TY - JOUR A1 - Jung, Jana T1 - Does youth matter? BT - long-term effects of youth characteristics on the diversity of partnership trajectories JF - Longitudinal and life course studies : LLCS ; international journal / Society for Longitudinal and Life Course Studies N2 - Previous research has mainly concentrated on the study of certain transitions and the influence of economic and socio-structural factors on partnership status. From a life course perspective, it remains unclear how factors anchored in youth are related to the diversity of partnership biographies. Arguing that individuals act and behave based on prior experiences and resources, I analyse how personal and social resources as well as socio-demographic characteristics influence the turbulence of longitudinal partnership trajectories. Using a longitudinal dataset from the German LifE Study, I examine partnership histories from the ages 16 to 45. The results suggest that in addition to the influence of an individual's socio-demographic placement (for example, religious commitment and regional living conditions), personal and social resources anchored in youth also have a long-term effect on the diversity of partnership trajectories. This article shows that women are influenced by their attitudes towards marriage and family, while men are influenced by their attitudes towards their careers. KW - partnership trajectories KW - youth characteristics KW - life course KW - sequence KW - analysis KW - regression tree Y1 - 2021 U6 - https://doi.org/10.1332/175795920X15980339169308 SN - 1757-9597 VL - 12 IS - 2 SP - 201 EP - 225 PB - Longview CY - London ER - TY - JOUR A1 - Imholt, Christian A1 - Reil, Daniela A1 - Eccard, Jana A1 - Jacob, Daniela A1 - Hempelmann, Nils A1 - Jacob, Jens T1 - Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus) JF - Pest management science N2 - BACKGROUND Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. RESULTS Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. CONCLUSION Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. (c) 2014 Society of Chemical Industry KW - climate change KW - population dynamics KW - bank vole KW - regression tree KW - outbreak Y1 - 2015 U6 - https://doi.org/10.1002/ps.3838 SN - 1526-498X SN - 1526-4998 VL - 71 IS - 2 SP - 166 EP - 172 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Schroeter, Kai A1 - Kreibich, Heidi A1 - Vogel, Kristin A1 - Riggelsen, Carsten A1 - Scherbaum, Frank A1 - Merz, Bruno T1 - How useful are complex flood damage models? JF - Water resources research N2 - We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely. KW - floods KW - damage KW - model validation KW - Bayesian networks KW - regression tree Y1 - 2014 U6 - https://doi.org/10.1002/2013WR014396 SN - 0043-1397 SN - 1944-7973 VL - 50 IS - 4 SP - 3378 EP - 3395 PB - American Geophysical Union CY - Washington ER -