent contribution of each BioClim variable and Rock
 Type. RockType_Chisquare_Graph_Figure3.R is the R code
 used to create Figure 3, showing the proportion of occurrences of each
 study species on primary parent rock types. This code also contains the
 chi-squared test for significance between the two species.
 primary_proportion_soil_2.csv is the data used to create Figure
 3, containing the proportion of occurrences of each study species on
 primary rock types. CC_CB_Primary_Rock_Reduced.csv is
 the data used for the chi-squared test in
 RockType_Chisquare_Graph_Figure3.R. RockType1Raster.tif
 is the raster of the primary parent rock type and was derived from the
 USGS California geologic map polygon shape file (Ludington et al.
 2005) RockType1Raster.tif is the raster of the
 secondary parent rock type and was derived from the USGS California
 geologic map polygon shape file (Ludington et al. 2005)
 Rock Type Lookup - Rocktype1 index.csv is used to look up
 lithology from numeric rock ids in RockType1Raster.tif.
 Rock Type Lookup - Rocktype2 index.csv is used to look up
 lithology from numeric rock ids in RockType2Raster.tif.
 Prep_Occurrence_Data.R is the script we used to download GBIF
 data of the two Clarkia species and remove erroneous entries. 
 Prep_Targetted_Background_Data.R is the script we used to
 download and prepare the GBIF data of all of the non-clarkia species we
 used as pseudo-absence data.  Prep_Env_Rasters.R is the
 script we used to prep environmental data raster bricks that were used to
 create the max ent models Run_MaxEnt_Models.R is the
 script we used to build MaxEnt models for the two species.
 CompetitiveEnvironment.R is the script to compare the competitive
 environments of Clarkia concinna and C. breweri. CoverData.csv, CoverDataTTests.csv, and
 CoverMetaData1.csv are input files for CompetitiveEnvironment.R and
 contain the competitive environment data and other site characteristics.
 CoverMetaData1.csv shows how the species (“sp”) and site codes
 (“sitecode”) in CoverDataTTests.csv correspond to the details in Appendix
 S4. “Observer” indicates who recorded the field data, and is either
 Kathleen Kay (“Kathleen”) or Shelley Sianta (“Shelley”).
 BroennimannAnalysis.R is the script we used to measure niche
 equivalency, measure niche similarity of the Clarkia species, and plot
 their environmental niche in PCA space. This script was adapted from
 Broennimann et al. (2012).