Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Development and validation of the Transition to Retirement Questionnaire

The aim of this study was to present the initial validation of a new questionnaire, the Transition to Retirement Questionnaire (TRQ) and to study its relationship with resistance to change and personality dimensions. Based on Schlossberg's typology of the retired, the TRQ is designed to assess five dimensions related to personal perceptions of transition to retirement, retirement, and personal plans and activities. The sample consisted of 1,054 professionally active or retired adults from the Swiss French-speaking Canton of Vaud. Exploratory principal components and confirmatory factor analyses highlighted a five-factor solution that fit coherently with Schlossberg's typology. Moreover, TRQ dimensions were related to resistance to change tendencies and personality dimensions. The TRQ seems to be an interesting tool for use in research but also for interventions with young retirees or people preparing for retirement.

Psychometrics of the Dyadic Coping Inventory in three language groups

This article introduces the Dyadic Coping Inventory (DCI; Bodenmann, 2008) and aims (1) to investigate the reliability and aspects of the validity of the Italian and French versions of the DCI, and (2) to replicate its factor structure and reliabilities using a new Swiss German sample. Based on 216 German-, 378 Italian-, and 198 French-speaking participants, the factor structure of the original German inventory was able to be replicated by using principal components analysis in all three groups after excluding two items in the Italian and French versions. The latter were shown to be as reliable as the German version with the exception of the low reliabilities of negative dyadic coping in the French group. Confirmatory factor analyses provided additional support for delegated dyadic coping and evaluation of dyadic coping. Intercorrelations among scales were similar across all three languages groups with a few exceptions. Previous findings could be replicated in all three groups, showing that aspects of dyadic coping were more strongly related to marital quality than to dyadic communication. The use of the dyadic coping scales in the actor-partner interdependence model, the common fate model, and the mutual influence model is discussed.