VBORNET缺口分析:蚊子媒介分布模型用于在缺乏记录的地区确定潜在物种分布区域。

Open health data Pub Date : 2016-12-19 DOI:10.5334/OHD.27
F. Schaffner, V. Versteirt, W. Bortel, H. Zeller, W. Wint, N. Alexander
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引用次数: 7

摘要

这是介绍建模向量分布的许多计划数据论文中的第一篇,本文中的模型是在ECDC资助的VBORNET项目期间产生的。这项工作在目前由ECDC和EFSA共同资助的VectorNet项目下继续进行。该数据文件包含作为VBORNET项目的一部分产生的沙蝇模型输出。进一步的数据论文将在采样季节结束后发表,届时将获得更多的实地数据,允许对更多的物种进行建模或验证和更新现有模型。这里描述的数据包包括2013年和2014年首次建模的沙蝇物种,作为VBORNET差距分析工作的一部分,旨在确定缺乏记录的地区的潜在物种分布区域。它包括四个物种模型以及基于陆地类别和环境限制的适宜性掩模。本文包括的种类有白蛉、白蛉、白蛉、白蛉和白蛉。这些物种在项目区域(欧洲、地中海盆地、北非和欧亚大陆)内的已知分布目前或多或少不完整。这些模型旨在填补预测分布的空白,提供a)协助有针对性的调查,以收集那些没有现场验证信息的地区的分布数据,以及b)项目范围内分布的初步指示。
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VBORNET gap analysis: Mosquito vector distribution models utilised to identify areas of potential species distribution in areas lacking records.
This is the first of a number of planned data papers presenting modelled vector distributions, the models in this paper were produced during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. This data paper contains the sand fly model outputs produced as part of the VBORNET project. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models. The data package described here includes those sand fly species first modelled in 2013 and 2014 as part of the VBORNET gap analysis work which aimed to identify areas of potential species distribution in areas lacking records. It comprises four species models together with suitability masks based on land class and environmental limits. The species included within this paper are Phlebotomus ariasi, Phlebotomus papatasi, Phlebotomus perniciosus and Phlebotomus tobbi. The known distributions of these species within the project area (Europe, the Mediterranean Basin, North Africa, and Eurasia) are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a) assistance in targeting surveys to collect ­distribution data for those areas with no field validated information, and b) a first indication of project wide distributions.
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