Genetic Connectivity among Populations of the Threatened Bog Turtle (Glyptemys muhlenbergii) and the Need for a Regional Approach to Turtle Conservation

The threatened Bog Turtle (Glyptemys muhlenbergii) is considered among the most sedentary of turtles, yet with population sizes generally below 50 individuals, gene flow among populations is clearly necessary to maintain healthy levels of genetic diversity. Therefore, designing effective reserve networks for this species will require clarification of the rates of among-population gene flow over several spatial scales. We obtained genetic samples from a complex of 11 Bog Turtle populations within the Berkshire-Taconic region of Massachusetts and New York, and all individuals (n  =  234) were genotyped across 15 microsatellite loci. Average multi-generation dispersal rates were inferred from population-level differences in allele frequencies using an approximate-likelihood approach, and recent dispersal rates were inferred using genetic assignment algorithms. Over small geographic distances (average inter-fen distance of ca. 1 km), among-population dispersal rates historically averaged between 0.25 and 0.5 effective migrants per population per year (ca. 1% of each population dispersing each year), and these dispersal rates appear to have persisted in recent decades. Over larger geographic distances (≥10 km), we infer that Bog Turtle populations in the Berkshire-Taconic region have experienced low rates of gene flow among populations according to a “stepping-stone” model. We conclude that (1) Bog Turtle populations with nearest-neighbor distances of <2 km should be managed as inter-connected demographic units, (2) dispersal movements among adjacent populations may enhance regional population stability, and (3) gene flow over larger spatial and temporal scales probably requires dispersal among “stepping stone” habitats that may not harbor viable populations. Regional conservation planning for these and other small-bodied, endangered turtles should focus on establishing and maintaining networks of loosely connected population complexes to mimic historical connectivity patterns.