Generalized Linear and Nonlinear Mixed Models for Longitudinal and Spatial Data

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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.