DOI: 10.5061/dryad.48hq1
title: Data from: Spatially explicit summary statistics for historical population genetic inference

description: The integration of population genetics with explicit spatial analyses is
 crucial to address a range of evolutionary and ecological questions under
 realistic scenarios. Ignoring space can lead to misleading inferences, yet
 incorporating spatial realism leads to using complex evolutionary models
 that necessitate distilling raw genetic data into summary statistics that
 capture information relevant to the models in question. However, summary
 statistics derived from traditional population genetic theory overlook the
 valuable spatial component of genetic variation that is innate in natural
 systems and can be informative about historical spatio-demographic
 processes. To overcome this limitation, we introduce and evaluate a new
 set of spatially explicit summary statistics that can be calculated from a
 wide range of molecular markers and that take advantage of
 well-established spatial genetic algorithms to summarize the spatial
 distribution and autocorrelation of genetic variation. Using spatially
 explicit demographic simulations of SNP data, we characterize their
 behavior under different realistic historical demographic scenarios and
 assess their relative contribution to accurate model selection and
 parameter estimation. We demonstrate that under a wide range of parameter
 values, alternate demographic histories could be best differentiated by
 supplementing traditional summary statistics with these new spatial
 statistics. We identify different subset of statistics, including
 Euclidean distances in spatial-PCA space, Monmonier's identification
 of genetic breaks, and spatial correlograms, that greatly improve
 discrimination of complex species histories and have sizeable potential to
 estimate associated parameters, although the added power is likely to be
 dependent on landscape models and sampling configurations. These results
 highlight the potential benefits of condensing spatial genetic information
 into informative summary statistics to substantially improve testing
 alternative historical demographic models that reflect the complex
 spatio-temporal dynamics of species evolutionary histories. This study
 bridges phylogeography and landscape genetics by paving the way for
 phylogeographers wanting to incorporate spatial models and data as well as
 landscape geneticists wanting to incorporate history.
description: Spatial simulations
 resultsTraditional and
 spatially explicit summary statistics obtained from spatial simulations
 under both landscape models tested: “altitudinal” (M1) and “latitudinal”
 (M2) models. Parameter settings associated with each simulation replicate
 are also provided.Simulations_results.zipScripts for the calculation of spatially explicit summary statisticsR scripts for the calculation of all spatially explicit summary statistics introduced in the associated publicationPipeline for spatially explicit simulationsThis pipeline allows the implementation of the spatially explicit simulations presented in the manuscript. Details on how to run it can be found in the ReadMe file.