Circuit theory predicts gene flow in plant and animal populations

By B. Mcrae, Paul Beier. Proceedings of the National Academy of Sciences of the United States of America, 2007

1,008 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ca6f1b49f1744553add79e9b1be0277a1d980bcc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

In Ecology

Citations in the corpus

Isolation by environment (2014, background): “…and in the past decade, new fields such as landscape genetics (Storfer et al. 2007; Balkenhol et al. 2009; Wagner & Fortin 2013) have arisen to examine the roles played by ecology and the environment in microevolutionary processes (McRae & Beier 2007; R€as€anen & Hendry 2008; Bolnick & Otto 2013).”
Circuit Theory and Model-Based Inference for Landscape Connectivity (2013, positive): “…ecology, where it has been theoretically linked to animal movement and gene flow in heterogeneous landscapes (McRae 2006; Cushman et al. 2006; McRae and Beier 2007; McRae et al. 2008; Urban et al. 2009; Cushman and Landguth 2010; Dyer, Nason, and Garrick 2010; Lookingbill et al. 2010;…”
SDMtoolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses (2014, methodology): “One prevalent method to do this is to estimate least-cost paths (LCPs) among sites (e.g. Ray 2005; McRae & Beier 2007; Etherington 2011).”
related: an R package for analysing pairwise relatedness from codominant molecular markers (2015, background): “It has recently been shown that such an approach can be particularly informative when assessing population structure and landscape genetics, where the network is based on pairwise genetic distances between sampling locations (Dyer & Nason 2004; Dyer 2007; McRae & Beier 2007; Garroway et al. 2008).”
Landscape genetics: where are we now? (2010, background): “Unsuitable natural habitat may be a significant barrier to gene flow (McRae & Beier 2007), as in the case of savanna habitats that fragment lemur populations (Radespiel et al. 2008) or dry grassland habitat fragmenting salamander populations (Rittenhouse & Semlitsch 2006).”
Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges (2010, background): “Similarly, spectral data can help to model resistance surfaces which are used to estimate the effective resistance of the landscape to gene flow (Spear et al., 2005; Cushman et al., 2006; McRae and Beier, 2007).”
Applications of landscape genetics in conservation biology: concepts and challenges (2010, background): “There is a need to predict regional conservation corridors and quantify the degree of expected connectivity between specific areas (e.g. Fall et al. 2007; McRae and Beier 2007).”
Representing genetic variation as continuous surfaces: An approach for identifying spatial dependency in landscape genetic studies (2008, background): “Several studies propose methods to estimate spatial location(s) of gene flow between pairs of sample locations (Arnaud 2003, Spear et al. 2005, McRae 2006, Cushman et al. 2006, McRae and Beier 2007 ).”
A range-wide model of landscape connectivity and conservation for the jaguar, Panthera onca (2010, background): “While most landscape analyses detect genetic discontinuities of a species after the fact (McRae and Beier, 2007), preliminary genetic data on jaguars indicate potential linkages between jaguar populations that were not previously considered.”
Placing linkages among fragmented habitats: do least‐cost models reflect how animals use landscapes? (2011, methodology): “Individual animals rarely use a single optimum route, and single-pixel-wide LCPs are of limited biological value (Majka, Jenness & Beier 2007; McRae & Beier 2007; McRae et al. 2008; Pinto & Keitt 2009).”
Identifying future research needs in landscape genetics: where to from here? (2009, background): “(sensu Manel et al. 2003), recent landscape genetic approaches largely focus on describing and mapping populations (e.g., Pritchard et al. 2000; Dupanloup et al. 2002; Franc ¸ois et al. 2006) and on identifying factors that influence rates and patterns of gene flow within and between populations (e.”
A case for incorporating phylogeography and landscape genetics into species distribution modelling approaches to improve climate adaptation and conservation planning (2010, methodology): “The effectiveness of this approach was assessed for central American populations of the big-leaf mahogany (Swientenia macrophylla) and North American populations of the wolverine (Gulo gulo) (McRae & Beier, 2007).”
Re-Evaluating Causal Modeling with Mantel Tests in Landscape Genetics (2013, background): “Landscape genetics provides a powerful approach to evaluate the effects of multiple landscape features on population connectivity [1–12].”
Estimating effective landscape distances and movement corridors: Comparison of habitat and genetic data (2015, background): “5.8; McRae and Beier 2007, McRae et al. 2008), in which multiple available pathways (including suboptimal ones) can be followed by the individuals and contribute to estimated connectivity among locations.”