Bill is a plant ecologist and statistical ecologist with a long-standing research career focused on understanding the structure and function of ecological systems using rigorous statistical methods. His work spans experimental and observational approaches to plant trait ecology, community assembly, and multivariate analysis. He has authored four influential scientific monographs and published over 170 peer-reviewed articles, making significant contributions to both ecological theory and statistical methodology in ecology.
Bill is particularly known for advancing causal inference methods in ecological research, including path analysis and structural equation modeling, and for promoting clear, reproducible workflows in data analysis. He integrates field ecology with statistical innovation, aiming to disentangle complex cause-and-effect relationships in natural systems.
Education & Career
• PhD in Plant Ecology
• Professor Emeritus, Université de Sherbrooke, Québec
• Author of Cause and Correlation in Biology and other key monographs in ecological statistics
Research Focus
Bill’s research bridges ecological theory and quantitative methods. His focus lies in understanding how environmental factors shape plant communities and trait distributions, and in developing and applying statistical tools—especially in R—for uncovering causal relationships in multivariate ecological data.
Current Projects
• Exploring functional trait variation and community assembly in plant systems
• Applying structural equation modeling to ecological datasets
• Developing accessible teaching materials for statistical ecology using R
Professional Contributions
Bill is internationally recognized for his work on causal modeling in ecology and has served as a mentor, collaborator, and consultant on numerous interdisciplinary research projects. His statistical expertise is widely sought in the ecological research community.
Teaching & Skills
• Experienced educator in plant ecology, statistical modeling, and multivariate analysis
• Teaches and writes about causal inference, regression methods, and model evaluation in R
• Committed to improving statistical literacy among ecologists and promoting open science practices
He has published four scientific monographs and over 170 peer-reviewed papers.