The SOLUTIONS project: challenges and responses for present and future emerging pollutants in land and water resources management.

SOLUTIONS (2013 to 2018) is a European Union Seventh Framework Programme Project (EU-FP7). The project aims to deliver a conceptual framework to support the evidence-based development of environmental policies with regard to water quality. SOLUTIONS will develop the tools for the identification, prioritisation and assessment of those water contaminants that may pose a risk to ecosystems and human health. To this end, a new generation of chemical and effect-based monitoring tools is developed and integrated with a full set of exposure, effect and risk assessment models. SOLUTIONS attempts to address legacy, present and future contamination by integrating monitoring and modelling based approaches with scenarios on future developments in society, economy and technology and thus in contamination. The project follows a solutions-oriented approach by addressing major problems of water and chemicals management and by assessing abatement options. SOLUTIONS takes advantage of the access to the infrastructure necessary to investigate the large basins of the Danube and Rhine as well as relevant Mediterranean basins as case studies, and puts major efforts on stakeholder dialogue and support. Particularly, the EU Water Framework Directive (WFD) Common Implementation Strategy (CIS) working groups, International River Commissions, and water works associations are directly supported with consistent guidance for the early detection, identification, prioritisation, and abatement of chemicals in the water cycle. SOLUTIONS will give a specific emphasis on concepts and tools for the impact and risk assessment of complex mixtures of emerging pollutants, their metabolites and transformation products. Analytical and effect-based screening tools will be applied together with ecological assessment tools for the identification of toxicants and their impacts. The SOLUTIONS approach is expected to provide transparent and evidence-based candidates or River Basin Specific Pollutants in the case study basins and to assist future review of priority pollutants under the WFD as well as potential abatement options.

Land use policies and practices for reducing vulnerability in rural Tajikistan

Tajikistan, with 93% of its surface area taken up by mountains and 65% of its labor force employed in agriculture, is judged to be highly vulnerable to risks, including climate change risks and food insecurity risks. The article examines a set of land use policies and practices that can be used to mitigate the vulnerability of Tajikistan’s large rural population, primarily by increasing family incomes. Empirical evidence from Tajikistan and other CIS countries suggests that families with more land and higher commercialization earn higher incomes and achieve higher well-being. The recommended policy measures that are likely to increase rural family incomes accordingly advocate expansion of smallholder farms, improvement of livestock productivity, increase of farm commercialization through improvement of farm services, and greater diversification of both income sources and the product mix. The analysis relies for supporting evidence on official statistics and recent farm surveys. Examples from local initiatives promoting sustainable land management practices and demonstrating the implementation of the proposed policy measures are presented.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Creating a public tool to assess and promote transparency in global land deals: the experience of the Land Matrix

The Beta version of the Land Matrix (Land Matrix 2012) was launched in April 2012 as a tool to promote public participation in building a constantly evolving database on large-scale land deals, and making the data visible and understandable. The aim of the Land Matrix partnership is to promote transparency and open data in decisionmaking over land and investment, as a step towards greater accountability. Since its launch, the Land Matrix has attracted a high degree of attention, and stirred some controversy. It provides valuable lessons on the challenges and benefits of promoting open data on practices that are often shrouded in secrecy. This paper critically examines the ongoing efforts by the Land Matrix partnership to build a public tool to promote greater transparency in decision-making over land and investment at a global level. It intends to provoke discussion of the extent to which such a tool can ultimately promote greater transparency and be a step towards greater accountability and improved decision-making. It will present the Land Matrix and its value addition, before detailing the challenges it encountered related to the measurement of the largescale land acquisition phenomenon. It will then specify how it intends to address these issues in order to establish a dynamic and participatory tool for open development.

Indigenous land reconfiguration and fragmented institutions: a historical political ecology of Tsimane’ lands (Bolivian Amazon)

Lands inhabited by indigenous peoples often have low population density but abundant natural resources. For those reasons, many actors have historically attempted to occupy those lands or use the resources in them. Increasing pressures over lands occupied by indigenous peoples have resulted in the awakening of indigenous peoples over their rights to land and resources generating many debates over indigenous peoples' rights to land and self-governance. In this article, we provide a historical and geographical overview of territorial and governance issues among the Tsimane', an indigenous group native to the Bolivian Amazon. We examine how the Bolivian state economic policies implemented during the 20th century affected the Tsimane' ancestral lands, and how – over the late-20th century – the Bolivian state accommodated Tsimane' claims to lands in between multiple interests. We show how national policies led to the reconfiguration of Tsimane' territoriality and to a fragmented institutional representation. Current indigenous territories and indigenous political representation are an expression of conflictive policies that have involved multiple actors and their specific interests on indigenous lands and its resources.