Williams Hefin Wyn, Cross Dónall Eoin, Crump Heather Louise, Drost Cornelis Jan, Thomas Christopher James
Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, Wales.
Parasit Vectors. 2015 Aug 28;8:440. doi: 10.1186/s13071-015-1046-4.
There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors.
We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs).
Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution.
By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of climate change in the future.
越来越多的证据表明蜱虫物种的地理分布正在发生变化。虽然相关的物种分布模型（SDMs）已被用于预测可能适合蜱虫生存的区域，但这些模型在评估时往往没有充分考虑数据中的空间模式，而这种模式可能会夸大预测变量对物种分布的影响。本研究使用空模型来严格评估气候的作用以及气候变化对欧洲八种蜱虫物种（包括几种重要的疾病传播媒介）未来气候适宜性的潜在影响。
我们基于观测数据对最大熵模型（Maxent）和马氏距离物种分布模型（Mahalanobis Distance SDMs）的性能与基于空物种分布或空气候数据的空模型进行了比较评估。这使得能够识别其分布与气候变量显示出显著关联的物种。随后使用最新一代（AR5）气候预测来预测四种代表性浓度路径（RCPs）下的未来气候适宜性。
八种蜱虫物种中有七种在其观测分布范围内表现出强烈的气候信号。未来预测表明，这些蜱虫物种的气候适宜性将有不同程度的向北转移，在最极端的RCPs下预测的转移幅度最大。尽管葡萄牙璃眼蜱（Hyalomma lusitanicum）的观测模型获得了较高的性能指标，但它的表现并不比空模型显著更好；这可能是由于非气候因素对其分布的影响。
通过将观测到的物种分布模型与空模型进行比较，我们的结果使我们有信心确定蜱虫分布中的气候信号并非仅仅是数据空间模式的结果。八种物种中有七种观测到的受气候驱动的物种分布模型的表现显著优于空模型，这表明这些蜱虫物种未来易受气候变化的影响。
