Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.
Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.
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DOI：
10.3390/ijgi2030645
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发表时间：
2013-09-01
影响因子：
3.4
通讯作者：
Remais JV
中科院分区：
文献类型：
--
作者：
Dhingra R;Jimenez V;Chang HH;Gambhir M;Fu JS;Liu Y;Remais JV
变温性疾病媒介可以通过种群大小和物候的空间变化对气候变化做出反应。缺乏定量描述符来表征、分析和可视化这些动态响应，特别是在大的空间域中。为了展示空间显式的动态建模方法的价值，我们使用覆盖美国东部的4×4公里网格模拟的温度强迫种群模型，使用建模(天气研究和预报(WRF)3.2.1)基线/当前(2001-2004)和预测(代表性浓度路径(RCP)4.5和RCP 8.5；2057-2059)气候数据，评估了莱姆病病媒-肩部硬蜱种群动态的空间变化。从模拟人口中提取了10个动态人口特征(DPF)，并对其进行了空间分析，以表征区域人口对当前和未来气候的响应。使用美国疾病控制和预防中心的数据，对当前气候下的每个DPF进行了评估，以确定其区分观察到的莱姆病风险和已知媒介存在/不存在的能力。高峰期媒介种群和高峰期媒介种群月份是当前莱姆病风险预测最好的DPF。当在基线和预测气候情景下审查时，DPF的时空分布发生变化，关键探测生命阶段的季节周期在某些情景下被压缩。我们的结果证明了动态种群反应的空间表征、分析和可视化的实用性，包括改变的物候-疾病媒介对气候变化的反应。
Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate.
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影响因子：
3.5
作者：
Adler, Frederick R.;Pearce-Duvet, Jessica M. C.;Dearing, M. Denise
通讯作者：
Dearing, M. Denise
影响因子：
3
作者：
Gething PW;Patil AP;Smith DL;Guerra CA;Elyazar IR;Johnston GL;Tatem AJ;Hay SI
通讯作者：
Hay SI
影响因子：
4.8
作者：
Ebi, KL;Hartman, J;Weyant, J
通讯作者：
Weyant, J
影响因子：
4.8
作者：
Jacobson, AR;Provenzale, A;Festa-Bianchet, M
通讯作者：
Festa-Bianchet, M
DOI：
10.1007/s10096-006-0167-2
发表时间：
2006-07-01
影响因子：
4.5
作者：
Bennet, L.;Halling, A.;Berglund, J.
通讯作者：
Berglund, J.