Global public policy, transnational policy communities, and their networks

Public policy has been a prisoner of the word "state." Yet, the state is reconfigured by globalization. Through "global public–private partnerships" and "transnational executive networks," new forms of authority are emerging through global and regional policy processes that coexist alongside nation-state policy processes. Accordingly, this article asks what is "global public policy"? The first part of the article identifies new public spaces where global policies occur. These spaces are multiple in character and variety and will be collectively referred to as the "global agora." The second section adapts the conventional policy cycle heuristic by conceptually stretching it to the global and regional levels to reveal the higher degree of pluralization of actors and multiple-authority structures than is the case at national levels. The third section asks: who is involved in the delivery of global public policy? The focus is on transnational policy communities. The global agora is a public space of policymaking and administration, although it is one where authority is more diffuse, decision making is dispersed and sovereignty muddled. Trapped by methodological nationalism and an intellectual agoraphobia of globalization, public policy scholars have yet to examine fully global policy processes and new managerial modes of transnational public administration

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessmentwas conducted by testing six detailed state-of-the-artmodels for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of themodels: 1) a blind test for 2005 2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009 2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement,model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling team of Democritus University of Thrace would like to thank Per-Erik Jansson (Royal Institute of Technology, Stockholm, Sweden) for his valuable help during the application of Coup Model.Groenendijk, P.; Heinen, M.; Klammler, G.; Fank, J.; Kupfersberger, H.; Pisinaras, V.; Gemitzi, A.... (2014). Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data. Science of the Total Environment. 499:463-480. https://doi.org/10.1016/j.scitotenv.2014.07.002S46348049

Forward K+ production in subthreshold pA collisions at 1.0 GeV

K+ meson production in pA (A = C, Cu, Au) collisions has been studied using the ANKE spectrometer at an internal target position of the COSY-Juelich accelerator. The complete momentum spectrum of kaons emitted at forward angles, theta < 12 degrees, has been measured for a beam energy of T(p)=1.0 GeV, far below the free NN threshold of 1.58 GeV. The spectrum does not follow a thermal distribution at low kaon momenta and the larger momenta reflect a high degree of collectivity in the target nucleus.Comment: 4 pages, 3 figure

Ancient DNA suggests modern wolves trace their origin to a late Pleistocene expansion from Beringia.

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographic distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single late Pleistocene population. Both the geographic origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a dataset of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore, and provides an insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.L.L., K.D. and G.L. were supported by the Natural Environment Research Council, UK (grant numbers NE/K005243/1, NE/K003259/1); LL was also supported by the European Research Council grant (339941‐ADAPT); A.M. and A.E. were supported by the European Research Council Consolidator grant (grant number 647787‐LocalAdaptation); L.F. and G.L. were supported by the European Research Council grant (ERC‐2013‐StG 337574‐UNDEAD); T.G. was supported by a European Research Council Consolidator grant (681396‐Extinction Genomics) & Lundbeck Foundation grant (R52‐5062); O.T. was supported by the National Science Center, Poland (2015/19/P/NZ7/03971), with funding from EU's Horizon 2020 programme under the Marie Skłodowska‐Curie grant agreement (665778) and Synthesys Project (BETAF 3062); V.P., E.P. and P.N. were supported by the Russian Science Foundation grant (N16‐18‐10265 RNF); A.P. was supported by the Max Planck Society; M.L‐G. was supported by a Czech Science Foundation grant (GAČR15‐06446S)

Ancient DNA suggests modern wolves trace their origin to a late Pleistocene expansion from Beringia.

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographic distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single late Pleistocene population. Both the geographic origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a dataset of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore, and provides an insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.L.L., K.D. and G.L. were supported by the Natural Environment Research Council, UK (grant numbers NE/K005243/1, NE/K003259/1); LL was also supported by the European Research Council grant (339941‐ADAPT); A.M. and A.E. were supported by the European Research Council Consolidator grant (grant number 647787‐LocalAdaptation); L.F. and G.L. were supported by the European Research Council grant (ERC‐2013‐StG 337574‐UNDEAD); T.G. was supported by a European Research Council Consolidator grant (681396‐Extinction Genomics) & Lundbeck Foundation grant (R52‐5062); O.T. was supported by the National Science Center, Poland (2015/19/P/NZ7/03971), with funding from EU's Horizon 2020 programme under the Marie Skłodowska‐Curie grant agreement (665778) and Synthesys Project (BETAF 3062); V.P., E.P. and P.N. were supported by the Russian Science Foundation grant (N16‐18‐10265 RNF); A.P. was supported by the Max Planck Society; M.L‐G. was supported by a Czech Science Foundation grant (GAČR15‐06446S)