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In this article, integration of rice markets in southern China is analyzed using the cointegration technique and monthly price data. Results show that there is a general lack of integration among the indica rice markets in China. Poor transport facilities, government interventions, and the limited amount of grain available for arbitrage are identified as the major impediments to market integration. Policy implications are discussed.

'With the world's largest population and second largest economy, China plays an important role in global food production and consumption. This book by a distinguished group of authors is timely to present an updated analysis of food consumption in China. The material covered is informative and comprehensive. All food-related traders, researchers and analysts would benefit from reading this book.' - Yanrui Wu, The University of Western Australia, Australia

This is the final version. Available on open access from the American Geophysical Union via the DOI in this record ; Data Availability Statement: The field data regarding mangrove seaward edge elevation relative to MWL is summarized from previous publications and is available as supplementary materials (Table S4 in Supporting Information S1).The field data regarding local SLR rates and vertical elevation dynamics is available as supplementary material (Table S5 in Supporting Information S1), summarized from the open-access publication by McKee et al. (2021). Delft3D is an open-source code available online (at https://oss.deltares.nl). The dynamic vegetation code with a representative model setting is available at https://github.com/xiedanghan/MangroveVulnerabilityModel. ; Mangrove forests are valuable coastal ecosystems that have been shown to persist on muddy intertidal flats through bio-morphodynamic feedbacks. However, the role of coastal conditions on mangrove behavior remains uncertain. This study conducts numerical experiments to systematically explore the effects of tidal range, small wind waves, sediment supply and coastal slope on mangrove development under sea-level rise (SLR). Our results show that mangroves in micro-tidal conditions are more vulnerable because of the gentler coastal equilibrium slope and the limited ability to capture sediment, which leads to substantial mangrove landward displacement even under slow SLR. Macro-tidal conditions with large sediment supply promote accretion along the profile and platform formation, reducing mangrove vulnerability for slow and medium SLR, but still cause rapid mangrove retreat under fast SLR. Small wind waves promote sediment accretion, and exert an extra bed shear stress that confines the mangrove forest to higher elevations with more favorable inundation regimes, offsetting SLR impacts. These processes also have important implications for the development of new landward habitats under SLR. In particular, our experiments show that landward habitat can be created even with limited sediment supply and thus without complete infilling of the available accommodation space. Nevertheless, new accommodation space may be filled over time with sediment originating from erosion of the lower coastal profile. Consistent with field data, model simulations indicate that sediment accretion within the forest can accelerate under SLR, but the timing and magnitude of accretion depend non-linearly on coastal conditions and distance from the mangrove seaward edge. ; China Scholarship Council ; Department of Physical Geography, Utrecht University ; NWO WOTRO Joint Sustainable Development Goal Research Program ; European Union Horizon 2020 ; National Natural Science Foundation of China

In the past decade we have witnessed the failure of traditional polls in predicting presidential election outcomes across the world. To understand the reasons behind these failures we analyze the raw data of a trusted pollster which failed to predict, along with the rest of the pollsters, the surprising 2019 presidential election in Argentina. Analysis of the raw and re-weighted data from longitudinal surveys performed before and after the elections reveals clear biases related to mis-representation of the population and, most importantly, to social-desirability biases, i.e., the tendency of respondents to hide their intention to vote for controversial candidates. We propose an opinion tracking method based on machine learning models and big-data analytics from social networks that overcomes the limits of traditional polls. This method includes three prediction models based on the loyalty classes of users to candidates, homophily measures and re-weighting scenarios. The model achieves accurate results in the 2019 Argentina elections predicting the overwhelming victory of the candidate Alberto Fernández over the incumbentpresident Mauricio Macri, while none of the traditional pollsters was able to predict the largegap between them. Beyond predicting political elections, the framework we propose is more general and can be used to discover trends in society, for instance, what people think about economics, education or climate change.

Due to revised phylogenies and newly discovered biogeographic distributions, scientific binomials are being amended continuously. Problematic is that wildlife protection legislation tends not to keep pace with these reappraisals, creating a wide range of legislative loopholes and potentially compromising ability to prosecute illegal wildlife trade (IWT). This serious and growing international problem proves particularly challenging in China because binomials used on China's national legislation have not been up-dated since 1989, alongside the enormous issues of IWT in this mega-diverse nation. Here we focus especially on mammals, because these support lucrative criminal markets and receive the greatest international policing efforts; however all protected taxa are vulnerable to this mis-naming ambiguity. To-date, the names of twenty-five threatened species, including eighteen mammals, have become incongruent with Chinese law. Additionally, two primate species, newly discovered within China, have not yet been incorporated into Chinese law. A further, six mammalian species are known by different synonyms between Chinese law and CITES, hindering international policing and compilation of data on IWT. Taxonomic revisions similarly undermine legislation in other mega-diverse countries; posing a critical risk to wildlife protection worldwide. We recommend that scientific binomials must be updated systematically across all 181 CITES signatory nations.