应用微地形生态位辨析算法提高物种分布模型模拟精度的研究

Simulation using species distribution models (SDMs) is one of the most important methodology in studying orgasms' response to climate change. Ecological niche is the kernel concept of it. It is seriously inadequate in concerning the problem of micro-topographical effect in describing niches in most SDMs. This project aims at solving micro-topographical niche (MTN) problem in SDMs by developing a new algorism: MTN discriminating algorithm. The new method is expected to significantly improve the accuracy of SDMs in mountainous areas. The key is to solve the conflicts between calculating complexity for lage geographical areas and high preciseness in describing the MTN. Research contents include: evaluation of the effects of MTN; development of the MTN discriminating algorism; development of method implementing the high precision niche to coarse resolution grid covering large geographical area; and implementing the new methodology to a case study in species in Pinaceae family-reconstructing their historical distributions and simulating their distributions in future climatic scenarios. The MTN algorism is a whole new exploration in this project, and there are certain new ideas in virtual species application, self-adaptive grid generation, and the concept of niche spectrum in sub-grid scale niche calculation. By solving the problem of MTN effect, the new methodology may provide new insights into research topics and management issues, such as: migration history of species in high precision, phylogenic explanation of high resolution genetic patterns, the general trends response of taxonomic groups to climate changes, and adaptive management to climate change in biodiversity conservation.

物种分布模型是研究生物对全球变化响应的重要工具，生态位理论是其核心概念。现有模型对生态位微地形效应的关注严重不足。本研究旨在通过开发微地形生态位辨析算法，处理微地形生态位效应，达到提高在大尺度地理范围内物种分布模拟精度的目标。关键难点在于兼顾大地理范围预测运算复杂性的限制与微地形生态位描述的精确性。研究内容包括：微地形效应评估、微地形生态位辨析算法模块开发、高精度生态位在粗网格上预测算法模块开发，及该新方法在中国松科植物历史分布区重建和未来气候情景下分布模拟的实例研究。微地形生态位辨析算法是本项目独创的全新尝试。项目在虚拟物种应用、自适应网格设计和亚网格生态位谱算法方面上也具有一定创新。项目对微地形生态位效应问题的解决，将对物种分布迁移历史的精细描述、高精度空间遗传格局的谱系地理解释、地形影响下生物类群对全球变化响应规律和生物多样性趋势研究以及应对气候变化的生物多样性保护决策提供新信息。

本项目针对全球变化普遍采用的生态位模型处理微地形影响不足的局面，通过新的微地形算法解决高空间分辨率与大范围计算难于兼顾的局面，开发了包括自适应网格在内的新算法和生态位谱算法，成功解决了上述关键问题。除了在Fortran语言编程下能够在高性能计算机下运行外，还额外开发了适应于个人电脑的R程序软件包。在应用方面，我们把新的算法应用于中国松科植物在未来气候变化情景下的应用，取得了良好效果，同时也正在进行古气候下松科植物分布历史的重建。不足之处是我们关于较大规模的野外考察和验证工作有所延迟，希望能在项目延续期内继续工作。另外，我们打算把该算法进一步完善，应用于区域尺度上生物多样性的变化和物种周转率的研究中。