Predicting species occurrences with habitat network models.

Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity [wc]), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc, and nt). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index (lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats

Methodology to account for uncertainties and tradeoffs in pharmaceutical environmental hazard assessment

Many pharmaceutical products find their way into receiving waters, giving rise to concerns regarding their environmental impact. A procedure was proposed that enables ranking of the hazard to aquatic species and human health due to such products. In the procedure, hazard assessment is based on five of the pharmaceutical product’s individual physico-chemical properties. These properties are aggregated using the weighted Euclidian distance as the utility function. The weights and physico-chemical properties are considered as random variables. Physico-chemical property uncertainty criteria are obtained from a literature review. Weight uncertainty is based on a hazard ranking from a panel of experts, the histogram of which is converted into a continuous probability density function using statistical Kernel smoothing technique. The hazard-ranking procedure was applied to a list of common pharmaceuticals used in Switzerland. The procedure is target-specific. Two rankings were presented: One giving priority to environmental protection and the other to human health. For most substances, the hazard rank depends on the target. For the Swiss case study, the ranking procedure led to the conclusion that the hormones ethinylestradiol and testosterone, along with the antibiotic erythromycin A, should be in all cases included in risk assessment methodologies, environmental concentration estimates and regular measurement campaigns. The methodology proposed is flexible and can be extrapolated to other substances and groups of experts

Application of the planning support system URBio

The planning support system URBio is demonstrated via two case studies. Both case studies are located in the canton of Geneva. The first case study is a greenfield planning project, where the goal is to build a new district on former agricultural land. The project responds to the urgent, global challenges of urbanization, and climate change by developing a relatively dense, ecofriendly district. The second case study focuses on a brownfield planning project, that is, the redevelopment of an existing neighborhood. Consequently, the planning support system was adapted to address the challenges and measures specific to urban redevelopment. Through both case studies, the reader will be walked through a typical application process of URBio, illustrating how it is used interactively to explore and narrow the search space, how new questions might come up during this process, and how URBio enables to find further answers. The first case study will illustrate with practical examples the trade-offs between common planning targets such as energy, density, and social aspects (e.g., share of parks). The second case study provides a more in-depth analysis of the current state of the energy system, the limits in achievable densities, and emission saving potentials by replacement of conversion systems and thermal building refurbishments