Generalized Linear and Nonlinear Mixed Models for Longitudinal and Spatial Data

纵向和空间数据的广义线性和非线性混合模型

• 批准号: RGPIN-2015-06124
• 负责人: Ma, Renjun
• 金额: $ 0.8万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613959
• 关键词: Generalized; Linear; Nonlinear; Mixed; Models

The abundance of species over time and space is of great interest in the contemporary ecology, conservation biology, and natural resource management. Observed abundance of different species of plants or animals at the same location is usually negatively correlated in a competitive community, whereas abundance of the same specie tends to be positively correlated because of shared environment and other underlying community characteristics. As the weed community is influenced both directly by fertilizers and indirectly through the effect of crop competition, the correlation is influenced by both shared environmental characteristics and competition. My research interests lie in the development of multivariate random effects models where random effects can be used to account for community effects and the association among neighbouring communities. Our new statistical methods can help the search for community composition patterns of species and their relationship with available environmental characteristics. For example, predicting the spatial distribution of wildlife populations is an important component of the development of management strategies for their conservation. Understanding abundance of species over time and space helps decision makers geographically target resource allocation at appropriate times in an attempt to remediate problem areas.

物种在时间和空间上的丰富性引起了当代生态学、保护生物学和自然资源管理的极大兴趣。在竞争性群落中，同一地点不同物种的植物或动物的丰度通常呈负相关，而由于共享环境和其他潜在的群落特征，同一物种的丰度往往呈正相关。由于杂草群落既受到肥料的直接影响，又受到作物竞争效应的间接影响，因此相关性受到共同的环境特征和竞争的影响。我的研究兴趣在于开发多元随机效应模型，其中随机效应可用于解释社区效应和邻近社区之间的关联。我们的新统计方法可以帮助寻找物种的群落组成模式及其与现有环境特征的关系。例如，预测野生动物种群的空间分布是制定野生动物保护管理策略的重要组成部分。了解物种在时间和空间上的丰富程度有助于决策者在适当的时间进行地理上的资源分配，以尝试修复问题区域。