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结合公众参与式监测和占有量建模预测扁虱对气候变化的分布反应。

Combining public participatory surveillance and occupancy modelling to predict the distributional response of Ixodes scapularis to climate change.

机构信息

Department of Geography and Environment, Mount Allison University, 144 Main Street, Sackville, New Brunswick, E4L 1A7, Canada.

Department of Biology, Mount Allison University, 63B York Street, Sackville, New Brunswick, E4L 1G7, Canada.

出版信息

Ticks Tick Borne Dis. 2018 Mar;9(3):695-706. doi: 10.1016/j.ttbdis.2018.01.018. Epub 2018 Feb 16.

Abstract

Ixodes scapularis, a known vector of Borrelia burgdorferi sensu stricto (Bbss), is undergoing range expansion in many parts of Canada. The province of New Brunswick, which borders jurisdictions with established populations of I. scapularis, constitutes a range expansion zone for this species. To better understand the current and potential future distribution of this tick under climate change projections, this study applied occupancy modelling to distributional records of adult ticks that successfully overwintered, obtained through passive surveillance. This study indicates that I. scapularis occurs throughout the southern-most portion of the province, in close proximity to coastlines and major waterways. Milder winter conditions, as indicated by the number of degree days <0 °C, was determined to be a strong predictor of tick occurrence, as was, to a lesser degree, rising levels of annual precipitation, leading to a final model with a predictive accuracy of 0.845 (range: 0.828-0.893). Both RCP 4.5 and RCP 8.5 climate projections predict that a significant proportion of the province (roughly a quarter to a third) will be highly suitable for I. scapularis by the 2080s. Comparison with cases of canine infection show good spatial agreement with baseline model predictions, but the presence of canine Borrelia infections beyond the climate envelope, defined by the highest probabilities of tick occurrence, suggest the presence of Bbss-carrying ticks distributed by long-range dispersal events. This research demonstrates that predictive statistical modelling of multi-year surveillance information is an efficient way to identify areas where I. scapularis is most likely to occur, and can be used to guide subsequent active sampling efforts in order to better understand fine scale species distributional patterns.

摘要

Ixodes scapularis,一种已知的 Borrelia burgdorferi sensu stricto (Bbss) 的载体,正在加拿大的许多地区进行范围扩张。新不伦瑞克省与 I. scapularis 种群已经建立的地区接壤,是该物种的范围扩张区。为了更好地了解这种蜱虫在气候变化预测下的当前和潜在未来分布,本研究应用了占有模型来分析通过被动监测获得的成功越冬的成年蜱虫的分布记录。本研究表明,I. scapularis 存在于该省最南端的地区,靠近海岸线和主要水道。冬季温度较低,用<0°C的度日数表示,被确定为蜱虫发生的一个强有力的预测因子,而年降水量的上升程度则略次之,导致最终模型的预测准确率为 0.845(范围:0.828-0.893)。RCP 4.5 和 RCP 8.5 气候预测都表明,到 2080 年代,该省相当大的一部分(大约四分之一到三分之一)将非常适合 I. scapularis。与犬类感染病例的比较表明,与基线模型预测有很好的空间一致性,但在蜱虫发生概率最高的气候范围内,仍存在携带 Bbss 的蜱虫,这表明存在由长距离扩散事件传播的蜱虫。本研究表明,对多年监测信息进行预测性统计建模是识别 I. scapularis 最可能发生的区域的有效方法,并且可以用于指导随后的主动采样工作,以更好地了解物种的细尺度分布模式。

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