A high-resolution soil erosion risk map of Switzerland as strategic policy support system

Soil erosion models and soil erosion risk maps are often used as indicators to assess potential soil erosion in order to assist policy decisions. This paper shows the scientific basis of the soil erosion risk map of Switzerland and its application in policy and practice. Linking a USLE/RUSLE-based model approach (AVErosion) founded on multiple flow algorithms and the unit contributing area concept with an extremely precise and high-resolution digital terrain model (2 m × 2 m grid) using GIS allows for a realistic assessment of the potential soil erosion risk, on single plots, i.e. uniform and comprehensive for the agricultural area of Switzerland (862,579 ha in the valley area and the lower mountain regions). The national or small-scale soil erosion prognosis has thus reached a level heretofore possible only in smaller catchment areas or single plots. Validation was carried out using soil loss data from soil erosion damage mappings in the field from long-term monitoring in different test areas. 45% of the evaluated agricultural area of Switzerland was classified as low potential erosion risk, 12% as moderate potential erosion risk, and 43% as high potential erosion risk. However, many of the areas classified as high potential erosion risk are located at the transition from valley to mountain zone, where many areas are used as permanent grassland, which drastically lowers their current erosion risk. The present soil erosion risk map serves on the one hand to identify and prioritise the high-erosion risk areas, and on the other hand to promote awareness amongst farmers and authorities. It was published on the internet and will be made available to the authorities in digital form. It is intended as a tool for simplifying and standardising enforcement of the legal framework for soil erosion prevention in Switzerland. The work therefore provides a successful example of cooperation between science, policy and practice.

Interaction of the solar wind with them Moon: An overview on the results from the SARA experiment aboard Chandrayaan-1

The results from the Sub-keV Atom Reflecting Analyzer (SARA) experiment onboard Chandrayaan-1 have revealed several hitherto unknown and interesting aspects about the interaction of solar wind with the Moon. The SARA experiment had two sensors — CENA and SWIM. The Chandrayaan-1 energetic neutrals analyzer (CENA), detected energetic neutral atoms (ENAs), and the Solar Wind Monitor (SWIM) measured ions of solar wind origin. In this review, we summarize the observations made by the SARA experiment, which are: (1) substantial (~20%) and sustained backscattering of solar wind protons from lunar surface as energetic neutral hydrogen,1 (2) minimagnetosphere around magnetic anomalies on Moon using the backscattered ENAs,2 (3) reflection of solar wind protons from the Moon surface,3 (4) huge (~50%) deflection of solar wind protons over strong magnetic anomalies,4 and (5) presence of protons in the near-lunar plasma wake.5 These results have implications on the lunar plasma environment, implantation of solar wind hydrogen on lunar surface, and behavior of small scale magnetic anomalies on planetary bodies. The SARA observations suggest that similar processes may happen on other airless bodies covered with regolith in the solar system as well as in extra-solar system. This paper presents a review of the results obtained from the SARA observation.

Will International Pursuit of the Millenium Development Goals Alleviate Poverty in Mountains?

Since September 2000, when world leaders agreed on time-bound, measurable goals to reduce extreme poverty, hunger, illiteracy, and disease while fostering gender equality and ensuring environmental sustainability, the Millennium Development Goals (MDGs) have increasingly come to dominate the policy objectives of many states and development agencies. The concern has been raised that the tight timeframe and financial restrictions might force governments to invest in the more productive sectors, thus compromising the quality and sustainability of development efforts. In the long term, this may lead to even greater inequality, especially between geographical regions and social strata. Hence people living in marginal areas, for example in remote mountain regions, and minority peoples risk being disadvantaged by this internationally agreed agenda. Strategies to overcome hunger and poverty in their different dimensions in mountain areas need to focus on strengthening the economy of small-scale farmers, while also fostering the sustainable use of natural resources, taking into consideration their multifunctionality.

Gene duplication: a drive for phenotypic diversity and cause of human disease

Gene duplication is one of the key factors driving genetic innovation, i.e., producing novel genetic variants. Although the contribution of whole-genome and segmental duplications to phenotypic diversity across species is widely appreciated, the phenotypic spectrum and potential pathogenicity of small-scale duplications in individual genomes are less well explored. This review discusses the nature of small-scale duplications and the phenotypes produced by such duplications. Phenotypic variation and disease phenotypes induced by duplications are more diverse and widespread than previously anticipated, and duplications are a major class of disease-related genomic variation. Pathogenic duplications particularly involve dosage-sensitive genes with both similar and dissimilar over- and underexpression phenotypes, and genes encoding proteins with a propensity to aggregate. Phenotypes related to human-specific copy number variation in genes regulating environmental responses and immunity are increasingly recognized. Small genomic duplications containing defense-related genes also contribute to complex common phenotypes.

Farmer land allocation for maize, groundnut and cotton production in Chipata District, Eastern Province, Zambia

Small-scale farmers in the Chipata District of Zambia rely on their farm fields to grow maize and groundnuts for food security. Cotton production and surplus food security crops are used to generate income to provide for their families. With increasing population pressure, available land has decreased and farmers struggle to provide the necessary food requirements and income to meet their family’s needs. The purpose of the study was to determine how a farmer can best allocate his land to produce maize, groundnuts and cotton when constrained by labor and capital resources to generate the highest potential for food security and financial gains. Data from the 2008-2009 growing season was compiled and analyzed using a linear programming model. The study determined that farmers make the most profit by allocating all additional land and resources to cotton after meeting their minimum food security requirements. The study suggests growing cotton is a beneficial practice for small-scale subsistence farmers to generate income when restricted by limited resources.

AGROFORESTRY ADDRESSING SOCIAL AND ENVIRONMENTAL ISSUES IN PARAGUAY

Paraguay is characterized in part by an economy reliant on a massive soy industry and as facing social and economic challenges resulting from highly inequitable distribution of wealth and land ownership, particularly for smallholder farmers in the rural areas of the country. Yerba mate (Ilex paraguariensis), a native tree of which the leaves are used in tea, has become an increasingly common crop grown among common among smallholder farmers (owners of 10 hectares or less) as a viable alternative to soy production on a small scale. In the rural agricultural community of Libertad del Sur, located in the heart of the severely deforested Bosque Atlántico del Alto-Paraná, a series of development initiatives including tree nurseries and agroforestry projects with yerba mate were implemented with involvement of several governmental and nongovernmental organizations. Research was conducted to identify effectiveness of an agroforestry strategy to promote reforestation activities and sustainable agriculture to achieve economic and subsistence goals of the rural population. Despite a severe drought impacting initial research goals, important lessons are considered regarding promotion of development work within the community as well as community perceptions towards development agencies. Pursuit of compromise between community member and agency goals using sustainable agricultural practices is identified as an effective means to promote mutually beneficial development strategies.

STATE-AND-TRANSITION MODELING AND ADAPTIVE MANAGEMENT: TOOLS FOR FUTURE CO-DEVELOPMENT OF MADAGASCAR’S NATURAL RESOURCES AND PEOPLE

Madagascar’s terrestrial and aquatic ecosystems have long supported a unique set of ecological communities, many of whom are endemic to the tropical island. Those same ecosystems have been a source of valuable natural resources to some of the poorest people in the world. Nevertheless, with pride, ingenuity and resourcefulness, the Malagasy people of the southwest coast, being of Vezo identity, subsist with low development fishing techniques aimed at an increasingly threatened host of aquatic seascapes. Mangroves, sea grass bed, and coral reefs of the region are under increased pressure from the general populace for both food provisions and support of economic opportunity. Besides purveyors and extractors, the coastal waters are also subject to a number of natural stressors, including cyclones and invasive, predator species of both flora and fauna. In addition, the aquatic ecosystems of the region are undergoing increased nutrient and sediment runoff due, in part, to Madagascar’s heavy reliance on land for agricultural purposes (Scales, 2011). Moreover, its coastal waters, like so many throughout the world, have been proven to be warming at an alarming rate over the past few decades. In recognizing the intimate interconnectedness of the both the social and ecological systems, conservation organizations have invoked a host of complimentary conservation and social development efforts with the dual aim of preserving or restoring the health of both the coastal ecosystems and the people of the region. This paper provides a way of thinking more holistically about the social-ecological system within a resiliency frame of understanding. Secondly, it applies a platform known as state-and-transition modeling to give form to the process. State-and-transition modeling is an iterative investigation into the physical makeup of a system of study as well as the boundaries and influences on that state, and has been used in restorative ecology for more than a decade. Lastly, that model is sited within an adaptive management scheme that provides a structured, cyclical, objective-oriented process for testing stakeholders cognitive understanding of the ecosystem through a pragmatic implementation and monitoring a host of small-scale interventions developed as part of the adaptive management process. Throughout, evidence of the application of the theories and frameworks are offered, with every effort made to retool conservation-minded development practitioners with a comprehensive strategy for addressing the increasingly fragile social-ecological systems of southwest Madagascar. It is offered, in conclusion, that the seascapes of the region would be an excellent case study worthy of future application of state-and-transition modeling and adaptive management as frameworks for conservation-minded development practitioners whose multiple projects, each with its own objective, have been implemented with a single goal in mind: preserve and protect the state of the supporting environment while providing for the basic needs of the local Malagasy people.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Enhancing rehabilitation of motor deficits with peripheral nerve stimulation

A number of different neurorehabilitation strategies include manipulation of the somatosensory system, e.g. in the form of training by passive movement. Recently, peripheral electrical nerve stimulation has been proposed as a simple, painless method of enhancing rehabilitation of motor deficits. Several physiological studies both in animals and in humans indicate that a prolonged period of patterned peripheral electrical stimulation induces short-term plasticity at multiple levels of the motor system. Small-scale studies in humans indicate that these plastic changes are linked with improvement in motor function, particularly in patients with chronic motor deficits after stroke. Somatosensory-mediated disinhibition of motor pathways is a possible underlying mechanism and might explain why peripheral electrical stimulation is more effective when combined with active training. Further large-scale studies are needed to identify the optimal stimulation protocol and the patient groups that stand to benefit the most from this technique.

The General Geology of the Cardwell Mining District

The Cardwell Mining District is part of the greater Whitehall Mining District. The district is situated about four miles to the east and northeast of Whitehall in the southern end of the Bull Mountains which are near the Continental Divide. The first reported production was in 1896 after the dis­covery of the Mayflower Mine. Mining has been carried on in­termittently and on a small scale since that time.

Electrolysis of Molten Mixtures of Galena and Lead Chloride.

Electrolysis of molten mixtures of lead chloride and galena was carried out under various conditions of temperature, time, composition, and current densities; without a diaphram, and with various diaphrams. Continuous runs, with necessary additions of lead sulfide and lead chloride to maintain a melt of the proper composition, were attempted on a small scale.

Laboratory Model Shaking Table; An Investigation of Defects and Suggested Improvements

The laboratory model is considered in this thesis. Information gained from this investigation has not been trans­ferred to the larger industrial machines. Some of the factors noted concerning the efficiency of the laboratory shaking table are inherent in this small scale model only.

Sampling-Design Effects on Properties of Species-Area Relationships - A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm(2)-100 m(2), any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m(2) plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm(2) and up to 140 species in 100 m(2), which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.

Soil Erosion and Conservation in Global Agriculture

About one-sixth of the world’s land area, that is, about one-third of the land used for agriculture, has been affected by soil degradation in the historic past. While most of this damage was caused by water and wind erosion, other forms of soil degradation are induced by biological, chemical, and physical processes. Since the 1950s, pressure on agricultural land has increased considerably owing to population growth and agricultural modernization. Small-scale farming is the largest occupation in the world, involving over 2.5 billion people, over 70% of whom live below the poverty line. Soil erosion, along with other environmental threats, particularly affects these farmers by diminishing yields that are primarily used for subsistence. Soil and water conservation measures have been developed and applied on many farms. Local and science-based innovations are available for most agroecological conditions and land management and farming types. Principles and measures developed for small-scale as well as modern agricultural systems have begun to show positive impacts in most regions of the world, particularly in wealthier states and modern systems. Much more emphasis still needs to be given to small-scale farming, which requires external support for investment in sustainable land management technologies as an indispensable and integral component of farm activities.

An insight into the actual socio-economic situation of Romania

Approximately half of the population experiences some degree of poverty while 10% live in extreme poverty (according to a report made by the Ministry of Labor, Social Solidarity and Family - MLSSF). This poverty has grown rapidly over the transition decade. Real wages, already amongst the lowest in Europe (including Central and Eastern Europe) in 1990, have since declined by approximately half. A high proportion of households, mostly those in rural areas, are engaged in informal economic activity such as small-scale farming, and it is estimated that at least one third of household incomes are in kind. High levels of poverty in the country tend to be associated with families of more than three children. The only ethnic group with a markedly distinct level of poverty is the Roma, who collectively experience 3.5 times the average poverty rate. Poverty appears to be up to half as prevalent again in rural areas (where over 45 % of the population live) compared to the urban areas, as there is also some regional concentration, often associated with declining of industrial activity.