Landscape genetics has emerged as a new research area that integrates population genetics, landscape ecology and spatial statistics. Researchers in this field can combine the high resolution of genetic markers with spatial data and a variety of statistical methods to evaluate the role that landscape variables play in shaping genetic diversity and population structure. While interest in this research area is growing rapidly, our ability to fully utilize landscape data, test explicit hypotheses and truly integrate these diverse disciplines has lagged behind. Part of the current challenge in the development of the field of landscape genetics is bridging the communication and knowledge gap between these highly specific and technical disciplines. The goal of this review is to help bridge this gap by exposing geneticists to terminology, sampling methods and analysis techniques widely used in landscape ecology and spatial statistics but rarely addressed in the genetics literature. We offer a definition for the term "landscape genetics", provide an overview of the landscape genetics literature, give guidelines for appropriate sampling design and useful analysis techniques, and discuss future directions in the field. We hope, this review will stimulate increased dialog and enhance interdisciplinary collaborations advancing this exciting new field.

The solution structure of a complex between a truncated form of HMG-I(Y), consisting of the second and third DNA binding domains (residues 51-90), and a DNA dodecamer containing the PRDII site of the interferon-beta promoter has been solved by multidimensional nuclear magnetic resonance spectroscopy. The stoichiometry of the complex is one molecule of HMG-I(Y) to two molecules of DNA. The structure reveals a new architectural minor groove binding motif which stabilizes B-DNA, thereby facilitating the binding of other transcription factors in the opposing major groove. The interactions involve a central Arg-Gly-Arg motif together with two other modules that participate in extensive hydrophobic and polar contracts. The absence of one of these modules in the third DNA binding domain accounts for its-100 fold reduced affinity relative to the second one.

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A major objective of ecology is to understand how ecological processes limit population connectivity and species' distributions. By spatially quantifying ecological components driving functional connectivity, we can understand why some locally suitable habitats are unoccupied, resulting in observed discontinuities in distribution. However, estimating connectivity may be difficult due to population stochasticity and violations of assumptions of parametric statistics. To address these issues, we present a novel application of Random Forests to landscape genetic data. We address the effects of three key ecological components on Bufo boreas connectivity in Yellowstone National Park: ecological process, scale, and hierarchical organization. Habitat permeability, topographic morphology, and temperature-moisture regime are all significant ecological processes associated with B. boreas connectivity. Connectivity was influenced by growing-season precipitation, 1988 Yellowstone fires, cover, temperature, impervious surfaces (roads and development), and topographic complexity (56% variation explained). We found that habitat permeability generally operates on fine scales, while topographic morphology and temperature-moisture regime operate across multiple scales, thus demonstrating the importance of cross-scale analysis for ecological interpretation. In a hierarchical analysis, we were able to explain more variation within genetic clusters as identified using Structure (a Bayesian algorithm) (74%; dispersal cover, growing-season precipitation, impervious surfaces) as opposed to between genetic clusters (45%; ridgelines, hot, dry slopes, length of hot season, and annual precipitation). Finally, the analytical methods we developed are powerful and can be applied to any species or system with appropriate landscape and genetic data.