Article

Estimating population size and trends of the Swedish brown bear Ursus arctos population

[ "Jonas Kindberg & Göran Ericsson, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, SE-90183 Umeå, Sweden - e-mail addresses: (Jonas Kindberg)
Wildlife Biology (Impact Factor: 1.07). 07/2011; DOI: 10.2981/10-100

ABSTRACT Estimating population size and trends are key issues in the conservation and management of large carnivores. The rebounding brown bear Ursus arctos population in Sweden is monitored by two different systems, both relying on voluntary resources. Population estimates have been calculated using Capture-Mark-Recapture methods, based on DNA-based scat surveys in five of the six Swedish counties with established bear populations. A total of 1,358 genotypes were identified using DNA extracted from collected scats. An independent ongoing programme, the Large Carnivore Observation Index (LCOI), was initiated in 1998. The LCOI uses effort-corrected observations of bears by moose Alces alces hunters during the moose hunt (> 2 million observation hours/year) and has shown a good correlation with relative population density of bears using the DNA-based method. From this, we have calculated population trends during the period 1998-2007. Using an exponential model, we estimated the yearly increase in the bear population to be 4.5% at the national level, varying between 0 and 10.2% in different counties. We used the regional population estimates and the trends from the LCOI, taking the variation from both systems into account using parametric bootstrapping, to calculate the regional as well as the national population size in Sweden in fall 2008. In one case (the northernmost county; Norrbotten) a DNA-scat survey was lacking, so we used assumptions based on data from the neighbouring county to estimate population size. We estimated the Swedish brown bear population to be 3,298 individuals (2,968-3,667; 95% confidence intervals) in 2008. Our results suggest that reliable information, necessary for the management of the brown bear population can be obtained from volunteers using standardised methods.

Full-text

Available from: Jon E Swenson, Jun 12, 2015
0 Followers
 · 
527 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Baseline information is lacking for the Syrian Brown Bear across the sub-species range, making it difficult to assess at any level. In the present investigation, our goal was to illustrate the population status of the Brown Bear in the Golestanak area, northern Iran, based on field surveys we conducted during the summers of 2011 and 2012. We counted a total of 30 and 21 bears in two consecutive years, with family groups consisting of more than half of the identified individuals. Sub-adults had the lowest contribution among the observed individuals, just below 10%, which may be due to their high dispersal behaviour to avoid adults. Our results provide a foundation for future systematic baseline investigations on the population status of the brown bear in northern Iran, which can be used in management programs. Aside from improving monitoring efforts within key habitats of the species, enhancing conservation efforts to secure the population is essential to safeguard this female core area.
    01/2015; 7(1). DOI:10.11609/JoTT.o3708.6796-9
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Genetic methods based on sampling of feces and hairs to study brown bears have become the method of choice for many wildlife researchers and managers. Feces and hairs are the most common sample material for DNA identification of individual bears. While the collection of feces and hairs in the field is carried out in an opportunistic manner, hair-trapping can be applied systematically at specific locations. We have here tested a novel systematic method based on hair sampling on power poles. The method relies on the specific behavior of bears to mark, scratch, bite and scrub on power poles, and by this also leave some hairs behind. During late summer and autumn we have investigated 215 power poles in the Pasvik Valley and sampled 181 hair samples in 2013 and 57 in 2014. A total of 17.3% of the samples collected in 2013 and 12.3% in 2014 were positive on brown bear DNA. Our success rates are comparable to other studies, however, DNA quality/content in the hair samples was generally low. Based on other studies, the method could be improved by sampling during spring and early summer and to use shorter frequencies of 2 to 4 weeks between each sampling. Based on our results and previous studies, we can conclude that this sampling technique should be improved by the development of a more accurate and frequent sampling protocol. Hair sampling from power poles may then lead to improved potential to collect valuable samples and information, which would be more difficult to collect otherwise.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Accurate and precise estimates of population size are critical for effective management but can be particularly difficult to achieve for small populations of large carnivores. We approached this challenge by integrating multiple noninvasive data sources into a DNA-based mark–recapture framework to estimate the abundance of the small and endangered Apennine brown bear population. To improve sample size and coverage, we collected hair samples from June to September 2011 by concurrently using 4 noninvasive sampling methods: intensive hair-snagging (forty-three 5 × 5-km cells and five 12-day sampling sessions) plus secondary sampling methods (bear rub trees, alpine buckthorn aggregations, and incidental sampling). Following marker selection based on tissue samples from 55 Apennine bears, we used 13 microsatellites (plus gender) and quality assurance protocols to identify multilocus genotypes from hair samples. We used Huggins closed models in program MARK to estimate population size, which allowed us to account for spatial, temporal, and demographic components of heterogeneity in secondary sampling methods. Based on 529 analyzed hair samples, 80.5% of which yielded high-confidence scores for all markers, we achieved a rather precise (CV = 7.9%) population estimate of 51 bears (95% CI = 47–66) including cubs. Compared to a previous survey in 2008, our results provide evidence that the Apennine brown bear population has not been declining in recent years. Additionally, the relatively high (closure corrected) density (39.7 bears/1,000 km 2
    Journal of Mammalogy 02/2015; 96(1):206-220. DOI:10.1093/jmamma/gyu029 · 2.23 Impact Factor