DOI: 10.5061/dryad.sxksn036m
title: Data and supplementary materials from: Large genetic divergence underpins cryptic local adaptation across ecological and evolutionary gradients

description: Environmentally covarying local adaptation is a form of cryptic local
 adaptation in which the covariance of the genetic and environmental
 effects on a phenotype obscures the divergence between locally adapted
 genotypes. Here, we systematically document the magnitude and drivers of
 the genetic effect (VG) for two forms of environmentally covarying local
 adaptation: counter- and cogradient variation. Using a hierarchical
 Bayesian meta-analysis, we calculated the overall effect size of VG as
 1.05 and 2.13 for populations exhibiting countergradient or cogradient
 variation, respectively. These results indicate that the genetic
 contribution to phenotypic variation represents a 1.05 to 2.13 standard
 deviation change in trait value between the most disparate populations
 depending on if populations are expressing counter- or cogradient
 variation. We also found that while there was substantial variance among
 abiotic and biotic covariates, the covariates with the largest mean
 effects were temperature (2.41) and gamete size (2.81). Our results
 demonstrate the pervasiveness and large genetic effects underlying
 environmentally covarying local adaptation in wild populations and
 highlights the importance of accounting for these effects in future
 studies.
description: To generate a full list of studies, we first analyzed
 studies indicated as showing counter- or cogradient variation in the
 qualitative analysis from Conover <em>et al.</em> [12]. We
 then searched the Web of Science topic field using the terms
 “counter*gradient variation” in May of 2018 and “co*gradient variation”
 (while excluding the previous search, as the wildcard renders them
 redundant) in June of 2019, resulting in 384 and 34 results, respectively.
 In August 2019, we also included studies citing the Conover <em>et
 al.</em> [12] review, as well as the earlier review article by
 Conover & Schultz [13]—682 studies total (some of which were
 redundant with studies in the prior search resulting in a total of 858
 studies). These methods are discussed in more depth in the Supplementary
 Methods. To
 be further included in our analysis, a study had to meet a set of
 qualifying criteria. Specifically, a study had to be designed to include
 some form of a common environment—this may have been in a common garden
 study or a reciprocal transplant using wild populations or populations
 recently brought into lab conditions. We did not include examples from
 domestic populations or lab induced selection. Additionally, studies must
 have included two or more common environments to determine the signal of
 local adaptation (countergradient, cogradient, or others such as GxE that
 were ultimately not included in this study), as well as two or more
 populations to compare the genotypic difference of the phenotypic response
 between populations. Finally, studies were determined to show counter- or
 cogradient based on plotted reaction norms to verify environmental and
 genetic effects covaried—<em>i.e.</em>, populations in away
 environments minimized (countergradient) or maximized genetic variance
 (cogradient) (positive or negative covariance, Fig. 1c,d)—and genotypes
 maintained their rank order across environments (Fig. S1). Occasionally,
 studies investigated these distinctions across multiple species in the
 place of populations and such studies were
 discarded. To
 calculate effect sizes, we took data from both tables and figures in
 manuscripts. For data in the form of figures, we used the software
 WebPlotDigitizer [39] to extract the relevant
 data. 
description: Any software able to open a Microsoft Excel file. 
 .RDS files need to be opened with program R using the readRDS()
 function