NSF Postdoctoral Fellowship in Biology FY 2020: Integrating biological collections and observational data sources to estimate long-term butterfly population trends

2020 财年 NSF 生物学博士后奖学金：整合生物收藏和观测数据源来估计蝴蝶种群的长期趋势

• 批准号: 2010698
• 负责人: Courtney Davis
• 金额: $ 13.8万
• 依托单位: Davis, Courtney Lynn
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2010698&HistoricalAwards=false
• 关键词: NSF; Postdoctoral; Fellowship; Biology; FY

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2020, Research Using Biological Collections. The fellowship supports research and training of the Fellow that will use biological collections in innovative ways. Recent studies suggest the possibility of being in the middle of an “insect apocalypse,” but true rates of decline for most insect species are unknown because of data limitations. For many insect species, biological collections (including digital specimens) are the only available long-term source of data on insect numbers and diversity. This postdoctoral research project aims to use biological collection data and other observational data sources to identify current trends and reasons for butterfly population changes. The project will also raise public awareness about conservation and the value of museum collections and promote additional museum-based research. To broaden the impact of the work, a museum exhibit and educational module will be designed, and undergraduates will be mentored in research. Biological collection's data exhibit spatiotemporal and collector-specific biases that make it difficult to estimate population trends using only digitized museum records. These biases have limited the use of museum records such that there is an untapped wealth of data available to evaluate the impacts of global changes on insects. This project evaluates the utility of newly developed data integration methods for estimating long-term population trends using multiple data sources, including digitized museum records, opportunistic citizen science observations, and structured count data from monitoring schemes that follow standardized protocols. An extensive simulation study will be used to evaluate the conditions under which it is useful and reasonable to integrate these three data types to track long-term population trends. An empirical case study focuses on estimating long-term trends for 32 open-habitat butterfly species in the Midwest Plains. Achievement of these research objectives will result in a transferable modeling framework that allows researchers to use biological collections data to reconstruct population trends through time. This research will also be used by the Lepidoptera of North America Network Thematic Collection’s Network to identify geographic regions in North America that are most amenable for inclusion in an integrated analysis and should be prioritized in future targeted digitization efforts. To broaden the impact of the work, undergraduates will be mentored in independent research, and an interactive museum display and K-12 educational module on butterfly ecology will be generated.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

本行动资助美国国家科学基金会2020年度生物学博士后研究奖学金，利用生物馆藏进行研究。该奖学金支持以创新方式使用生物馆藏的研究员的研究和培训。最近的研究表明，可能正处于“昆虫末日”之中，但由于数据限制，大多数昆虫物种的真实下降率尚不清楚。对于许多昆虫物种来说，生物标本（包括数字标本）是昆虫数量和多样性唯一可用的长期数据来源。本博士后研究项目旨在利用生物采集数据和其他观测数据源来确定当前蝴蝶种群变化的趋势和原因。该项目还将提高公众对保护和博物馆藏品价值的认识，并促进更多以博物馆为基础的研究。为了扩大作品的影响，将设计一个博物馆展览和教育模块，并指导本科生进行研究。生物馆藏的数据表现出时空和收藏者特定的偏见，这使得仅使用数字化博物馆记录来估计人口趋势变得困难。这些偏见限制了博物馆记录的使用，因此有大量未开发的数据可用于评估全球变化对昆虫的影响。该项目评估了新开发的数据集成方法的效用，该方法使用多种数据源来估计长期人口趋势，包括数字化博物馆记录、机会主义公民科学观察和遵循标准化协议的监测方案的结构化计数数据。将进行一项广泛的模拟研究，以评价在何种条件下将这三种数据类型结合起来以跟踪长期人口趋势是有用和合理的。以美国中西部平原32种开放生境蝴蝶为研究对象，对其长期趋势进行了研究。这些研究目标的实现将导致一个可转移的建模框架，使研究人员能够使用生物收集数据来重建人口随时间的趋势。这项研究还将被北美网络主题收集网络鳞翅目用于确定北美最适合纳入综合分析的地理区域，并应在未来有针对性的数字化工作中优先考虑。为了扩大作品的影响，将指导本科生进行独立研究，并将产生一个互动的博物馆展示和K-12蝴蝶生态学教育模块。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。