For conservation of wild species, it is important to understand how landscape change and land management can affect gene flow and movement. Landscape genetic analyses provide a powerful approach to infer effects of various landscape factors on gene flow, thereby informing conservation actions. The Persian squirrel is a keystone species in the woodlands and oak forests of Western Asia, where it has experienced recent habitat loss and fragmentation. We conducted landscape genetic analyses of individuals sampled in the northern Zagros Mountains of Iran (provinces of Kurdistan, Kermanshah, and Ilam), focusing on evaluation of isolation by distance (IBD) and isolation by resistance (IBR), using 16 microsatellite markers. The roles of geographical distance and landscape features including roads, rivers, developed areas, farming and agriculture, forests, lakes, plantation forests, rangelands, shrublands and rocky areas of varying canopy cover, and swamp margins on genetic structure were quantified using individual-based approaches and resistance surface modelling. We found a significant pattern of IBD but only weak support for an effect of forest cover on genetic structure and gene flow. It seems that geographical distance is an important factor limiting the dispersal of the Persian squirrel in this region. The results of the current study inform ongoing conservation programs for the Persian squirrel in the Zagros oak forest.

Study site and sampling

Individuals of the Persian squirrel were sampled in the north of the Zagros Forest in Iran (2016–2018) (Kurdistan, Kermanshah and Ilam; Fig. 1). Tissues including small pieces of fur, skin, muscle, and ear were sampled from live, captured animals or corpses, and the geographical coordinates of sampling points were recorded. For sampling of live squirrels, conducted in cooperation with the Department of Environment in Iran, live Persian squirrels illegally taken by hunters or local people were sampled, and all live squirrels were released after capture (Asadi Aghbolaghi et al. 2019). We only included in our dataset samples from animals whose location of capture was certain. Tissues were preserved in ethanol at -20 °C. No samples from zoos were considered in this research because of the risk of hybridization in captivity (Taberlet et al. 1999; Fig 1). A total of 38 individuals were included in this study, all identified previously as belonging to the northern Zagros population group based on mitochondrial and nuclear gene sequences (population group G4 in Asadi Aghbolaghi et al. 2019).

DNA extraction and microsatellite amplification

DNA was extracted from tissue samples using a DNeasy Blood and Tissue Kit (Qiagen, Germantown, MD), with a final elution volume of 50 μL. We amplified 19 dinucleotide microsatellite loci (Scv1, Scv3, Scv4, Scv6, Scv8, Scv9, Scv12, Scv13, Scv14, Scv15, Scv16, Scv18, Scv19, Scv20, Scv23, Scv24, Scv25, Scv27, Scv31, Scv32; Hale et al. 2001a). Microsatellite loci were amplified individually in 15 μL reactions containing 0.5 μL template DNA, 1 X AmpliTaq buffer, 1.5 mM MgCl2, 0.75 mM each dNTP, 0.5 mM each primer, and 0.2 U AmpliTaq DNA polymerase (Applied Biosystems, Foster City, CA) under the following cycling conditions: 95°C for 2 min; 35 cycles of 94°C for 15 s, annealing temperature (48, 52, or 54°C) for 15 s (see Hale et al. 2001a), and 72°C for 15 s; followed by 72°C for 10 min. PCR amplifications were performed in a PTC 0200 DNA Engine Cycler (Bio-Rad, Hercules, CA). Forward primers were labeled with a fluorescent dye and PCR products were visualized and sized on an Applied Biosystems 3730S capillary DNA analyzer, under standard run conditions, with 500 LIZ as the internal size standard. Electropherograms generated by the DNA analyzer were scored using GeneMarker software (V 2.6.3) and all genotypes were checked manually (Hulce et al. 2011).

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