Bayesian clustering techniques and progressive partitioning to identify population structuring within a recovering otter population in the UK

Abstract

Summary1. After a major decline, the UK otter Lutra lutra population is now recovering in its known strongholds (northern England, Wales and Borders and southwest England) and also in central England where the population had become small, fragmented and was reinforced with captive bred individuals. Bayesian clustering and GIS are used here to identify the genetic structure of the UK otter population and to assess expansion from strongholds and the contribution of introduced otters. Large carnivores have recently started to recolonize landscapes where they were formerly absent, especially in developed countries and understanding the expansion of these populations is essential for informing conservation management, linking fragmented populations and re-establishing gene flow. 2. Three Bayesian clustering techniques were used (structure, geneland spatial and baps4 spatial) to estimate the number of otter populations (K). A novel progressive partitioning approach was tested to identify genetic substructuring at various hierarchical levels using successive partitions at K = 2. 3. Four regional populations were identified that reflect known population history. Isolated populations in southwest England and in Wales and its borders showed the lowest levels of genetic diversity. Higher diversity and private alleles in northern and central England reflect the proximity to genetically diverse Scottish populations and the positive effect of reintroductions. 4. Progressive partitioning was used to produce a more detailed analysis, by allowing comparison and combination of clusters identified by different techniques and by avoiding the subjective estimation and choice of K. 5. Synthesis and applications. Although the otter population is increasing, our data show little sign of population expansion from the stronghold regions into central England, instead reflecting the success of population reinforcement in this area. Our progressive partitioning approach allows the identification of fine-scale substructure (11 groups) that enables the prioritization of management effort including identifying barriers to dispersal within and between populations and monitoring of introduced individuals.

Indirect effects of bioinvasions in Yellowstone Lake: The response of river otters to declines in native cutthroat trout

“…In addition, a weak but significant deviation from HWE was detected across the pooled loci (p = 0.04). Multilocus F IS was 0.07 (p = 0.03), suggesting some inbreeding within the Yellowstone Lake population or a possible Wahlund effect (Hobbs et al, 2011). We identified a single panmictic population from STRUCTURE analyses and evidence of a bottleneck based on heterozygote excess under the IAM model (Wilcoxon test; p = 0.007) and TPM model (Wilcoxon test; p = 0.015), but not the SMM model (Wilcoxon test; p = 0.109).…”

“…Interestingly, studies of the Eurasian otter (e.g., Randi et al, 2003;Hobbs et al, 2011) and giant otter (Pteronura brasiliensis; Pickles et al, 2012) did not detect bottlenecks in populations known to have recently declined. On the other hand, Hájková et al (2007) identified bottlenecks in otter populations from the Czech and Slovak Republics and suggested they arose from large declines in abundance over a short duration.…”

Spatial and seasonal factors are key determinants in the aggregation of helminths in their definitive hosts: Pseudamphistomum truncatum in otters (Lutra lutra)

“…Pseudamphistomum truncatum were identified morphologically (following Yamaguti, 1971). The location of each otter was assigned to an ecologically relevant Environment Agency region of the UK (Anglian Region, Wales, Southwest, Midlands, Northwest, Northeast, South of England, Thames, UK) delineated by river catchment drainage boundaries (see Sherrard-Smith et al, 2009), which to a large extent mirrors genetic structure of otters in the UK (Hobbs et al, 2011). Month and year of host death, sex, age class (adult or sub-adult), length and body mass were recorded.…”

Genetic structure of captive and free-ranging okapi (Okapia johnstoni) with implications for management

“…This was done to further investigate genetic structure in the wild and to attempt to assign the founder individuals to a part of the wild okapi distribution. Individuals were assigned to a given population if they had greater than or equal to 0.5 probability of assignment to that population (Hobbs et al 2011). GENELAND was run with K = 1-10, 500,000 iterations, uncorrelated allele frequencies and six independent runs.…”