Understanding Invasion and Disease Ecology and Evolution through Computational Data Education

通过计算数据教育了解入侵和疾病生态学和进化

• 批准号: 2151820
• 负责人: Travis Marsico
• 金额: $ 199.95万
• 依托单位: Arkansas State University Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151820&HistoricalAwards=false
• 关键词: Understanding; Invasion; Disease; Ecology; Evolution

The living world is a complex thicket of connections among organisms. As humans continue to modify Earth’s biota, novel species interactions — including invasive species and emergent diseases — will become more commonplace. Effective responses to diseases and damaging species hinge on understanding their causes and impacts. Since the scale of novel interactions ranges from molecules to communities and beyond, accurately predicting the outcomes of newly interacting organisms will increasingly require collaborations and integrated tools shared among biologists, ecologists, computer scientists, and data scientists. This NSF Research Traineeship (NRT) project will bridge the fields of invasion biology, disease ecology, and computer science to discover the causes and consequences of novel interactions at multiple levels of biological organization. The project, "Understanding Invasion and Disease Ecology and Evolution through Computational Data Education (UandI-DEECoDE)," will provide its trainees with an interdisciplinary, experiential education; a collaborative and inclusive working environment; research and travel support; and professional skills development for a variety of scientific careers. The traineeship anticipates preparing seventy (70) MS and Ph.D. students, including 16 funded trainees from doctoral programs in Environmental Sciences and Molecular Biosciences. This interdisciplinary research and training program of study will provide students with the computational knowledge and skills necessary to maximize the power and scalability of predicting outcomes of context-dependent novel interactions. It will also provide the biological knowledge necessary to develop innovative and timely solutions to counter emergent diseases and invasive species. Furthermore, trainees will explore the conceptual temporal framework of species interactions (from initial contact to persistence to expansion) to motivate new algorithms for evolutionary computation. Trainees will be immersed in a program that emphasizes communication, teamwork, ethics, mentorship, cross-cultural competency, and leadership throughout their graduate studies. The activities will encompass specific interdisciplinary and project-based coursework, professional development institutes, data science bootcamps, mentorship networks, research pods, and the opportunity to conduct science abroad. Direct local impacts will include long-lasting institutional improvements to graduate student life by sustaining more Ph.D. lines and building a solid and inclusive graduate student culture. Scientific literacy, appreciation, and engagement deficits in Northeast Arkansas will be addressed by infusing UandI-DEECoDE into the local community through targeted outreach activities. Beyond the region, UandI-DEECoDE will address the critical roles of global awareness, information systems, and predictive modeling to tackle the growing issues regarding invasive species and diseases. Targeted recruitment efforts, accessible research and training support, and intentional mentorship will increase participation and scientific representation of historically marginalized groups in STEM. UandI-DEECoDE will contribute scientists to the knowledge-based workforce in the Arkansas Delta, one of the most disadvantaged regions in the United States and beyond. The focus of UandI-DEECoDE at the intersection of disease ecology, invasion biology, and data science makes this program the first of its kind to explicitly address the need to converge these fields to enhance mechanistic understanding of ecology and evolution among newly interacting species.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.

生命世界是由生物体之间的复杂联系构成的。随着人类继续改变地球的生物群，新的物种相互作用——包括入侵物种和新出现的疾病——将变得更加普遍。对疾病和有害物种的有效应对取决于了解它们的原因和影响。由于新型相互作用的范围从分子到群落甚至更远，准确预测新相互作用的生物体的结果将越来越需要生物学家、生态学家、计算机科学家和数据科学家之间的合作和集成工具。这个NSF研究实习生（NRT）项目将连接入侵生物学、疾病生态学和计算机科学领域，在生物组织的多个层面上发现新的相互作用的原因和后果。该项目名为“通过计算数据教育了解入侵和疾病生态和进化”，将为受训者提供跨学科的体验式教育；协作和包容的工作环境；研究和差旅支持；并为各种科学事业发展专业技能。该项目预计将培养70名硕士和博士学生，其中包括16名来自环境科学和分子生物科学博士项目的资助学员。这个跨学科的研究和培训计划将为学生提供必要的计算知识和技能，以最大限度地提高预测情境依赖的新交互结果的能力和可扩展性。它还将提供必要的生物学知识，以制定应对突发疾病和入侵物种的创新和及时解决办法。此外，学员将探索物种相互作用的概念时间框架（从初始接触到持续到扩展），以激发进化计算的新算法。受训者将沉浸在一个强调沟通、团队合作、道德、指导、跨文化能力和领导能力的项目中，贯穿他们的研究生学习。这些活动将包括具体的跨学科和基于项目的课程、专业发展机构、数据科学训练营、指导网络、研究舱以及在国外进行科学研究的机会。直接的地方影响将包括通过维持更多的博士学位线和建立一个坚实和包容的研究生文化来长期改善研究生生活的制度。通过有针对性的外展活动，将undi - deecode注入当地社区，解决阿肯色州东北部的科学素养、鉴赏力和参与能力不足的问题。在该区域之外，卢旺达国际生物多样性研究所将探讨全球意识、信息系统和预测建模在解决日益严重的入侵物种和疾病问题方面的关键作用。有针对性的招聘工作、可获得的研究和培训支持以及有意的指导将增加历史上边缘化群体在STEM中的参与和科学代表性。andi - deecode将为阿肯色州三角洲的知识型劳动力提供科学家，这是美国和其他地区最落后的地区之一。unandi - deecode的重点是疾病生态学、入侵生物学和数据科学的交叉，这使得该项目成为同类项目中第一个明确解决这些领域融合的需要，以增强对新相互作用物种之间生态学和进化的机制理解。美国国家科学基金会研究实习生（NRT）计划旨在鼓励开发和实施大胆的、具有潜在变革性的STEM研究生教育培训新模式。该项目致力于通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式，在高优先级跨学科或融合研究领域对STEM研究生进行有效培训。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。