DNA from scats combined with capture–recapture modeling: a promising tool for estimating the density of red foxes—a pilot study in ... View Full Text


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Article Info

DATE

2018-11-13

AUTHORS

Per Wegge, Beate Banken Bakke, Morten Odden, Jørund Rolstad

ABSTRACT

In spite of its important role as predator of small game species, estimating the density of red fox Vulpes vulpes has been hampered by the species’ highly variable ranging pattern and elusive behavior. DNA analysis from scats combined with spatially explicit capture–recapture (SECR) modeling might remedy this. In a 50-km2 coniferous forest in southeast Norway, we collected scats on logging roads in late winter. DNA was extracted, amplified, and genotyped using 11 microsatellite markers. Of 184 samples collected, 126 were genotyped successfully, of which 46 (36.5%) produced individual genetic profiles. Twenty-five of these were different individuals: 13 females and 12 males. Nine of them were identified in multiple scats; mean recapture rate among all was 1.8/animal. Applying a conventional capture–recapture model (CAPWIRE) to the genotyped samples, 36 (95% CI 26–52) different individuals were estimated to have been present in the area during the sampling period. For estimating population density, we constructed three differently sized occupancy areas based on distances between recaptures, viz. ½ and 1/1 mean maximum distance moved (MMDM) and the local convex hull home range method (LoCoH). Areas varied from 60 km2 (½MMDM) to 112 km2 (MMDM), producing density estimates of 0.60 and 0.32 foxes/km2, respectively; the 95% LoCoH range method produced an estimate of 0.44 animals/km2. Based on SECR modeling, the density was estimated at 0.38 (95% CI 0.21–0.70) animals/km2. Smaller confidence intervals are expected with more appropriate sampling design than used in this pilot study. More... »

PAGES

147-154

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13364-018-0408-7

DOI

http://dx.doi.org/10.1007/s13364-018-0408-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1109888592


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