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Inbreeding is common in nature, and many laboratory studies have documented that inbreeding depression can reduce the fitness of individuals. Demonstrating the consequences of inbreeding depression on the growth and persistence of populations is more challenging because populations are often regulated by density- or frequency-dependent selection and influenced by demographic and environmental stochasticity. A few empirical studies have shown that inbreeding depression can increase extinction risk of local populations. The importance of inbreeding depression at the metapopulation level has been conjectured based on population-level studies but has not been evaluated. We quantified the impact of inbreeding depression affecting the fitness of individuals on metapopulation persistence in heterogeneous habitat networks of different sizes and habitat configuration in a context of natural butterfly metapopulations. We developed a spatial individual-based simulation model of metapopulations with explicit genetics. We used Approximate Bayesian Computation to fit the model to extensive demographic, genetic, and life-history data available for the well-studied Glanville fritillary butterfly (Melitaea cinxia) metapopulations in the Åland islands in SW Finland. We compared 18 semi-independent habitat networks differing in size and fragmentation. The results show that inbreeding is more frequent in small habitat networks, and consequently, inbreeding depression elevates extinction risks in small metapopulations. Metapopulation persistence and neutral genetic diversity maintained in the metapopulations increase with the total habitat amount in and mean patch size of habitat networks. Dispersal and mating behavior interact with landscape structure to determine how likely it is to encounter kin while looking for mates. Inbreeding depression can decrease the viability of small metapopulations even when they are strongly influenced by stochastic extinction-colonization dynamics and density-dependent selection. The findings from this study support that genetic factors, in addition to demographic factors, can contribute to extinctions of small local populations and also of metapopulations. This article is protected by copyright. All rights reserved.

Purpose. The study extends research by Santtila et al. (2008) by investigating the effectiveness of linking cases of serial homicide using behavioural patterns of offenders, analysed through Bayesian reasoning. The study also investigates the informative value of individual behavioural variables in the linking process. Methods. Offender behaviour was coded from official documents relating to 116 solved homicide cases belonging to 19 separate series. The basis of the linkage analyses was 92 behaviours coded as present or absent in the case based on investigator observations on the crime scene. We developed a Bayesian method for linking crime cases and judged its accuracy using cross-validation. We explored the information added by individual behavioural variables, first, by testing if the variable represented purely noise with respect to classification, and second, by excluding variables from the original model, one by one, by choosing the behaviour that had the smallest effect on classification accuracy. Results. The model achieved a classification accuracy of 83.6% whereas chance expectancy was 5.3%. In simulated scenarios of only one and two known cases in a series, the accuracy was 59.0 and 69.2%, respectively. No behavioural variable represented pure noise but the same level of accuracy was achieved by analysing a set of 15, as analysing all 92 variables. Conclusion. The study illustrates the utility of analysing individual behavioural variables through Bayesian reasoning for crime linking. Feasible applied use of the approach is illustrated by the effectiveness of analysing a small set of carefully chosen variables.

International audience; Hybridisation and gene flow can have both deleterious and adaptive consequences for natural populations and species. To better understand the extent of hybridisation in nature and the balance between its beneficial and deleterious outcomes in a changing environment, information on naturally hybridising nonmodel organisms is needed. This requires the characterisation of the structure and extent of natural hybrid zones. Here, we study natural populations of five keystone mound-building wood ant species in the Formica rufa group across Finland. No genomic studies across the species group exist, and the extent of hybridisation and genomic differentiation in sympatry is unknown. Combining genome-wide and morphological data, we demonstrate more extensive hybridisation than was previously detected between all five species in Finland. Specifically, we reveal a mosaic hybrid zone between Formica aquilonia, F. rufa and F. polyctena, comprising further generation hybrid populations. Despite this, we find that F. rufa, F. aquilonia, F. lugubris and F. pratensis form distinct gene pools in Finland. We also find that hybrids occupy warmer microhabitats than the nonadmixed populations of cold-adapted F. aquilonia, and suggest that warm winters and springs, in particular, may benefit hybrids over F. aquilonia, the most abundant F. rufa group species in Finland. In summary, our results indicate that extensive hybridisation may create adaptive potential that could promote wood ant persistence in a changing climate. Additionally, they highlight the potentially significant ecological and evolutionary consequences of extensive mosaic hybrid zones, within which independent hybrid populations face an array of ecological and intrinsic selection pressures.