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Weighted distributions for forest management and research. Weighted distributions provide a theory that brings together many of the stand attributes used in forest management. This theory, while powerful, is straightforward to apply in the context of forest management using statistical software, or packages such as Balance. These methods make it simpler to get compatible estimates from probability-based stand models.
Optimal methods for developing uneven-aged stand management guidelines. Based on models of forest growth, these methods can be used to maximize numerous different objective functions for management; examples include financial objectives, and total biomass. When both the underlying growth and financial models are closely applicable to a given location, the resulting management guides will be optimal with respect to the objective chosen, and provide the basis for better management.
New methods for sampling down coarse woody debris in forest ecosystems. We continue to develop new methods for the estimation of down coarse woody material; of special interest are the new methods based on probability proportional to size sampling, such as perpendicular distance sampling and its variants, and point relascope sampling. Both field and simulation testing are components of this effort.
Data assimilation methods in forestry. Data assimilation brings models and sampling together in an optimal (for linear systems) or suboptimal (for nonlinear systems) manner through the use of sequential estimation methods. These probabilistically-based methods are very powerful, and show great potential for use in both forest research and management.
Research Interest
Weighted distributions for forest management and research. Weighted distributions provide a theory that brings together many of the stand attributes used in forest management. This theory, while powerful, is straightforward to apply in the context of forest management using statistical software, or packages such as Balance. These methods make it simpler to get compatible estimates from probability-based stand models.
Optimal methods for developing uneven-aged stand management guidelines. Based on models of forest growth, these methods can be used to maximize numerous different objective functions for management; examples include financial objectives, and total biomass. When both the underlying growth and financial models are closely applicable to a given location, the resulting management guides will be optimal with respect to the objective chosen, and provide the basis for better management.
New methods for sampling down coarse woody debris in forest ecosystems. We continue to develop new methods for the estimation of down coarse woody material; of special interest are the new methods based on probability proportional to size sampling, such as perpendicular distance sampling and its variants, and point relascope sampling. Both field and simulation testing are components of this effort.
Data assimilation methods in forestry. Data assimilation brings models and sampling together in an optimal (for linear systems) or suboptimal (for nonlinear systems) manner through the use of sequential estimation methods. These probabilistically-based methods are very powerful, and show great potential for use in both forest research and management.
Research Interest
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