Why sampling scheme matters: the effect of sampling scheme on landscape genetic results

By M. D. Schwartz, Kevin S. McKelvey. Conservation Genetics, 2009

426 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a46e9570cab41de49046635c1b2b5a7c36556e22

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In Genetics

Citations in the corpus

Identifying future research needs in landscape genetics: where to from here? (2009, background): “…can result in serious errors (Pascual-Hortal and Saura 2007; Wu 2007), landscape genetic studies should evaluate how the spatial configuration of the samples and the spatial resolution of the landscape data influence statistical results and ecological conclusions (Schwartz and McKelvey 2009).”
Applications of landscape genetics in conservation biology: concepts and challenges (2010, background): “Further, in reality and especially so in conservation biology, many landscape genetic studies rely on opportunistic sampling, e.g. samples are obtained from hunters or harvesters in the case of larger vertebrates (Schwartz and McKelvey 2009).”
Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern (2012, background): “Schwartz & McKelvey (2009) demonstrated that clustered sampling can lead to erroneous conclusions about the number of populations when using Bayesian clustering approaches to define populations when IBD is a driving force.”
Integrating genetic data into management of marine resources: how can we do it better? (2008, background): “…is not unlimited, and their ability to provide meaningful information when levels of population genetic differentiation are weak (as occurs with many marine species) has not been rigorously studied (Hauser et al. 2006; Latch et al. 2006; Waples and Gaggiotti 2006; Schwartz and McKelvey 2008).”
The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem (2016, background): “…et al. 2009; Jombart et al. 2010; Pritchard et al. 2010), when close relatives are included in the data set (Anderson & Dunham 2008; Pritchard et al. 2010; Rodriguez-Ramilo & Wang 2012; Rodr ıguezRamilo et al. 2014) or when autocorrelation exists at the sampling scale (Schwartz & McKelvey 2009).”
Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho (2010, background): “Methods to delineate discrete populations are known to identify boundaries even in continuously structured populations ( Schwartz and McKelvey 2009 ); observing a coincidence between a landscape feature and a putative subpopulation boundary does not confirm the role of that feature in creating spati”
Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches (2010, methodology): “Simulations could quantify effects on N̂e of sampling strategies (Schwartz and McKelvey 2008), age structures, and immigration patterns for both 368 Conserv Genet (2010) 11:355–373”
Species Delimitation in Herpetology (2019, background): “Limited sampling of specimens is especially likely to result in clusters of geographically proximate samples being identified as ‘‘species’’ (Schwartz and McKelvey, 2008; Rittmeyer and Austin, 2012; Barley et al., 2018), even if the only genetic structure within the samples represents classic…”
Landscape genetics: where are we now? (2010, background): “…genetic distance measures and Bayesian clustering measures also assume that individuals are inherently clustered into groups, which can be problematic for species that are more uniformly dis- 2010 Blackwell Publishing Ltd tributed on the landscape, such as large mammals (Schwartz & McKelvey 2009).”