Associate Professor
Forest Measurements
and Modeling
PhD. Ecology and Evolution, Rutgers University, 2001;
B.S. Natural Resource Management, Cook College, 1995; C.T.E. (Certified Tree Expert) 1997
Contact Information
215 Natural Resources Building
Michigan State University
East Lansing, MI 48824
Phone: (517) 355-2399
Fax: (517) 432-1143
Email: macfar24@msu.edu
Courses Taught
- FOR 306 - Forest Biometry
- FOR 420 - Forestry Field Studies
Degree Options for Graduate Students
- M.S. or Ph.D. in Forestry
- Dual M.S. or Ph.D. in Forestry and Ecology and Evolutionary Biology through the Ecology and Evolutionary and Behavioral Biology graduate program
Current Projects
My research program focuses on answering two basic questions:
- How do we know what we think we know about forests? (i.e., forest measurements)
- How can we utilize what we know to better understand how forests work and how to manage them more effectively? (i.e., forest modeling).
As forests are living systems, the context for answering these two basic questions is ecological. Researchers in my lab will work towards developing a mechanistic understanding of how trees grow, compete, survive and reproduce in different environments, and how forest productivity across the landscape reflects these underlying biological processes.
Research Opportunities for Graduate Students
Research assistants working in my program will have the opportunity to get out in the forest and use a wide range of tools to measure it. Back at the lab, students will work toward developing new models and metrics using a variety of computer-based analytical techniques.
Prospective graduate students interested in conducting research in forest measurements and modeling should feel free to contact me. If your prior background is not in forestry you are welcome to apply, so long as you have strong quantitative abilities and an interest in forestry. The interdisciplinary nature of my research program will allow for a broad range of individuals with a wide range of talents to participate, including (but not limited to) those with prior degrees or skills in ecology, computer programming, mathematics and statistics.
Recent Projects
- Developing a host-based spatial risk analysis for the invasive forest pest the Emerald Ash Borer.
- Assessing variation in ecological land type associations in the northeastern United States.
- Describing size-resource-growth relationships in northern hardwood forests using allometric growth models.
- Modeling tree growth and survival using mechanistic light competition models in Pinus taeda plantations.
Recent Publications
MacFarlane, D.W., Green, E.J., Brunner, A., and Amateis, R.L. 2003. Modeling loblolly pine canopy dynamics for a light capture model. For. Ecol.& Manage. 173: 145-168.
MacFarlane, D.W., Green, E.J., Brunner, A., and Burkhart, H.E. 2002. Predicting survival and growth rates for individual loblolly pine trees from light capture estimates. Can. J. For. Res. 32(11): 1970-1983.
MacFarlane, D.W. Linking an Individual Tree Growth Model to a Spatially Explicit Light Capture Model. Proceedings of the Symposium on Statistics and Information Technology in Forestry, September 8-12, 2002, Virginia Polytechnic Institute and State University, Blacksburg, Virginia USA.
MacFarlane, D.W., Coutros, C. and Dunn, J. 2002. "Landscape Classification for the Highlands of New Jersey". N.J. Forest Service. Pub#. NJ-ECOMAP-2, 114 pp. (w / CD-ROM. containing digital maps).
MacFarlane, D.W., Coutros, C. and Dunn, J. 2001. Land Type Associations using Digital Soils Maps and Landscape Topography. In, Proceedings of the Land Type Association Conference: Development and Use in Natural Resources Management, Planning and Research. April 24-26, 2001. University of Wisconsin, Madison, WI.
MacFarlane, D.W., Green, E.J., and Burkhart, H.E. 2000. Population density influence assessment and application of site index. Can. J. For. Res. 30(9): 1472-1475.
MacFarlane, D.W., Green, E.J., and Valentine, H.T. 2000. Incorporating uncertainty into the parameters of a forest growth model. Ecol. Model. 134:27-40.
Green, E.J., MacFarlane, D.W., and Valentine, H.T. 2000. Bayesian synthesis for quantifying uncertainty in predictions from process models. Tree physiology 20: 415-419
Green, E.J., MacFarlane, D.W., Valentine, H.T. and Strawderman, W.E. 1999. Assessing uncertainty in a stand growth model by Bayesian Synthesis. For. Sci. 45(4): 528-538.
Valentine, H.T., Amateis, R.L., Burkhart, H.E., Gregoire, T.G., Hollinger, D.Y. and MacFarlane, D.W. 1999. Growth of loblolly pine in a changing atmosphere. South. J. Appl. For. 23(4):212-216
MacFarlane, D.W., Green, E.J., and Burkhart, H.E. 2000. Population density influences assessment and application of site index. Can. J. For. Res. 30(9): 1472-1475.