Uncovering Ecosystem Service Bundles through Social Preferences

Ecosystem service assessments have increasingly been used to support environmental management policies, mainly based on biophysical and economic indicators. However, few studies have coped with the social-cultural dimension of ecosystem services, despite being considered a research priority. We examined how ecosystem service bundles and trade-offs emerge from diverging social preferences toward ecosystem services delivered by various types of ecosystems in Spain. We conducted 3,379 direct face-to-face questionnaires in eight different case study sites from 2007 to 2011. Overall, 90.5% of the sampled population recognized the ecosystem’s capacity to deliver services. Formal studies, environmental behavior, and gender variables influenced the probability of people recognizing the ecosystem’s capacity to provide services. The ecosystem services most frequently perceived by people were regulating services; of those, air purification held the greatest importance. However, statistical analysis showed that socio-cultural factors and the conservation management strategy of ecosystems (i.e., National Park, Natural Park, or a non-protected area) have an effect on social preferences toward ecosystem services. Ecosystem service trade-offs and bundles were identified by analyzing social preferences through multivariate analysis (redundancy analysis and hierarchical cluster analysis). We found a clear trade-off among provisioning services (and recreational hunting) versus regulating services and almost all cultural services. We identified three ecosystem service bundles associated with the conservation management strategy and the rural-urban gradient. We conclude that socio-cultural preferences toward ecosystem services can serve as a tool to identify relevant services for people, the factors underlying these social preferences, and emerging ecosystem service bundles and trade-offs

Injury severity models for motor vehicle accidents: a review

“Permission is granted by ICE Publishing to print one copy for personal use. Any other use of these PDF files is subject to reprint fees" (www.transport-ice.com). http://dx.doi.org/10.1680/tran.11.00026Modelling of traffic accidents injury severity is a complex task. In the last few years the number and variety of studies that analyse injury severity of traffic accidents have increased considerably. In this paper 19 modelling techniques used to model injury severity of traffic accidents where at least a 4-wheeled vehicle is involved have been analysed. The analysis and the comparison between models was performed based on seven criteria (modelling technique, number of records, number of variables, area type, features, injury level and model fit). In general, it is not possible to recommend a method that could be identified as the best one. Each modelling technique has its own limitations and characteristics, awareness of which will help analysts to decide the best method to be used in each particular modelling problem. However, some general conclusions can be established: in most cases the results of models’ fits are found to be satisfactory, though not excellent; in the case of data mining models, accuracy improves with balanced datasets; and no correlation was found to exist between the number of accident records and the number of analysed variables.TRYSE Research Group, Department of Civil Engineering, University of Granada, Spai