外来入侵物种的大数据获取及预测分析方法研究进展

随着全球经济一体化推进,国际国内贸易往来剧增,生物入侵问题愈加突出,国内外应加强生物安全工作。随着外来入侵物种数据的大量积累,将大数据技术运用到外来入侵物种防控工作中变得至关重要。本文将近些年国内外针对外来入侵物种防控和检测监测工作中涉及的以下3种大数据技术进行综述：1)基于PDA(personal digital assistant)、SOA(service-oriented architecture)、GIS(geographic information system)、GNSS(global navigation satellite system)等移动应用技术设计并开发的外来入侵物种大数据采集方法;2)国内外主要的外来入侵生物数据库;3)预测外来入侵物种潜在地理分布、定殖可能性以及潜在经济损失的大数据预测与分析方法。为生物入侵的早期预警和快速反应提供信息技术支持。

Progress on big data acquisition and predictive analysis methods for invasive alien species

With the advancement of global economic integration, the intensification of international trade and domestic trade and the problem of biological invasion has become more and more prominent. Biosafety work at home and abroad should be strengthened. With the massive accumulation of invasive alien species (IAS) data, it is crucial to apply big data technology to its prevention and control work. This paper aims to summarize the following three big data technologies involved in the prevention and control, detection and monitoring of IAS at home and abroad in recent years: 1) Big data collection method for IAS based on mobile application technologies such as PDA (personal digital assistant), SOA (service-oriented architecture), GIS (geographic information system) and GNSS (global navigation satellite system); 2) Major alien invasive biological databases at home and abroad; 3) Big data prediction and analysis methods to predict the potential geographic distribution, colonization possibility and potential economic losses of IAS. This review will provide information technology support for the early warning and rapid response of biological invasion.