A practical toolbox for design and analysis of landscape genetics studies

Abstract

Landscape genetics integrates theory and analytical methods of population genetics and landscape ecology. Research in this area has increased in recent decades, creating a plethora of options for study design and analysis. Here we present a practical toolbox for the design and analysis of landscape genetics studies following a seven-step framework: (1) define the study objectives, (2) consider the spatial and temporal scale of the study, (3) design a sampling regime, (4) select a genetic marker, (5) generate genetic input data, (6) generate spatial input data, and (7) choose an analytical method that integrates genetic and spatial data. Study design considerations discussed include choices of spatial and temporal scale, sample size and spatial distribution, and genetic marker selection. We present analytical methods suitable for achieving different study objectives. As emerging technologies generate genetic and spatial data sets of increasing size, complexity, and resolution, landscape geneticists are challenged to execute hypothesis-driven research that combines empirical data and simulation modeling. The landscape genetics framework presented here can accommodate new design considerations and analyses, and facilitate integration of genetic and spatial data by guiding new landscape geneticists through study design, implementation, and analysis.