An empirical perspective for understanding climate change impacts in Switzerland

Regional Environmental Change - Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans....     

Assessing alpine plant vulnerability to climate change: a modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Speciation of five arsenic species (arsenite, arsenate, MMAAV, DMAAV and AsBet) in different kind of water by HPLC-ICP-MS

A method using Ion Chromatography hyphenated to an Inductively Coupled Plasma-Mass Spectrometer has been developed to accurately determine arsenite (As(III)), arsenate (As(V)), mono-methylarsonic acid (MMAA(V)), dimethylarsinic acid (DMAA(V)) and arsenobetaine (AsBet) in different water matrices. The developed method showed a high sensitivity with detection limits for each arsenic species close to 0.4pg injected. Arsenite and arsenate were the major species found in surface and well waters, but AsBet and DMAA(V) were found in some surface waters, which has never been reported before, while in some natural mineral waters located in volcanic region, the arsenic content exceeded the maximal admissible arsenic content by European legislation standards and the predominant form was As(V).     

Prenatal diagnosis of respiratory chain deficiency by direct mutation screening

Respiratory chain deficiency (RCD) is responsible for a clinically heterogeneous group of early-onset untreatable disorders. Enzymological prenatal diagnosis (PD) can only be offered to a fraction of families. Moreover, due to the two-fold genetic origin of the respiratory chain (nuclear and mitochondrial DNA) and owing to the large number of nuclear genes involved in the respiratory chain assembly, maintenance and functioning, the identification of the disease causing gene in a given family remains challenging. Here, we report on PD of RCD by direct screening of NDUFV1, SDH-Fp, SCO1 and SURF1 mutations in five unrelated families with complex I, II and IV deficiency, respectively. The identification of the disease-causing gene in a given family with RCD is a major issue to provide both adequate genetic counselling and early, reliable PD. Copyright © 2001 John Wiley & Sons, Ltd.     

Mapping wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France

Every year, more than 50,000 wildland fires affect about 500,000 ha of vegetation in southern European countries, particularly in wildland-urban interfaces (WUI). This paper presents a method to characterize and map WUIs at large scales and over large areas for wildland fire prevention in the South of France. Based on the combination of four types of building configuration and three classes of vegetation structure, 12 interface types were classified. Through spatial analysis, fire ignition density and burned area ratio were linked with the different types of WUI. Among WUI types, isolated WUIs with the lowest housing density represent the highest level of fire risk.     

Towards a multidisciplinary and integrated strategy in the assessment of adverse health effects related to air pollution: the case study of Cracow (Poland) and asthma

Complex interaction between anthropogenic activities, air quality and human health in urban areas, such as in Cracow sustains the need for the development of an interdisciplinary and integrated risk-assessment methodology. In such purpose, we propose a pilot study performed on asthmatics and based on a combined use of a biomarker, such as metallothionein 2A (MT-2A) in the characterization of human exposure to one or a mixture of pollutants and of Geographical Information Systems (G.I.S.) which integrates climatic and urban anthropogenic parameters in the assessment of spatio-temporal dispersion of air pollutants. Considering global incidence of air pollution on asthma and on peripheral blood lymphocytes MT-2A expression should provide a complementary information on biological risks linked to urban anthropogenic activities. Such study would help for the establishment of a sustainable development in urban areas that can maintain the integrity of air quality and preserve human health.     

Specification of the logit model: The case of valuation of nonmarket goods

We address the proper specification of the logit model for estimation of nonmarket commodity demand. Economic theory is used to show the conditions which must be met by the logit functional form if it is to yield valid estimates of welfare change measures and demand relationships. An empirical example is used to illustrate the argument. Recreational boating data were collected using the contingent valuation method (CVM) in Texas. In one instance the demand curve is positively sloped due to the specific functional form chosen. The estimated demand curve for the theoretically preferred functional form has the expected negative slope.