Incorporating host-parasite biotic factors in species distribution models: Modelling the distribution of the castor bean tick, Ixodes ricinus

Q2 Social Sciences Irish Geography Pub Date : 2020-11-01 DOI:10.2014/IGJ.V53I2.1416
Sinead McDonough, P. Holloway
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引用次数: 1

Abstract

Understanding where ticks are found, and the drivers of their geographic distributions is imperative for successful epidemiological precautions. Predictive models of tick distributions are often projected using solely abiotic (e.g. climate) variables, despite the strong biotic interaction that host species undoubtedly have with parasitic species. We used species distribution modelling to project the distribution of Ixodes ricinus in Ireland and the United Kingdom using different combinations of abiotic, biotic, and abiotic-biotic variables. We found that models parameterised solely on abiotic variables generally reported lower accuracy and ecological realism than models that incorporated biotic factors alongside climate. We also investigated representation of host distribution in models, testing four different methods (habitat suitability of individual hosts, presence-absence of individual hosts, ensembled habitat suitability, and ensembled presence-absence). Biotic representations of ensembled host distributions alongside abiotic variables reported the highest accuracy, with the variable representing host diversity (e.g. number of host species) the most important variable when measured using a jackknife test. Moreover, our results suggested how host distributions are represented (i.e. presence-absence, habitat suitability) greatly impacted results, with differences reported among habitat specialists and generalists. Results suggest that it is now imperative for projections of parasitic species to include a representation of biotic factors with host species. This research has improved our understanding of the drivers of tick distributions in a national context, and the investigation of biotic representation should foster discussion among researchers working in species distribution modelling and the wider biogeography discipline. 
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在物种分布模型中纳入宿主-寄生虫生物因素:蓖麻蜱分布模型
了解蜱虫的发现地点及其地理分布的驱动因素对于成功的流行病学预防措施至关重要。蜱虫分布的预测模型通常仅使用非生物(如气候)变量进行预测,尽管宿主物种无疑与寄生物种存在强烈的生物相互作用。我们使用物种分布模型,利用非生物、生物和非生物生物变量的不同组合,预测了蓖麻硬蜱在爱尔兰和英国的分布。我们发现,与将生物因素与气候结合在一起的模型相比,仅以非生物变量为参数的模型通常报告的准确性和生态真实性较低。我们还研究了宿主分布在模型中的代表性,测试了四种不同的方法(单个宿主的栖息地适宜性、单个宿主的存在-不存在、整体栖息地适宜性和整体存在-不在场)。集合宿主分布的生物表示与非生物变量一起报告了最高的准确性,当使用jackknife测试测量时,代表宿主多样性的变量(例如宿主物种的数量)是最重要的变量。此外,我们的研究结果表明,宿主分布的表现方式(即存在与否、栖息地适宜性)极大地影响了结果,据报道,栖息地专家和多面手之间存在差异。结果表明,现在对寄生物种的预测必须包括宿主物种的生物因素的代表。这项研究提高了我们对国家背景下蜱虫分布驱动因素的理解,对生物代表性的调查应该促进从事物种分布建模和更广泛的生物地理学学科的研究人员之间的讨论。
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来源期刊
Irish Geography
Irish Geography Social Sciences-Geography, Planning and Development
CiteScore
2.10
自引率
0.00%
发文量
0
期刊介绍: Irish Geography is the premier peer-reviewed journal devoted to the geography of Ireland. It has an international distribution and is read on six continents. Its reputation for quality is long established and standards are maintained by an internationally based editorial advisory board. Irish Geography has been published by the Geographical Society of Ireland since 1944. An early editorial decision was to concentrate on the geography of Ireland and this has been maintained ever since. This focus has been a source of strength to the journal and has been important in enhancing its international reputation.
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