基于环境DNA动力学建模的河流鱼类物种分布与丰度评估

所有生物体在其栖息的环境中会留下DNA痕迹，检测环境样品中DNA信号来示踪物种分布正引领生物监测技术的变革。目前关于环境DNA的研究聚焦于其监测方法标准化方面，但对河流水体中环境DNA来源、衰减和运输等动力学过程认知不足。环境DNA随水体平流、滞留和再悬浮过程发生迁移和衰变，阻碍了DNA信号的准确检测。识别河流水体中环境DNA动力学过程，并将环境DNA数据与水文参数建模可有效提升监测结果准确性。本课题将首先通过野外微宇宙实验分析河流典型鱼类环境DNA衰减和运输等特征；其次，揭示水文条件变化对环境DNA动力学过程的影响，建立基于水文特征的环境DNA数据模型；最后，结合模型场景模拟和多样点DNA源验证，采用计算机迭代算法，高分辨地解析河流系统中环境DNA信号来源，准确且量化地评估鱼类物种分布与丰度。本课题将为河流水体中环境DNA动力学过程识别及基于环境DNA的鱼类物种监测提供理论和方法支撑。

All organisms leave traces of DNA in their habitats, detecting the DNA signals in environmental samples to trace occurrence patterns of species has been revolutionizing the biomonitoring technology. Currently, the study on environmental DNA (eDNA) focuses on the standardization of monitoring methods. However, the understanding of the source, decay and transport of eDNA in rivers is insufficient. eDNA migrates and decays with the processes of water advection, retention and resuspension, which restricts the accuracy of DNA signal detection. Identifying the of eDNA dynamics in rivers and modeling the eDNA data with hydrological parameters can effectively improve the accuracy of monitoring results. In this project, we first analyze the eDNA dynamics (e.g., decay and transport) of typical fish species in rivers using field microcosm systems; secondly, reveal the effects of hydrological conditions (e.g., water temperature, velocity and water flow) on the eDNA dynamics process, and develop the hydrology-based eDNA data models; finally, combined with model scenario simulation and multiple point DNA source, detect eDNA signals in river ecosystems with high resolution to accurately and quantitatively analyze the fish species distribution and abundance using computer iterative algorithm. This project will provide theoretical and methodological support for the identification of eDNA dynamics process in rivers and fish species monitoring based on eDNA technology.