Andreas Hamann

Assoc Chair/Graduate Program (Forest Genetics and Global Change Biology), Faculty of Agricultural, Life and Environmental Sci - Renewable Resources Dept

Contact

Assoc Chair/Graduate Program (Forest Genetics and Global Change Biology), Faculty of Agricultural, Life and Environmental Sci - Renewable Resources Dept
Email
andreas.hamann@ualberta.ca
Phone
(780) 492-6429
Address
733 General Services Building
9007 - 116 St NW
Edmonton AB
T6G 2H1

Overview

About

My primary research fields are global change biology, genetics, and climate change adaptation with applications in forest ecology and management. I ask: How are tree species and their populations adapted to the environments in which they occur? How is the growth and health of natural tree populations and planted forests affected by climate change? How should we manage our forest resources under changing environments?

Graduate students and staff in my lab work on climate change adaptation strategies for the forestry sector, ecological and conservation genetics, forest growth, tree improvement, dendrochronology, ecophysiology, and phenology of tree species in boreal, temperate and tropical ecosystems (research). We further maintain GIS and climate databases for North America, South America and Europe (data).


Research

Opportunities for Graduate Students, Postdocs & Research Associates

If you are interested in joining the research group as graduate student, postdoc or research associate, see these opportunities and positions.

Courses

REN R 480 - Applied Statistics for Environmental Sciences

Focuses on problem formulation, method selection, and interpretation of statistical analysis. Covers data management and data visualization, statistical tests for parametric, non-parametric and binomial data, linear and non-linear regression approaches. Participants will gain general statistical literacy and learn how to visualize and analyze data with open-source software packages. Prerequisite: *60. *3 introductory statistics recommended.


REN R 580 - Applied Statistics for Environmental Sciences

Focuses on problem formulation, method selection, and interpretation of statistical analysis. Covers data management and data visualization, statistical tests for parametric, nonparametric and binomial data, linear and non-linear regression approaches. Participants engage in problem-based learning by analyzing data from their thesis research project. Students without a suitable dataset should enroll in two or more *1 REN R 58X courses instead. Prerequisite: *3 introductory statistics recommended.


REN R 690 - Multivariate Statistics for Environmental Sciences

Focuses on visualizing and analyzing complex biological or environmental data for the purpose of prediction and scientific hypothesis testing. Covers classical and modern approaches to ordination and classification, direct and indirect gradient analysis, and models of ecological and environmental interactions. Participants engage in problem-based learning by analyzing data from their thesis research project. Students without a suitable dataset should enroll in two or more *1 REN R 58X courses instead. Prerequisite: *3 introductory statistics recommended.


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