EAGER: Environmental drivers of biodiversity: leveraging a history of NSF-funded research to test models of butterfly responses to global change

EAGER：生物多样性的环境驱动因素：利用 NSF 资助的研究历史来测试蝴蝶对全球变化的反应模型

• 批准号: 1839021
• 负责人: Leslie Ries
• 金额: $ 30万
• 依托单位: Georgetown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1839021&HistoricalAwards=false
• 关键词: EAGER; Environmental; drivers; biodiversity; leveraging

Our most pressing ecological priority is to determine how human activity is driving global shifts in biodiversity and how we can balance preserving ecosystem function with the needs of a growing human population. The PI proposes new ecological research on the Pierid family of butterflies that have been the subject of research on thermal responses over the last 40 years. The overarching goal of this research is to extend and generalize Species Distribution Models (SDM), the dominant modeling approach to understanding large-scale shifts of biodiversity in the face of global change. The PI will leverage that 40 year legacy of thermal response research to develop general models of how butterflies respond to changing environments. In order to verify how well these models perform and their ability to make both species-specific and general predictions, models will be validated with large-scale monitoring data sets. There is a growing resource of citizen-science monitoring data but there are also several NSF-funded academic monitoring programs that have occurred over the years. Another aspect of this project is to bring together those academic and citizen science data into a unified publicly-available data set. The research is expected to advance macrosystems ecology study of thermal ecology and responses of biodiversity, especially ectotherms while also serving as a strong demonstration of data reuse by focusing on a well-studied and wide-spread group of butterfly species, the Pierids. Research in macrosystems ecology requires two disparate ecological data types that are rarely generated or employed by the same research community: mechanistic, experimental data and data from large spatiotemporally-replicated monitoring programs. The two dominant environmental factors driving the distribution and abundance of butterflies are thermal environment (impacted by climate) and host-plant availability (impacted by land use change and climate). There are 14 previous and current NSF-funded projects focused on primarily thermal, but also nutritional drivers of performance in one family of butterflies, Pierids. Thermal environments have several impacts on butterfly performance. Indirectly, temperature drives the seasonal timing and distribution of host-plant (food) resources. It also provides energy for growth for developing caterpillars. Host-plants are also a key component of butterfly development, not just for the obvious reason that they acquire all their nutrition for growth from these plants, but the quality of the plants also determines their growth rate. There has been a long legacy of research on the thermal and nutritional constraints of growth for many insects, but these models have not yet been fully employed to make range-wide predictions for butterflies. We propose to bring together a legacy of NSF-funded research on butterfly responses to environmental change with long-term monitoring data that can be used, respectively, to generate and test mechanistic SDMs over multiple spatiotemporal scales.This project is supported by the National Science Foundation?s Public Access Initiative which is managed by the NSF Office of Advanced Cyberinfrastructure on behalf of the Foundation.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.

我们最紧迫的生态优先事项是确定人类活动如何推动全球生物多样性的变化，以及我们如何在保护生态系统功能和满足不断增长的人口需求之间取得平衡。PI建议对Pierid蝴蝶家族进行新的生态学研究，该家族在过去40年里一直是热反应研究的主题。这项研究的总体目标是扩展和推广物种分布模型(SDM)，这是理解面对全球变化的生物多样性大规模变化的主要建模方法。PI将利用40年热反应研究遗产来开发蝴蝶如何对不断变化的环境做出反应的一般模型。为了验证这些模型的表现有多好，以及它们做出特定物种和一般预测的能力，模型将用大规模监测数据集进行验证。公民科学监测数据的来源越来越多，但也有几个由NSF资助的学术监测项目多年来一直在进行。该项目的另一个方面是将这些学术和公民科学数据整合到一个统一的公开可用的数据集中。这项研究有望推进热生态和生物多样性响应的大系统生态学研究，同时也是数据重用的有力证明，重点放在研究得很好和分布广泛的蝴蝶种群上。宏观系统生态学的研究需要两种不同的生态数据类型，而这两种数据类型很少被同一研究界产生或使用：机械性的实验数据和来自大型时空复制监测项目的数据。驱动蝴蝶分布和丰度的两个主要环境因素是热环境(受气候影响)和寄主植物可用性(受土地利用变化和气候影响)。之前和现在有14个由NSF资助的项目，主要集中在热量，但也有营养驱动一个蝴蝶家族的表现，Pierids。热环境对蝴蝶的性能有几个影响。间接地，温度决定了寄主植物(食物)资源的季节性时间和分布。它还为发育中的毛虫提供生长所需的能量。寄主植物也是蝴蝶发育的关键组成部分，不仅因为它们从寄主植物那里获得所有生长所需的营养，而且寄主植物的质量也决定了它们的生长速度。关于许多昆虫生长的温度和营养限制的研究已经有很长一段时间了，但这些模型还没有完全用于对蝴蝶进行全范围的预测。我们建议将美国国家科学基金会资助的蝴蝶对环境变化响应的研究成果与长期监测数据结合起来，分别用于在多个时空尺度上生成和测试机械性SDMS。该项目由国家科学基金？S公共访问倡议支持，该倡议由美国国家科学基金会高级网络基础设施办公室代表基金会管理。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智力优势和更广泛的影响审查标准进行评估，被认为值得支持。