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Dr. Treg Christopher

Dr. Christopher is now at the Washington State Department of Natural Resources.

I am interested in spatial scaling and context issues related to both ecological modeling and environmental economics. Some example questions related to these topics are: How do different resolutions of spatial data inputs affect model outcomes? How does context and distance from an ecosystem service (i.e. spatial discounting) affect an individual's or stakeholder-group's perception of value?

My work at the Institute for Natural Resources was aiding the development of landscape-level State and Transition models for predicting forest and arid-land growth, succession and disturbances under a no-management scenario and for evaluating the possible effects of a variety of management/treatment scenarios. The website for this on-going project is: .

My dissertation research (PhD University of Vermont, 2009) focused on improving methods for incorporating spatial scale into ecosystem services valuation. My specific research topic used multilevel (regression) modeling to determine the marginal contribution of open/green space to the value of residential properties in Baltimore, Maryland (hedonic analysis). My Master's thesis (University of Montana, 2002) tested the effects of the non-random distribution of trees on predictions of canopy cover in a forest computer model widely used by the U.S. Forest Service.

Previous research with the U.S. Forest Service in the Pacific Northwest, involved a diversity of issues such as: monitoring the effects of alternative timber harvesting methods on understory vegetation; monitoring the effects of air pollution on Lichens and Bryophytes; collecting field data for the prediction optimal habitats for sensitive species; monitoring the effects of prescribed burns and wildfires on vegetation and soils; and field sampling and mapping of potential vegetation communities.

E-mail: treg [at]

Projects:  Tapash: Scaling Forest Structure and Simulated Wildfire in WA
Treg Christopher,
Jan 3, 2013, 10:06 AM