Using spatial Bayesian methods to determine the genetic structure of a continuously distributed population: clusters or isolation by distance?

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Assessing population structure in the face of isolation by distance: Are we neglecting the problem? (2018, background): “On the opposite way, there is also a bias in spatial correlation methods towards the detection of IBD when, in reality, there are geographically distinct clusters of populations (Guillot, Leblois, Coulon, & Frantz, 2009; Meirmans, 2012).”
Do cities represent sources, sinks or isolated islands for urban wild boar population structure? (2017, background): “Given the relatively weak levels of IBD, it is unlikely that these genetic partitions are artefacts (Frantz et al. 2009).”
The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem (2016, background): “The program performance and accuracy is nevertheless known to be affected when isolation by distance is present (Frantz 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…”
Genetic diversity in the European wild boar Sus scrofa: phylogeography, population structure and wild x domestic hybridization (2011, background): “Different clustering methods may happen to identify a variable number of clusters, as found in a population at the borders of the Netherlands, Luxembourg and Germany (Frantz et al. 2009).”