Career adaptability profiles and their relationship to adaptivity and adapting

Research on career adaptability predominantly uses variable-centered approaches that focus on the average effects in terms of the predictors and outcomes within a given sample. Extending this research, the present paper used a person-centered approach to determine whether subgroups with distinct adaptability profiles in terms of concern, control, curiosity and confidence can be identified. We also explored the relationship between the various adaptability profiles and adapting (career planning, career decision-making difficulties, career exploration, and occupational self-efficacy beliefs) and adaptivity (core self-evaluations and proactivity). Using latent profile analysis, we found distinct adaptability profiles among 350 German university students. Students with different profiles differed significantly in their levels of adapting. This finding was confirmed in a second study of 1226 students selected from the same population. In both samples, the adaptability profiles differed mainly in terms of their adaptability levels but not their shape. Moreover, in both samples, the students whose profiles indicated generally higher adaptability showed more adapting compared with the students whose profiles indicated generally lower adaptability. Study 2 also showed that students with higher-adaptability profiles showed significantly higher adaptivity. The results suggest that level effects dominate adaptability profiles, implying the existence of a general adaptability factor within university students that is meaningfully related to adapting and adaptivity.

Using multiple landscape genetic approaches to test the validity of genetic clusters in a species characterized by an isolation-by-distance pattern

Bayesian clustering methods are typically used to identify barriers to gene flow, but they are prone to deduce artificial subdivisions in a study population characterized by an isolation-by-distance pattern (IbD). Here we analysed the landscape genetic structure of a population of wild boars (Sus scrofa) from south-western Germany. Two clustering methods inferred the presence of the same genetic discontinuity. However, the population in question was characterized by a strong IbD pattern. While landscape-resistance modelling failed to identify landscape features that influenced wild boar movement, partial Mantel tests and multiple regression of distance matrices (MRDMs) suggested that the empirically inferred clusters were separated by a genuine barrier. When simulating random lines bisecting the study area, 60% of the unique barriers represented, according to partial Mantel tests and MRDMs, significant obstacles to gene flow. By contrast, the random-lines simulation showed that the boundaries of the inferred empirical clusters corresponded to the most important genetic discontinuity in the study area. Given the degree of habitat fragmentation separating the two empirical partitions, it is likely that the clustering programs correctly identified a barrier to gene flow. The differing results between the work published here and other studies suggest that it will be very difficult to draw general conclusions about habitat permeability in wild boar from individual studies.