A simple linear model for estimating ozone AOT40 at forest sites from raw passive sampling data

A rapid, empirical method is described for estimating weekly AOT40 from ozone concentrations measured with passive samplers at forest sites. The method is based on linear regression and was developed after three years of measurements in Trentino (northern Italy). It was tested against an independent set of data from passive sampler sites across Italy. It provides good weekly estimates compared with those measured by conventional monitors (0.85 ≤R(2)≤ 0.970; 97 ≤ RMSE ≤ 302). Estimates obtained using passive sampling at forest sites are comparable to those obtained by another estimation method based on modelling hourly concentrations (R(2) = 0.94; 131 ≤ RMSE ≤ 351). Regression coefficients of passive sampling are similar to those obtained with conventional monitors at forest sites. Testing against an independent dataset generated by passive sampling provided similar results (0.86 ≤R(2)≤ 0.99; 65 ≤ RMSE ≤ 478). Errors tend to accumulate when weekly AOT40 estimates are summed to obtain the total AOT40 over the May-July period, and the median deviation between the two estimation methods based on passive sampling is 11%. The method proposed does not require any assumptions, complex calculation or modelling technique, and can be useful when other estimation methods are not feasible, either in principle or in practice. However, the method is not useful when estimates of hourly concentrations are of interest.     

Geographic distribution and environmental characterization of livestock production systems in Eastern Africa

The central role played by livestock in the livelihoods of rural households in the developing world is seldom fully appreciated by policy makers, development agencies and donors. Knowledge gaps in the geographic distribution and environmental determinants of farming systems, especially if viewed through the livestock lens, compound this problem. We have produced a map of pastoral, agro-pastoral and mixed farming systems across Eastern Africa, by analysing datasets collected in the framework of livelihood analysis. Input data were gathered between 2000 and 2007 by various emergency and development agencies for Djibouti, Eritrea, Kenya, Somalia, Uganda and parts of Ethiopia and Sudan. A quantitative definition of the production systems is adopted, based on the ratio of livestock- to crop-derived income. The resulting livelihood-based map of livestock production systems was compared through correspondence analysis to an alternative livestock production systems map, produced independently from environmental data. Convergence between the two mapping approaches was evident. The geographic distribution of the livestock production systems was also modelled using multivariate analysis of remotely sensed and other geospatial datasets. Models show high statistical accuracy, and were thus used to fill the gaps in the observed distribution of livestock production systems. Finally, selected environmental factors underpinning the systems (agro-climatology, human and livestock populations and land cover) were analysed in detail, enabling the livestock production systems to be characterized in terms of them. The regional scope of the map, as well as its direct link with a vast amount of livelihood information, render it a valuable tool for a range of development and research applications, including those related to global change.     

The quantitative real-time PCR applications in the monitoring of marine harmful algal bloom (HAB) species

In the last decade, various molecular methods (e.g., fluorescent hybridization assay, sandwich hybridization assay, automatized biosensor detection, real-time PCR assay) have been developed and implemented for accurate and specific identification and estimation of marine toxic microalgal species. This review focuses on the recent quantitative real-time PCR (qrt-PCR) technology developed for the control and monitoring of the most important taxonomic phytoplankton groups producing biotoxins with relevant negative impact on human health, the marine environment, and related economic activities. The high specificity and sensitivity of the qrt-PCR methods determined by the adequate choice of the genomic target gene, nucleic acid purification protocol, quantification through the standard curve, and type of chemical detection method make them highly efficient and therefore applicable to harmful algal bloom phenomena. Recent development of qrt-PCR-based assays using the target gene of toxins, such as saxitoxin compounds, has allowed more precise quantification of toxigenic species (i.e., Alexandrium catenella) abundance. These studies focus only on toxin-producing species in the marine environment. Therefore, qrt-PCR technology seems to offer the advantages of understanding the ecology of harmful algal bloom species and facilitating the management of their outbreaks.     

The legacy of large dams in the United States

The sustainability of large dams has been questioned on several grounds. One aspect that has been less explored is that the development of dams and reservoirs often enables agricultural expansion and urban growth, which in turn increase water consumption. As such, dam development influences, while being influenced by, the spatial and temporal distribution of both supply and demand of water resources. In this paper, we explore the interplay between large dams, patterns of population growth and agricultural expansion in the United States over the past two centuries. Based on a large-scale analysis of spatial and temporal trends, we identify three distinct phases, in which different processes dominated the interplay. Then, we focus on agricultural water use in the Southwest region (Arizona, California and Nevada) and explore chicken-and-egg dynamics where water supply partly meets and partly fuels water demand. Lastly, we show that the legacy of dams in the United States consists of a lock-in condition characterized by high levels of water consumption, especially in the Southwest, which leads to severe water crises and groundwater overexploitation when droughts occur.     

Development of SuperSmart Grids for a more efficient utilisation of electricity from renewable sources

If Europe is serious about reaching its target to keep global mean temperature increase below 2 °C, it must strive for a 100% renewable electricity system by 2050. The SuperSmart Grid approach combines what is often perceived as two exclusive alternatives: wide area power generation and decentralised power generation. We argue that by combining these, in fact, complementary measures, it is possible to address the crucial issue of renewable generation—fluctuating supply—in a comprehensive as well as in a technologically and economically viable manner. Thus, the SuperSmart Grid simultaneously can contribute to energy security, climate security, social security, and national security.