title: The problem of estimating recent genetic connectivity in a changing world.
abstract: Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent-based method (Migrate-n) and a disequilibrium-based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over-estimated recent migration rates; (ii) the coalescent-based method (Migrate-n) provided better estimates of recent migration rate than the disequilibrium-based method (BayesAss); (iii) the coalescent-based method did not accurately reflect long-term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic-connectivity changes over time could lead to inaccurate conclusions.
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Toronto, 25 Harbord Street, Toronto, ON, M5S 3G5, Canada.
authors.forename: Pasan
authors.initials: P
authors.lastname: Samarasin
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Toronto, 25 Harbord Street, Toronto, ON, M5S 3G5, Canada.
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Shuter
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street, Toronto, ON, M5S 3B2, Canada.
authors.forename: Stephen I
authors.initials: SI
authors.lastname: Wright
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Toronto, 25 Harbord Street, Toronto, ON, M5S 3G5, Canada.
authors.forename: F Helen
authors.initials: FH
authors.lastname: Rodd
mesh_terms: D003247:Conservation of Natural Resources; D004463:Ecology; D017753:Ecosystem; D005828:Genetics, Population; D011157:Population Dynamics
keywords: BayesAss; Migrate-n; coalescent; coalescente; conectividad histórica; contemporary migration; fragmentación; fragmentation; historical connectivity; migración; migración contemporánea; migration