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景观指标能否帮助确定意大利库蠓的分布情况?

Can landscape metrics help determine the Culicoides imicola distribution in Italy?

作者信息

Ippoliti Carla, Gilbert Marius, Vanhuysse Sabine, Goffredo Maria, Satta Giuseppe, Wolff Eléonore, Conte Annamaria

出版信息

Geospat Health. 2013 Nov;8(1):267-77. doi: 10.4081/gh.2013.72.

Abstract

Culicoides imicola is considered to be one of the main vectors of bluetongue disease in the Mediterranean Basin. However, local variations occur. For example, in Italy, C. imicola is a stable and abundant population in Sardinia and is widely distributed across the island, whilst in Tuscany on the Italian mainland, it ranges from low abundance in the west and coastal areas to absence in the eastern part of the region. Entomological surveillance data collected over 10 years were used to classify 52 sites as low to medium or high C. imicola abundance in Sardinia, and 59 sites as either positive or negative in Tuscany. The land cover was mapped from high-resolution remote sensing images using an object-based image analysis approach and a set of landscape metrics with 500 m buffers around each site. Multivariate analysis was used to test the statistical association of landscape metrics to C. imicola presence and abundance together with other eco-climatic and topographic variables. In Sardinia, 75% of the sites were correctly classified based on altitude alone and the inclusion of landscape- related variables did not improve the classification. In Tuscany, the mean annual temperature allowed classifying 70% of the positive/negative sites correctly. When landscape metrics was included in the multivariate model, an improvement up to 80% was obtained. The presence of riparian vegetation and water was found to be positively correlated with C. imicola presence, whilst forest (including the edge between the forest and cultivated areas) was found to be negatively related to the presence of C. imicola.

摘要

伊氏库蠓被认为是地中海盆地蓝舌病的主要传播媒介之一。然而,存在局部差异。例如,在意大利,伊氏库蠓在撒丁岛是一个稳定且数量众多的种群,广泛分布于全岛,而在意大利大陆的托斯卡纳,其数量从西部和沿海地区的低丰度到该地区东部的没有分布。利用10年收集的昆虫学监测数据,将撒丁岛的52个地点分类为伊氏库蠓低丰度至中等丰度或高丰度,将托斯卡纳的59个地点分类为阳性或阴性。使用基于对象的图像分析方法和一组景观指标,从高分辨率遥感图像中绘制每个地点周围500米缓冲区内的土地覆盖情况。多元分析用于测试景观指标与伊氏库蠓的存在和丰度以及其他生态气候和地形变量之间的统计关联。在撒丁岛,仅根据海拔高度就有75%的地点被正确分类,纳入与景观相关的变量并没有改善分类效果。在托斯卡纳,年平均温度能够正确分类70%的阳性/阴性地点。当将景观指标纳入多元模型时,分类准确率提高到了80%。发现河岸植被和水的存在与伊氏库蠓的存在呈正相关,而森林(包括森林与耕地之间的边缘)与伊氏库蠓的存在呈负相关。

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