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Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

机译:开发了第一个Rhipicephalus(Boophilus)spp地理参考图。 1970年至今的墨西哥及其空间分布预测

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The tick genus Ripicephalus (Boophilus) , particularly R. microplus , is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.
机译:壁虱属Ripicephalus(Boophilus),特别是R. microplus,是影响牲畜健康的最重要的外寄生虫之一,并被认为是一种流行病学风险,因为它造成了重大的经济损失,这主要是由于受侵染动物向多个国家出口的限制。其空间分布与环境因素有关,主要是温暖的温度和较高的相对湿度。在这项工作中,我们整合了一个数据集,该数据集由墨西哥的Rhipicephalus spp。的5843个记录组成,涵盖了近50年的时间,以了解哪些环境变量主要影响此壁虱的分布。使用DIVA-GIS软件对事件进行地理定位,并使用最大熵方法(Maxent)对潜在的电流分布进行建模。该算法生成了具有高预测能力的图(曲线下的面积= 0.942),提供了测试变量的各种贡献和排列重要性。在确定Rhipicephalus spp的空间分布概率中,降水季节,特别是3月,和等温是最重要的气候变量。墨西哥(分别为15.7%,36.0%和11.1%)。我们的发现表明,Rhipicephalus已在墨西哥广泛殖民,包括以不同类型的气候为特征的地区。我们得出的结论是,使用Rhipicephalus记录和一组环境变量的Maxent分布模型可以预测该国the价范围的程度,该信息应支持综合控制策略的发展。

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