Associate Professor, Forest Measurements and Modeling
PhD in Ecology and Evolution, Rutgers University, 2001
BS in Natural Resource Management, Cook College, 1995
CTE (Certified Tree Expert), 1997
My research program focuses on answering two basic questions:
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., Kuyah, S., Mulia, R., Dietz, J., Muthuri, C., and Van Noordwijk, M. 2014. Evaluating a non-destructive method for calibrating tree biomass equations derived from tree branching architecture. Trees: Structure and Function, DOI 10.1007/s00468-014-0993-2.
Ver Planck N.R., MacFarlane, D.W. 2014. Modelling vertical allocation of tree stem and branch volume for hardwoods. Forestry; 00, 1–16 doi:10.1093/forestry/cpu007
An, Hong Su, MacFarlane, David W. 2012. Comparing a new model-based method to fixed-area sampling for estimating the abundance of standing dead trees. Forestry, 2013; 86, 231–239, doi:10.1093/forestry/cps079.
Wang, Z., MacFarlane, D.W. 2012. Evaluating the biomass production of coppiced willow and poplar clones in Michigan, USA, over multiple rotations and different growing conditions. Biomass and Bioenergy, 46, 380-388.
Woodall, C.W., Domke, G.M., MacFarlane, D.W., and Oswalt, C.M. 2011. Comparing field- and model-based standing dead tree carbon stock estimates across forests of the US. Forestry, 2011; doi: 10.1093/forestry/cpr065
Finley, A.O., S. Banerjee, and D.W. MacFarlane. 2011. A Hierarchical Model for Quantifying Forest Variables over Large Heterogeneous Landscapes with Uncertain Forest Areas. Journal of the American Statistical Association. March 2011, Vol. 106, No. 493, 31-48.
MacFarlane, D.W. 2011. Allometric scaling of branch volume in hardwood trees in Michigan, USA: implications for improvements in above-ground forest carbon biomass inventories. For. Sci. 57(6):451– 459.
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.
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.