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 preclinical assessment of a bioartificial pancreas.

Transplantation of insulin secreting cells is regarded as a possible treatment for type 1 diabetes. One major difficulty in this approach is, however, that the transplanted cells are exposed to the patient's inflammatory and autoimmune environment, which originally destroyed their own beta-cells. Therefore, even if a good source of insulin-secreting cells can be identified for transplantation therapy, these cells need to be protected against these destructive influences. The aim of this project was to evaluate, using a clonal mouse beta-cell line, whether genetic engineering of protective genes could be a viable option to allow these cells to survive when transplanted into autoimmune diabetic mice. We demonstrated that transfer of the Bcl-2 anti-apoptotic gene and of several genes specifically interfering with cytokines intracellular signalling pathways, greatly improved resistance of the cells to inflammatory stresses in vitro. We further showed that these modifications did not interfere with the capacity of these cells to correct hyperglycaemia for several months in syngeneic or allogeneic streptozocin-diabetic mice. However, these cells were not protected against autoimmune destruction when transplanted into type 1 diabetic NOD mice. This suggests that in addition to inflammatory attacks by cytokines, autoimmunity very efficiently kills the transplanted cells, indicating that multiple protective mechanisms are required for efficient transplantation of insulin-secreting cells to treat type 1 diabetes.