OPUS: A Computational Theory of Biodiversity

OPUS：生物多样性的计算理论

• 批准号: 2241353
• 负责人: Jorge Soberon
• 金额: $ 13.91万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241353&HistoricalAwards=false
• 关键词: OPUS; Computational; Theory; Biodiversity

Biodiversity can be defined as the patterns of distribution of species, genes, and ecosystems on the planet. It is amply documented that the activities of human societies are substantially increasing the extinction rate of species, the loss of genetic variation, and the degradation of ecosystems. This loss imperils many of the services that biodiversity offers such as pollination, pest control, cleansing of water, promoting soil health, and providing resources for innovation in industry and health. Thus, forecasting how the distribution of species change through time is of urgent and critical importance to conserve the remaining biodiversity on this planet. This project will make important contributions to this goal by synthesizing publicly-available data and decades of previous research to develop novel computational models that will realistically predict changes in the distributions of species, communities, and ecosystems. Applications of these models will provide insight into the expansion of invasive species, emergence of human and agricultural diseases, and the impacts of climate change on threatened and endangered species. Results of this project include visual and dynamic maps that will form interactive displays at the University of Kansas Natural History Museum. An important training component is the involvement of a graduate student in the development of the dynamic mathematical models of species distributions as well as the writing of the book and software. The synthesis of decades of research and data will culminate in a book and software that will be accessible to the evolution and ecology research community so that the new models developed in this project can be used broadly and extensively across many species and ecological communities around the world. Currently, most models of species distributions are static and based on presence-absence data; this project will incorporate additional data sources such physiology and species interactions to generate dynamic distribution models for those species. Furthermore, this project will use these models from multiple species to represent ecological changes of whole communities and environments through time and to predict biodiversity patterns over entire landscapes.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.

生物多样性可以定义为地球上物种、基因和生态系统的分布模式。有充分证据表明，人类社会的活动大大增加了物种的灭绝速度、遗传变异的丧失和生态系统的退化。这种损失危及生物多样性提供的许多服务，例如授粉、害虫防治、净化水、促进土壤健康以及为工业和健康创新提供资源。因此，预测物种分布随时间的变化对于保护地球上剩余的生物多样性至关重要。该项目将通过综合公开数据和数十年的先前研究来开发新颖的计算模型，从而现实地预测物种、群落和生态系统分布的变化，从而为这一目标做出重要贡献。这些模型的应用将有助于深入了解入侵物种的扩张、人类和农业疾病的出现以及气候变化对受威胁和濒危物种的影响。该项目的成果包括视觉和动态地图，这些地图将在堪萨斯大学自然历史博物馆形成交互式展示。一个重要的培训内容是研究生参与物种分布动态数学模型的开发以及书籍和软件的编写。数十年的研究和数据的综合将最终形成一本书和软件，可供进化和生态学研究界使用，以便该项目开发的新模型可以在世界各地的许多物种和生态群落中广泛使用。目前，大多数物种分布模型都是静态的，并且基于存在与不存在数据；该项目将纳入生理学和物种相互作用等额外数据源，以生成这些物种的动态分布模型。此外，该项目将使用来自多个物种的这些模型来代表整个群落和环境随时间的生态变化，并预测整个景观的生物多样性模式。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。