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Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever
Journal of Wildlife Management ( IF 2.3 ) Pub Date : 2021-02-23 , DOI: 10.1002/jwmg.22015
Gerald Reiner 1 , Martin Rumpel 1 , Karl Zimmer 2 , Hermann Willems 1
Affiliation  

For areas at risk for African swine fever (ASF) introduction from neighboring regions, it is important for epidemic control to know how wild boar (Sus scrofa) dispersion dynamics could be used to combat the spread of ASF. In this regard, long‐term information based on population genetic data makes an important contribution. We selected our study area as Rhineland‐Palatinate, Germany, because it had a high density of wild boars and was threatened by ASF via infected wild boars from neighboring Belgium. On an area of around 20,000 km2, we collected almost 1,200 blood samples from 22 wild boar hunting grounds. The study area included a network of potential barriers to movement, including roads and rivers. We assessed genetic differentiation based on microsatellite data. We used 2 spatial (Bayesian Analysis of Population Structure [BAPS] and TESS) and 1 non‐spatial (STRUCTURE) Bayesian model‐based approaches to analyze the data. Each of the algorithms detected 4 clusters with different cluster compositions in different areas and identified the highest degrees of differentiation between hunting grounds east and west of the Rhine River, between Pfalz and Eifel‐Hunsrück, and to a lesser degree between Westerwald and Taunus and between Eifel and Hunsrück. Thus, genetic evidence suggests barriers of different strength that might be helpful in a setup of complex and expensive measures against the spread of animal diseases such as ASF. The described approach could also provide valuable information for other threatened regions to contain ASF. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.

中文翻译:

非洲猪瘟濒危地区野猪种群的遗传分化

对于可能从邻近地区引入非洲猪瘟(ASF)的地区,对于流行病控制而言,重要的是要知道如何使用野猪(Sus scrofa)扩散动态来对抗ASF的传播。在这方面,基于种群遗传数据的长期信息做出了重要贡献。我们选择研究区域为德国莱茵兰-普法尔茨州,因为它的野猪密度高,并且受到来自邻国比利时的被感染野猪的ASF威胁。约20,000 km 2,我们从22个野猪狩猎场收集了近1200个血液样本。研究区域包括一个潜在的行动障碍网络,包括道路和河流。我们基于微卫星数据评估了遗传分化。我们使用了2种基于空间的(贝叶斯人口结构[BAPS]和TESS分析)和1种基于非空间(结构)贝叶斯模型的方法来分析数据。每种算法都检测到4个在不同区域具有不同群集组成的群集,并确定了莱茵河以东和西部,Pfalz和Eifel-Hunsrück之间的狩猎场之间的最高区分度,以及Westerwald和Taunus之间以及之间的较小程度的区分。埃菲尔(Eifel)和洪斯吕克(Hunsrück)。因此,遗传证据表明,不同强度的障碍可能有助于采取一系列复杂而昂贵的措施来防止诸如ASF之类的动物疾病的传播。所描述的方法还可以为其他受威胁地区包含ASF提供有价值的信息。©2021作者。Wiley Periodicals LLC代表野生动物协会出版的《野生动物管理杂志》。
更新日期:2021-03-08
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