Genetic population structure of fishers (Pekania pennanti) in the Great Lakes region: remnants and reintroductions

Abstract

Reintroduction programs have been pivotal in augmenting populations of fishers (Pekania pennanti (Erxleben, 1777)) and re-establishing them to their former range in North America. The majority of reintroduction efforts in fishers have been considered demographically successful, but reintroductions can alter genetic population structure and success has rarely been evaluated in fishers from a genetic standpoint. We used microsatellite data (n = 169) to examine genetic population structure of fishers in the Great Lakes region and comment on the success of past reintroductions at two different spatial scales. We found significant genetic population structure among source and reintroduced populations within the Great Lakes region and large-scale genetic structure between fisher populations located in two geographically distant regions (Great Lakes and Northeast) in the eastern United States. Reintroductions associated with the Great Lakes produced results that were largely consistent with other studies of fisher reintroductions in the Northeast. However, our data are the first to support a measurable impact on genetic population structure in Pekania pennanti pennanti (Erxleben, 1777) from a reintroduction using geographically distant source and reintroduced populations. When feasible, we strongly recommend that reintroduction programs include an investigation of the underlying genetic structure to better define intended goals and supplement measures of demographic success.

Population genetics of the wolverine in Finland: the road to recovery?

“…Our results suggest that the translocated wolverines have survived and reproduced for decades in western Finland. Indeed, translocations have the ability to alter the genetic make-up of populations and the genetic signature of translocations can remain detectable for a long time (Puckett et al 2014;Grauer et al 2017;Hapeman et al 2017). However, we did not detect signs of expansion from the western cluster towards the east but rather an expansion of the natural eastern cluster to the west.…”

Eco‐evolutionary factors that influence its demographic oscillations in Prochilodus costatus (Actinopterygii: Characiformes) populations evidenced through a genetic spatial–temporal evaluation

“…Several approaches have been improved to analyze environmental stochastic events and evolutionary mechanisms, that are based on coalescence reconstruction and tools from computational statistics, including moment matching (Kaut & Wallace, 2003 ), population decline and growth detection (Cornuet & Luikart, 1996 ), and likelihood approaches with varying effective population sizes ( Ne of Wright, 1931 ) (Gilbert & Whitlock, 2015 ) based on contemporary and past Ne (Drummond, Rambaut, Shapiro, & Pybus, 2005 ; Waples, 1989 ; Waples & Yokota, 2007 ). These approaches have helped us to improve our knowledge about how evolutionary processes influence the life history of organisms (i.e., demographic events), in the wild (Hapeman, Latch, Rhodes, Swanson, & Kilpatrick, 2017 ; Perrier, Guyomard, Bagliniere, Nikolic, & Evanno, 2013 ; Pil et al, 2018 ). Likewise that have been recently affected by selection/anthropogenic pressures, such as rapid contemporary climate change (Crozier & Hutchings, 2014 ), habitat degradation and disconnection (Lourenço et al, 2017 ), (re)introduction of species (Hapeman et al, 2017 ), and/or stocking programs (Hansen, Fraser, Meier, & Mensberg, 2009 ).…”

“…These approaches have helped us to improve our knowledge about how evolutionary processes influence the life history of organisms (i.e., demographic events), in the wild (Hapeman, Latch, Rhodes, Swanson, & Kilpatrick, 2017 ; Perrier, Guyomard, Bagliniere, Nikolic, & Evanno, 2013 ; Pil et al, 2018 ). Likewise that have been recently affected by selection/anthropogenic pressures, such as rapid contemporary climate change (Crozier & Hutchings, 2014 ), habitat degradation and disconnection (Lourenço et al, 2017 ), (re)introduction of species (Hapeman et al, 2017 ), and/or stocking programs (Hansen, Fraser, Meier, & Mensberg, 2009 ).…”

Multiscale patterns of isolation by ecology and fine-scale population structure in Texas bobcats

“…Predicting if IBE will occur is difficult in highly vagile species because both overall high connectivity and habitat-based gene flow can be detected in the same species (e.g., Reding et al, 2012;Kierepka & Latch, 2016a). Further, disparities between observed patterns in gene flow in populations of the same species can arise from examining landscape factors at differing spatial scales, as the landscape factors important for gene flow may not be fully encompassed or present at all spatial scales (e.g., Anderson et al, 2010;Short Bull et al, 2011;Hapeman et al, 2017;Kierepka et al, 2020).…”

“…Genetic variation in vagile species often is a function of spatial scale where habitat preferences and local adaptation influence gene flow at small spatial scales and high dispersal abilities impact broadscale population structure. Because the landscape variables impacting gene flow are not consistent across spatial scales (e.g., Anderson et al, 2010;Galpern, Manseau & Wilson, 2012;Hapeman et al, 2017), single-scale studies may overlook or underestimate important patterns of gene flow. As a result, recent studies have emphasized the importance of multiscale examinations of spatial genetic structure (Aylward, Murdoch & Kilpatrick, 2020;Burgess & Garrick, 2020;Kierepka et al, 2020).…”