Department of Geography and Environmental Sustainability, University of Oklahoma, Norman OK, USA.
Department of Biology, Southern Nazarene University, Bethany, OK, USA.
J Med Entomol. 2022 Nov 16;59(6):1936-1946. doi: 10.1093/jme/tjac145.
Exposure to mosquito-borne diseases is influenced by landscape patterns and microclimates associated with land cover. These influences can be particularly strong in heterogeneous urban landscapes where human populations are concentrated. We investigated how land cover and climate influenced abundances of Ae. albopictus (Skuse) (Diptera: Culicidae) and Cx. quinquefasciatus (Say) (Diptera: Culicidae) in Norman, Oklahoma (United States). From June-October 2019 and May-October 2020 we sampled mosquitoes along an urban-rural gradient using CO2 baited BG Sentinel traps. Microclimate sensors at these sites measured temperature and humidity. We mapped environmental variables using satellite images from Landsat, Sentinel-2, and VIIRS, and the CHIRPS rainfall dataset. We also obtained meteorological data from the closest weather station. We compared statistical models of mosquito abundance based on microclimate, satellite, weather station, and land cover data. Mosquitoes were more abundant on trap days with higher temperature and relative humidity. Rainfall 2 wk prior to the trap day negatively affected mosquito abundances. Impervious surface cover was positively associated with Cx. quinquefasciatus and tree cover was negatively associated with Ae. albopictus. Among the data sources, models based on satellite variables and land cover data had the best fits for Ae. albopictus (R2 = 0.7) and Cx. quinquefasciatus (R2 = 0.51). Models based on weather station or microclimate data had weaker fits (R2 between 0.09 and 0.17) but were improved by adding land cover variables (R2 between 0.44 and 0.61). These results demonstrate the potential for using satellite remote sensing for mosquito habitat analyses in urban areas.
登革热媒介蚊虫的孳生受与土地覆被相关的景观格局和小气候的影响。在人类高度集中的异质化城市景观中,这些影响可能尤为强烈。本研究在美国俄克拉荷马州诺曼市调查了土地覆被和气候如何影响白纹伊蚊(Skuse)(双翅目:蚊科)和致倦库蚊(Say)(双翅目:蚊科)的数量。2019 年 6 月至 10 月和 2020 年 5 月至 10 月,我们沿城乡梯度使用 CO2 引诱 BG Sentinel 诱捕器对蚊虫进行了采样。这些地点的微气候传感器测量了温度和湿度。我们使用 Landsat、Sentinel-2 和 VIIRS 卫星图像以及 CHIRPS 降雨数据集绘制了环境变量图,并从最近的气象站获取了气象数据。我们还比较了基于微气候、卫星、气象站和土地覆被数据的蚊虫丰度统计模型。在温度和相对湿度较高的诱捕日,蚊虫更丰富。诱捕日前 2 周的降雨量会对蚊虫数量产生负面影响。不透水面覆盖率与致倦库蚊呈正相关,而树木覆盖率与白纹伊蚊呈负相关。在数据源中,基于卫星变量和土地覆被数据的模型对白纹伊蚊(R2 = 0.7)和致倦库蚊(R2 = 0.51)的拟合效果最好。基于气象站或微气候数据的模型拟合效果较弱(R2 在 0.09 到 0.17 之间),但添加土地覆被变量后有所改善(R2 在 0.44 到 0.61 之间)。这些结果表明,利用卫星遥感技术分析城市地区的蚊虫栖息地具有潜力。