David MacFarlane, Ph.D.
Associate Professor, Forest Measurements and Modeling215 Natural Resources Building
Ph.D. in Ecology and Evolution, Rutgers University, 2001
B.S. in Natural Resource Management, Cook College, 1995
C.T.E. (Certified Tree Expert), 1997
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).
Forests are complex ecosystems that are intricately linked to environmental quality and human industry. I am interested in developing new methods for measuring attributes of forests, particularly those attributes that are typically given less attention (under-measured), such as tree bark & branch measurements. I am also interested in improving methods for accurate forest resource inventories, particularly wood products and carbon biomass inventories. This involves developing novel survey and sampling methodologies as well as new measurements. An exciting area of research I am working in now involves using models to improve sampling methods.
MacFarlane, D.W. 2010. Predicting branch to bole volume scaling relationships from varying centroids of tree bole volume. Can. J. For. Res. 40(12): 2278–2289.
Finley, A.O., S. Banerjee, and D.W. MacFarlane. A hierarchical model for predictingforest variables over large heterogeneous domains. Journal of the American Statistical Association. In Press.
MacFarlane, D.W. Allometric scaling of branch volume in hardwood trees in Michigan, USA: implications for improvements in above-ground forest carbon biomass inventories. For. Sci., In Press.
MacFarlane, D.W. and Luo, A. 2009. Quantifying tree and forest bark structure with a bark-fissure index. Can. J. For. Res. 39(10): 1859–1870
MacFarlane, D.W. 2008. Potential availability of urban wood biomass in Michigan: implications for energy production, carbon sequestration and sustainable forest management in the USA. Biomass & Bioenergy, 33, 628-634.
Rubin B.D. and MacFarlane, D.W. 2008. Using the space-time permutation scan statistic to map anomalous diameter distributions drawn from landscape-scale forest inventories. For. Sci. 54(5): 523-533.
MacFarlane, D.W. 2007. Quantifying urban saw timber abundance and quality in southeastern Lower Michigan, U.S. Arboriculture and Urban Forestry 33(4): 253-263.
Zakrzewski, W.T., MacFarlane D.W. 2006. Regional stem profile model for cross border comparisons of harvested red pine (Pinus resinosa Ait.) in Ontario and Michigan, For. Sci. 52(4): 468-475.
MacFarlane, D.W. and Kobe, R.K. 2006. Selecting models for capturing tree size effects on growth-resource relationships. Can. J. For. Res. 36: 1695-1704.