讲座题目：When and where to expect species: linking ecological niche model and phenology events mapping
主 讲 人：朱耿平 助理教授
主 持 人：黎绍鹏 教授
开始时间：7月24日 09:30
讲座地址：腾讯会议ID: 939-574-990（密码：819668）
主办单位：beat365
报告人简介：
朱耿平，华盛顿州立大学昆虫系，博士后/助理教授(career track)。报告人以昆虫为主要研究对象围绕生态位模型运用开展工作，在入侵昆虫风险分析和生物多样性保护等领域取得原创成果，提出了一系列新的策略来提升生态位模型的空间转移能力，成功地将昆虫生理耐受性整合至生态位模型，并在实际运用中揭示了金环胡蜂，茶翅蝽和美国白蛾等10余种重要入侵害虫的生态位动态及全球潜在分布。近五年以第一作者或通讯作者在PNAS、Ecography、Ecological Applications、J Pest Science等昆虫学或生态学期刊上发表SCI论文10余篇，h-index = 20，曾主持国家自然科学基金面上项目和青年项目，两次获得中国精品期刊顶尖学术论文奖。近年来，报告人将基于研究和实际应用相结合，注重推动生态模拟和空间分析技术在区域入侵物种(昆虫)风险分析和综合治理中的运用。
报告内容简介：
The importance of habitat suitability predictions of where species are potentially distributed were well recognized, with which practitioners could establish protected areas for conservation or plan field survey of introduced species. However, the date of when species would be active across geography were often overlooked, without which we might miss proper timeline for action intervention. Putting phenological dates on the map would provide both geographic distribution of species and the date of their phenological activity. With the increasing availability of daily grid data, we are now able to put phenology event dates on the map, with which we could expect when and where to find species. In addition, niche and distributional model techniques are now widely used in habitat suitability predictions, there are questions remain unresolved of using these suitability predictions for planning biodiversity conservation or invasive species management.
In this presentation, I will (1) briefly talked about my past work on niche and distributional modeling applications; I will (2) focus on recent work on using niche model prediction for planning field survey of invasive species, where I will introduce my new enmRoute R package, together with the Shinyapp that we developed to facilitate its application; I will (3) demonstrate my ongoing work on phenological event mapping, where I will show two approaches (i.e., process and correlative approaches) that could put phenological events on the map: the former is by relating species’ temperature development threshold and thermal requirements to the daily grid temperature; whereas the latter seeks to predict the date of phenological event via statistical approach using citizen data. I expect these techniques could greatly support invasive species management and biodiversity conservation by responding when and where to expect species.
