Estimating Population Size of Elusive Animals with DNA from Hunter‐Collected Feces: Four Methods for Brown Bears

• Published in: Conservation Biology
• Main Authors: BELLEMAIN, EVA, SWENSON, JON E., TALLMON, DAVID, BRUNBERG, SVEN, TABERLET, PIERRE
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2005
• Subjects: Ursus arctos
• Online Access: http://dx.doi.org/10.1111/j.1523-1739.2005.00549.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1523-1739.2005.00549.x; http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1523-1739.2005.00549.x/fullpdf

Abstract: Noninvasive genetic methods can be used to estimate animal abundances and offer several advantages over conventional methods. Few attempts have been made, however, to evaluate the accuracy and precision of the estimates. We compared four methods of estimating population size based on fecal sampling. Two methods used rarefaction indices and two were based on capture‐mark‐recapture (CMR) estimators, one combining genetic and field data. Volunteer hunters and others collected 1904 fecal samples over 2 consecutive years in a large area containing a well‐studied population of brown bears ( Ursus arctos ). On our 49,000‐km 2 study area in south‐central Sweden, population size estimates ranged from 378 to 572 bears in 2001 and 273 to 433 bears in 2002, depending on the method of estimation used. The estimates from the best model in the program MARK appeared to be the most accurate, based on the minimum population size estimate from radio‐marked bears in a subsection of our sampling area. In addition, MARK models included heterogeneity and temporal variation in detection probabilities, which appeared to be present in our samples. All methods, though, incorrectly suggested a biased sex ratio, probably because of sex differences in detection probabilities and low overall detection probabilities. The population size of elusive animals can be estimated reliably over large areas with noninvasive genetic methods, but we stress the importance of an adequate and well‐distributed sampling effort. In cases of biased sampling, calibration with independent estimates may be necessary. We recommend that this noninvasive genetic approach, using the MARK models, be used in the future in areas where sufficient numbers of volunteers can be mobilized.