Scale-dependent effects of a heterogeneous landscape on genetic differentiation in the Central American squirrel monkey (Saimiri oerstedii).
Landscape genetic studies offer a fine-scale understanding of how habitat heterogeneity influences population genetic structure. We examined population genetic structure and conducted a landscape genetic analysis for the endangered Central American Squirrel Monkey (Saimiri oerstedii) that lives in the fragmented, human-modified habitats of the Central Pacific region of Costa Rica. We analyzed non-invasively collected fecal samples from 244 individuals from 14 groups for 16 microsatellite markers. We found two geographically separate genetic clusters in the Central Pacific region with evidence of recent gene flow among them. We also found significant differentiation among groups of S. o. citrinellus using pairwise F(ST) comparisons. These groups are in fragments of secondary forest separated by unsuitable "matrix" habitats such as cattle pasture, commercial African oil palm plantations, and human residential areas. We used an individual-based landscape genetic approach to measure spatial patterns of genetic variance while taking into account landscape heterogeneity. We found that large, commercial oil palm plantations represent moderate barriers to gene flow between populations, but cattle pastures, rivers, and residential areas do not. However, the influence of oil palm plantations on genetic variance was diminished when we restricted analyses to within population pairs, suggesting that their effect is scale-dependent and manifests during longer dispersal events among populations. We show that when landscape genetic methods are applied rigorously and at the right scale, they are sensitive enough to track population processes even in species with long, overlapping generations such as primates. Thus landscape genetic approaches are extremely valuable for the conservation management of a diverse array of endangered species in heterogeneous, human-modified habitats. Our results also stress the importance of explicitly considering the heterogeneity of matrix habitats in landscape genetic studies, instead of assuming that all matrix habitats have a uniform effect on population genetic processes.
Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, New York, United States of America. mblair1@amnh.org
Mary E
ME
Blair
Don J
DJ
Melnick
D000818:Animals; D001499:Bayes Theorem; D044822:Biodiversity; D016000:Cluster Analysis; D003364:Costa Rica; D017753:Ecosystem; D005243:Feces; D051456:Gene Flow; D014644:Genetic Variation; D005828:Genetics, Population; D005838:Genotype; D005843:Geography; D018895:Microsatellite Repeats / Q000235:genetics; D008957:Models, Genetic; D012453:Saimiri / Q000235:genetics*; D017422:Sequence Analysis, DNA