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      Recent Pangolin Seizures in China Reveal Priority Areas for Intervention : Network analysis of China pangolin market

      , ,
      Conservation Letters
      Wiley-Blackwell

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          Poaching is more than an Enforcement Problem

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            Use of social network analysis to characterize the pattern of animal movements in the initial phases of the 2001 foot and mouth disease (FMD) epidemic in the UK.

            Aggregated movement data do not take into account the relative position of the units within a higher-level structure. Social network analysis (SNA) and graph theory provide a tool to organise and analyse relational data overcoming the limitations of standard methods where the position of individuals/observations does not affect the result of the analysis. Some recorded movements of cattle and sheep during the initial phase of the 2001 foot and mouth disease (FMD) outbreak in the UK, before the ban on animal movements was imposed, are analysed descriptively using SNA. With the data available, a directed dichotomized network with 653 nodes and 797 arches was analysed. Most of the 10 nodes with the highest betweenness (3 farms, 4 markets and 3 dealers) were identified as key players in the initial spread of the infection. Three groups of nodes with distinctive proportion of k < or = 2 neighbours would result in three different theoretical outbreak dimensions assuming that the infection is only disseminated by the movements included in the network: no spread, spread up to 7% and around 25%. There are three hierarchical clusters with 308, 215 and 130 nodes, respectively. Farms in cluster 1 appear to be more similar in their movement patterns to non-farm holdings than to farms in clusters 2 and 3. Relative betweenness, k-neighbours and structural equivalence using hierarchical clustering were able to identify key actors in the evolution of the initial phases of the FMD outbreak such as markets, dealers and farms with atypical movement patterns. Holdings with high betweenness, large number of k < or = 2 neighbours and with movement pattern as in cluster 1 should be targeted in disease control activities once primary actors like markets, dealers and slaughter houses have been contained.
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              Wildlife trade, consumption and conservation awareness in southwest China

              Commercial trade in wildlife is the major cause of species endangerment and a main threat to animal welfare in China and its neighboring countries. Driven by consumptive use for food and traditional medicine, the large volume of both legal and illegal trade in wildlife has caused great destruction to ecosystems and pushed many species to the brink of extinction. Data gathered from trading hubs at ports, boundary markets, city markets and stores, indicates the large amount of wildlife traded in the region of Guangxi, Yunnan and Qinghai provinces, a direct result of the numerous wildlife markets available. In a survey distributed in various trading places, while about half of the respondents agreed that wildlife should be protected, 60% of them had consumed wildlife at some point in the last 2 years. The results also indicated that law and regulation on wildlife trade control is insufficient. Wildlife trade controls are very limited because of bias on the utilization of wildlife as a natural resource to be exploited by the government agencies. The survey also shows that the current situation of wildlife consumption in key cities in China is serious, especially the consumption for food. The main consumption groups in China are male and young people with high education levels and good incomes. The key in public awareness publicity and education is to give them more information on the negative impacts of wildlife consumption and knowledge of protection.
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                Author and article information

                Journal
                Conservation Letters
                CONSERVATION LETTERS
                Wiley-Blackwell
                1755263X
                November 2017
                November 01 2017
                : 10
                : 6
                : 757-764
                Article
                10.1111/conl.12339
                8aca02e7-1fb6-4e3a-880c-c298624c4566
                © 2017

                http://doi.wiley.com/10.1002/tdm_license_1.1

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