Recognizing sources of uncertainty in disease vector ecological niche models: An example with the tick Rhipicephalus sanguineus sensu lato
Recognizing sources of uncertainty in disease vector ecological niche models: An example with the tick Rhipicephalus sanguineus sensu lato
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DOI：
10.1016/j.pecon.2020.03.002
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发表时间：
2020-04-01
影响因子：
4.7
通讯作者：
Samy, Abdallah M.
中科院分区：
文献类型：
--
作者：
Alkishe, Abdelghafar;Cobos, Marlon E.;Samy, Abdallah M.
流行病学是使用生态位模型来评估物种潜在分布或潜在范围扩展的许多领域之一。当这些模型在空间和时间上转移时，重要的是要了解其预测中不确定性的来源和位置。在这里，我们使用蜱物种Rhipicephalus sanguineus sensu lato（分布在世界各地的不同地区）为例，我们第一次，其全球地理分布特征，使用生态位建模，并探讨在空间和时间转移模型所涉及的不确定性。我们根据严格外推的风险以及我们预测中的变化量和变化模式来评估不确定性。我们整合了发生记录和气候数据，以校准世界5个地区的模型，并将其投射到11个大气环流模型（GCM）和2050年的两个代表性浓度路径排放情景（RCP）中。在不同校准区域创建的模型显示，来自美国东部、墨西哥南部、南美洲、欧洲、北非、撒哈拉以南国家、亚洲和澳大利亚的模型预测之间的合适区域高度一致。研究了R. sanguineus sensulato在两个RCP之间非常相似，但GCM、模型重复和模型参数化对检测到的总体变异有重要贡献。模式的不确定性（严格的外推面积和变化）在我们的模型预测取决于校准面积，并强调了重要的影响，不考虑变异和外推风险的生态位模型预测的解释。
Epidemiology is one of many fields that use ecological niche modeling to assess potential distributions or potential range expansions of species. When such models are transferred in space and time, it is important to understand sources and location of uncertainty in their predictions. Here, we used the tick species Rhipicephalus sanguineus sensu lato (distributed in different areas around the world) as an example; for the first time, we characterized its global geographic distribution using ecological niche modeling, and explore the uncertainty involved in transferring models in space and time. We assessed uncertainties based on risks of strict extrapolation and amounts and patterns of variation in our predictions. We integrated occurrence records and climate data to calibrate models for 5 world regions, and to project them to 11 general circulation models (GCMs) and two representative concentration pathway emissions scenarios (RCPs) for 2050. Models created in different calibration areas showed high agreement of suitable areas among model predictions from the eastern United States, southern Mexico, South America, Europe, North Africa, sub-Saharan countries, Asia, and Australia. The global potential distributions of R. sanguineus sensulato were very similar between the two RCPs, but GCMs, model replicates, and model parametrizations contributed importantly to the overall variation detected. Patterns of uncertainty (strict extrapolation areas and variation) in our model predictions depended on the calibration area, and underlined the important implications of not considering variability and extrapolation risk in interpretations of ecological niche model projections.