Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Campo Boario, Teramo, Italy.
Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.
PLoS One. 2019 Jul 3;14(7):e0219072. doi: 10.1371/journal.pone.0219072. eCollection 2019.
Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies.
生态区域化是根据特定的环境和气候因素将一个地区划分为相似区域的过程。气候和环境强烈影响着全球范围内导致人类和动物重大疾病的病媒的存在和分布。在本文中，我们采用基于数据的空间聚类方法，使用最近和详细的气候和环境因素的空间数据，开发了意大利的生态气候区域图。我们选择了七个变量，这些变量与广泛的人类和动物媒介传播疾病（VBD）有关：海拔标准差、白天陆地表面平均温度、陆地表面温度年循环的平均幅度和峰值时间、陆地表面温度年循环的平均和幅度、绿色值年循环以及每日平均降雨量。主成分分析（PCA）后，采用基于 k-medoids 技术的多元地理聚类，将具有相似特征的像素分组到不同的生态区中，并在不同的空间分辨率（250 m、1 km 和 2 km）下进行。我们表明，生态区的空间结构通常在不同的空间分辨率下保持不变，我们将生成的生态区地图与与意大利蓝舌病（BT）和西尼罗河病（WND）媒介相关的两个数据集进行了比较。已知的库蠓栖息地特征在 22 个特定生态区中的 2 个（在 250 m 分辨率下）中得到了很好的捕捉。已知库蠓 obsoletus/scoticus 分布在整个半岛，因此占据了所有采样的生态区。WND 爆发地点强烈聚集在 22 个生态区中的 4 个生态区中，这些生态区以人类影响的景观为主，具有强烈的耕作和复杂的灌溉网络。这种方法在 VBD 情况下可以作为一种支持工具，确定有利于 VBD 传播的像素为基础的区域，指出在意大利哪里可以优先进行监测和预防措施。此外，适合特定 VBD 媒介的生态区可以为昆虫学监测策略提供信息。
