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Der Verfasser, ein Jurist, analysiert aus der Perspektive seines Fachgebietes das Spannungsfeld zwischen internationalen Nichtregierungsorganisationen und Regierungen im Hinblick auf Fragen der Menschenrechte. Neben rechtlichen Fragen der Durchsetzung der Menschenrechte spielt in der Betrachtung auch ein Manifest von Nichtregierungsorganisationen eine Rolle, in dem die in vielen Ländern Afrikas fehlende Verfolgung schwerer Verstöße gegen die Menschenrechte thematisiert wird. (DÜI-Kör)

[15], 243, [13] p. : ill., port., plans ; Translation of: Relation nouvelle d'un voyage de Constantinople. ; Advertisements: p. [9]-[13] at end. ; Reproduction of original in Bodleian Library.

While food security can be approached as a local issue, it is strongly influenced by factors at inter-regional and global scales related to production, transaction (e.g. trade and distribution) and consumption, and by drivers such as climate, population growth, diet change, as well as social, political and technological developments. Action on food security therefore benefits from being informed by current global patterns and potential future changes and taking an integrated approach to assessing impacts of proposed responses. Modelling can notably contribute by assessing the influence of various factors on food security. Due to the significant complexity and uncertainty involved, model development and use is simplified by approaching it as an exploratory process rather than aiming for a comprehensive historically accurate model. We present a macro-scale conceptual model to help structure and guide this exploration. We begin with the broad question "Will future developments achieve and maintain food security?" with the intent of exploring alternate possibilities of future developments, definitions of food security and factors influencing this question, beginning with assessing whether there is enough green and blue water to meet dietary energy requirements under typical current and future climatic variation. The conceptual model guides the selection of factors to explore sequentially through modelling (keeping other variables constant), iteratively building complexity as necessary. This helps to construct understanding using manageable building blocks, with the conceptual model evolving as it is used. The staged decomposition of this complex issue provides a framework to help build capacity for individuals and government agencies to understand their actions and policy respectively in a global context, with the hope that improving knowledge of adaptation options can help secure food supply to everyone.

While food security can be approached as a local issue, it is strongly influenced by factors at inter-regional and global scales related to production, transaction (e.g. trade and distribution) and consumption, and by drivers such as climate, population growth, diet change, as well as social, political and technological developments. Action on food security therefore benefits from being informed by current global patterns and potential future changes and taking an integrated approach to assessing impacts of proposed responses. Modelling can notably contribute by assessing the influence of various factors on food security. Due to the significant complexity and uncertainty involved, model development and use is simplified by approaching it as an exploratory process rather than aiming for a comprehensive historically accurate model. We present a macro-scale conceptual model to help structure and guide this exploration. We begin with the broad question "Will future developments achieve and maintain food security?" with the intent of exploring alternate possibilities of future developments, definitions of food security and factors influencing this question, beginning with assessing whether there is enough green and blue water to meet dietary energy requirements under typical current and future climatic variation. The conceptual model guides the selection of factors to explore sequentially through modelling (keeping other variables constant), iteratively building complexity as necessary. This helps to construct understanding using manageable building blocks, with the conceptual model evolving as it is used. The staged decomposition of this complex issue provides a framework to help build capacity for individuals and government agencies to understand their actions and policy respectively in a global context, with the hope that improving knowledge of adaptation options can help secure food supply to everyone.

| openaire: EC/H2020/819202/EU//SOS.aquaterra Funding Information: Marko Kallio and Vili Virkki were funded by the Aalto University School of Engineering Doctoral Programme. Marko Kallio additionally received funding from Maa-ja Vesitekniikan Tuki ry. Matti Kummu received funding from the Academy of Finland project WATVUL (grant no. 317320), Emil Aaltonen Foundation project eat-less-water, and European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant no. 819202) from which Vili Virkki received additional funding. Joseph H. A. Guillaume received funding from an Australian Research Council Discovery Early Career Researcher Award (project no. DE190100317) Funding Information: Financial support. Marko Kallio and Vili Virkki were funded by the Aalto University School of Engineering Doctoral Programme. Marko Kallio additionally received funding from Maa-ja Vesitekni-ikan Tuki ry. Matti Kummu received funding from the Academy of Finland project WATVUL (grant no. 317320), Emil Aaltonen Foundation project "eat-less-water", and European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant no. 819202) from which Vili Virkki received additional funding. Joseph H. A. Guillaume received funding from an Australian Research Council Discovery Early Career Researcher Award (project no. DE190100317). Publisher Copyright: © 2021 Marko Kallio et al. ; An increasing number of different types of hydrological, land surface, and rainfall-runoff models exist to estimate streamflow in river networks. Results from various model runs from global to local scales are readily available online. However, the usability of these products is often limited, as they often come aggregated in spatial units which are not compatible with the desired analysis purpose. We present here an R package, a software library Hydrostreamer v1.0, which aims to improve the usability of existing runoff products by addressing the modifiable area unit problem and allows non-experts with little knowledge of hydrology-specific modelling issues and methods to use them for their analyses. Hydrostreamer workflow includes (1) interpolation from source zones to target zones, (2) river routing, and (3) data assimilation via model averaging, given multiple input runoff and observation data. The software implements advanced areal interpolation methods and area-to-line interpolation not available in other products and is the first R package to provide vector-based routing. Hydrostreamer is kept as simple as possible - intuitive with minimal data requirements - and minimises the need for calibration. We tested the performance of Hydrostreamer by downscaling freely available coarse-resolution global runoff products from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) in an application in 3S Basin in Southeast Asia. Results are compared to observed discharges as well as two benchmark streamflow data products, finding comparable or improved performance. Hydrostreamer v1.0 is open source and is available from http://github.com/mkkallio/hydrostreamer/ (last access: 5 May 2021) under the MIT licence. ; Peer reviewed

The water-energy-food nexus is a topical subject for research and practice, reflecting the importance of these sectors for humankind and the complexity and magnitude of the challenges they are facing. While the nexus as a concept is not yet mature or fully tested in practice, it has already encouraged a range of approaches in a variety of contexts. This article provides a set of definitions recognizing three perspectives that see the nexus as an analytical tool, governance framework and as an emerging discourse. It discusses the implications that an international transboundary context brings to the nexus and vice versa. Based on a comparative analysis of three Asian regions-Central Asia, South Asia and the Mekong Region-and their related transboundary river basins, we propose that the transboundary context has three major implications: diversity of scales and perspectives, importance of state actors and importance of politics. Similarly, introducing the nexus as an approach in a transboundary context has a potential to provide new resources and approaches, alter existing actor dynamics and portray a richer picture of relationships. Overall, the significance of water-energy-food linkages and their direct impacts on water allocation mean that the nexus has the potential to complement existing approaches also in the transboundary river basins. ; Peer reviewed

Exploring adaptation pathways is an emerging approach for supporting decision making under uncertain changing conditions. An adaptation pathway is a sequence of policy actions to reach specified objectives. To develop adaptation pathways, interactions between environment and policy response need to be analysed over time for an ensemble of plausible futures. A fast, integrated model can facilitate this. Here, we describe the development and evaluation of such a model, an Integrated Assessment Metamodel (IAMM), to explore adaptation pathways in the Rhine delta for a decision problem currently faced by the Dutch Government. The theory-motivated metamodel is a simplified physically based model. Closed questions reflecting the required accuracy were used to evaluate the model's fitness. The results show that such a model fits the purpose of screening and ranking of policy options and pathways to support the strategic decision making. A complex model can subsequently be used to obtain more detailed information.

Exploring adaptation pathways is an emerging approach for supporting decision making under uncertain changing conditions. An adaptation pathway is a sequence of policy actions to reach specified objectives. To develop adaptation pathways, interactions between environment and policy response need to be analysed over time for an ensemble of plausible futures. A fast, integrated model can facilitate this. Here, we describe the development and evaluation of such a model, an Integrated Assessment Metamodel (IAMM), to explore adaptation pathways in the Rhine delta for a decision problem currently faced by the Dutch Government. The theory-motivated metamodel is a simplified physically based model. Closed questions reflecting the required accuracy were used to evaluate the model's fitness. The results show that such a model fits the purpose of screening and ranking of policy options and pathways to support the strategic decision making. A complex model can subsequently be used to obtain more detailed information.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.

International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of "policy analytics" was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.