Postdoctoral Research Fellowship in Biology: Spatiotemporal Dynamics of Biodiversity–Disease Relationships

该行动资助了2022财年的NSF生物学博士后研究奖学金，即调查基因组，环境和表型之间相互作用的生命规则的综合研究。该研究金支持研究员的研究和培训，以创新的方式为生活规则领域做出贡献。该项目将促进对疾病风险动态的科学理解。野生动物疾病在自然界中很常见，偶尔会从野生动物“蔓延”到人类。尽管与人类福祉有这种联系，但科学家们对与野生动物疾病的出现和传播有关的环境属性缺乏全面的了解。特别是，生物多样性与疾病风险之间的关系（例如，生物多样性是放大还是稀释了疾病风险）的认识很少，也不清楚这种关系如何随着全球变化而改变。因此，该项目将采用最先进的建模方法来了解生物多样性和疾病风险之间的动态关系。通过寻找生物多样性与疾病关系的一般性并记录其背景依赖性，该项目将加强对野生动物疾病对人类健康构成的威胁的未来预测。该项目将利用国家生态观测网（氖）关于啮齿动物-蜱虫（莱姆病）和鸟类-蚊子（西尼罗河病毒）系统的数据，描述生物多样性-疾病关系的时空变化特征。特别是，该研究员将调查1）两个系统的生物多样性-疾病关系在空间上是否相似，2）这些关系对生物多样性变化的敏感性，以及3）季节性和气候对生物多样性-疾病关系的时间动态的影响。该研究员将开发多尺度的综合模型，允许多个数据集（即，关于主机以及向量的数据）被组合成一个内聚的整体。综合模型应用贝叶斯框架将实现这一联系，估计主机子模型中的主机生物多样性指标，然后使用这些数量作为疾病子模型中的预测因子。综合模型由于其在理解复杂现象方面的有效性而在生物学科中日益突出，该项目将为未来的研究提供信息，这些研究将结合联合收割机数据集来解决疾病生态学中的问题。除了研究之外，研究员还将开展职业培训活动（例如，该奖项反映了NSF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。

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2022, Integrative Research Investigating the Rules of Life Governing Interactions Between Genomes, Environment and Phenotypes. The fellowship supports research and training of the fellow that will contribute to the area of Rules of Life in innovative ways. This project will advance scientific understanding of disease risk dynamics. Wildlife diseases are common in nature and occasionally “spill over” from wildlife to human populations. Despite this link to human well-being, scientists lack a comprehensive understanding of the environmental attributes associated with the emergence and spread of wildlife diseases. In particular, the relationship between biodiversity and disease risk (e.g., whether biodiversity amplifies or dilutes disease risk) is poorly understood, and it is unclear how this relationship might be altered with ongoing global change. Therefore, the project will apply state-of-the-art modeling approaches to understand the dynamic relationship between biodiversity and disease risk. By seeking generalities in biodiversity–disease relationships and documenting their context dependence, the project will enhance future predictions of threats to human health posed by wildlife diseases. The project will characterize spatiotemporal variation in biodiversity–disease relationships using data from the National Ecological Observatory Network (NEON) on rodent–tick (Lyme disease) and bird–mosquito (West Nile virus) systems. In particular, the fellow will investigate 1) whether biodiversity–disease relationships from the two systems scale similarly over space, 2) the sensitivity of these relationships to biodiversity change, and 3) the influence of seasonality and climate on temporal dynamics of biodiversity–disease relationships. The fellow will develop multiscale, integrated models, which allow multiple datasets (i.e., data on hosts as well as vectors) to be combined into a cohesive whole. The integrated model—applied in a Bayesian framework—will accomplish this linkage by estimating host biodiversity metrics in a host submodel and then using these quantities as predictors in a disease submodel. Integrated models are gaining prominence in biological disciplines due to their effectiveness in understanding complex phenomena, and this project will inform future investigations that combine datasets to tackle problems in disease ecology. In addition to the research, the fellow will undertake career training activities (e.g., statistical workshops) and engage in activities to broaden participation in science, including mentoring an undergraduate student in summer research and leading a training module on using NEON data in a graduate ecology course.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.