Genetic isolation by distance and landscape connectivity in the American marten (Martes americana)

By T. Broquet, Nicolas Ray, E. Petit, J. Fryxell, Françoise Burel. Landscape Ecology, 2006

172 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c83cb11538cf6ddfd76cf8d37e8b6576e338d8d0

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Citations in the corpus

Forks in the Road: Choices in Procedures for Designing Wildland Linkages (2008, background): “Furthermore, the location of a least-cost path is highly sensitive to pixel size and errors in classifying single pixels (Broquet et al. 2006).”
A case for incorporating phylogeography and landscape genetics into species distribution modelling approaches to improve climate adaptation and conservation planning (2010, background): “In a study of the American marten (Martes americana), least-cost distances, based on individuals avoiding known dispersal barriers such as logging sites and undeveloped forest stands, better explained pairwisegenetic distances than did Euclidean geographic distances (Broquet et al., 2006).”
Individual dispersal, landscape connectivity and ecological networks (2013, unknown): “the island model, the stepping stone model, or the continuous model (Maynard Smith, 1989)] with contrasting assumptions (Broquet et al., 2006; Broquet & Petit, 2009).”
Beyond description: the active and effective way to infer processes from spatial patterns. (2009, methodology): “…Mladenoff 1999, Fall and Fall 2001, Fortin and Dale 2005, McIntire et al. 2007); and (4) through analysis of the spatial pattern itself with the goal of uncovering the process (e.g., Olden et al. 2001, Tuomisto et al. 2003, McIntire 2004, Fang 2005, Broquet et al. 2006, Fajardo and McIntire 2007).”
Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho (2010, background): “A surprising number of landscape genetic studies have evaluated a single landscape resistance hypothesis relative to a null model of isolation by distance or isolation by barriers (e.g. Coulon et al. 2004; Broquet et al. 2006; Schwartz et al. 2009).”
Circuit Theory and Model-Based Inference for Landscape Connectivity (2013, unknown): “Approaches based on isolation by distance (Wright 1943; Spear et al. 2005; Broquet et al. 2006) hypothesize that gene flow is based on a random walk in a homogeneous landscape, and thus that a genetic distance metric computed from observed genetic information is correlated with the straight-line…”
Estimating landscape resistance to movement: a review (2012, background): “Surprisingly, only six of the papers reviewed adopted this approach (McRae and Beier 2007; Rae et al. 2007; Broquet et al. 2009; Koscinsky et al. 2009; Murphy et al. 2010; Nichol et al. 2010), and they often reached different conclusions regarding the best grain size, illustrating the point that one”
Quantifying and disentangling dispersal in metacommunities: how close have we come? How far is there to go? (2010, background): “Here the effective distance of the path needed to reach the target with the least cost, or the cumulative cost of a particular path is used to assess the connectivity (Broquet et al. 2006), increased values equating with decreased probability (Bender and Fahrig 2005; Driezen et al.”
Habitat suitability modelling to correlate gene flow with landscape connectivity (2008, methodology): “The effectiveness of these models can be validated by population- or individual-based genetic analyses (Coulon et al. 2004; Vignieri 2005; Broquet et al. 2006; Epps et al. 2007).”
Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis (2010, background): “In many cases, especially with categorical variables (i.e. land cover), the researcher hypothesizes arbitrary costs based on the perceived relative costs among variables (e.g. Chardon et al. 2003; Broquet et al. 2006).”
The pond network: can structural connectivity reflect on (amphibian) biodiversity patterns? (2011, background): “Since it addressed to the level of organisms, conservation biology should be mainly interested in functional connectivity (Lindborg and Eriksson 2004; Broquet et al. 2006; Arens et al. 2007; Jordán et al. 2007).”
A brief guide to Landscape Genetics (2006, background): “The special section is complemented by three contributed research papers describing applications of landscape genetics in animals, (i.e.,) an insect (Holzhauer et al. 2006), a fish (Neville et al. 2006) and a mammal ( Broquet et al. 2006 ).”
SDMtoolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses (2014, background): “Some researchers generate friction land-scapes from classiﬁed satellite images where each major habitat type represents a diﬀerent friction value (i.e. Broquet et al. 2006).”