Job/Research Area: Biodiversity and Landscape Modeling
Major Responsibilities/Research Interests: Community ecology, species diversity and conservation, ecological methodologies and modeling, and spatial statistics.
Introduction to the theory and application of biodiversity with an emphasis on quantitative analysis of biodiversity data. The course covers the concepts of biodiversity (genetic, species and ecosystem), dynamics of species populations, diversity measurements, estimation of species richness, diversity patterns (species-abundance, species-area, distribution-abundance, local-regional, beta diversity, richness-productivity, etc.), mechanisms of biodiversity maintenance, and methods and models for biodiversity conservation. Laboratory session involves using statistical software R for analyzing various real diversity data. Prerequisite: REN R 364.
Winter Term 2022Focuses on analyzing complex biological or environmental data for the purpose of prediction and scientific hypothesis testing. Covers multiple regression for a continuous response, logistic regression for a binary response, and log-linear models for count data, non-linear regression and generalized additive models for non-linear relationships, path analysis using structural equation modeling. Prerequisite: knowledge equivalent to REN R 581 and REN R 582 is required.
Winter Term 2022