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Research

Current Projects

Growth and Yield Modeling

Planning Tools for Sustainable Forest Management

Refinement of the Forest Vegetation Simulator, Northeastern Variant, Growth and Yield Model

Forest managers rely on growth and yield models to assess whether their short term plans will meet long term sustainability goals. This is important from the standpoint of both the business and environmental viability of forestry in the long term. The models that are currently in use in the Maine were initially built on data from the 1970s and 1980s and often use older statistical techniques. Tests have shown that these models may not produce the best predictions of how the forests of Maine will grow. CFRU cooperators have recognized this deficiency and have set the development of better growth and yield models as one of their top research priorities. This project works towards achieving this goal by developing a large database of growth and yield data from the state of Maine and eastern Canadian Provinces. The data in this database are being analyzed with the latest statistical techniques to rebuild growth and yield model components with the ultimate goal of producing a refined growth and yield model. Look here for more information.

Modeling Natural Regeneration and Ingrowth in Managed Stands of the Acadian Region

A growth and yield model that is used to assess the long term sustainability of forest practices needs to not only be able to accurately predict how existing trees will grow, but also be able to accurately predict what type of, and how many, new trees will enter the forest given different growing conditions and disturbances. Despite the obvious importance of this modeling component, it is usually an area of weakness for growth and yield models, and the models currently in use in the northeast are no exception. This project attempts to contribute to the growth and yield modeling effort supported by the members of the CFRU by developing statistical models that explain what types of trees will enter a stand given various conditions as well as how many of these trees will appear. For more information on this project, see the proposal here.

Preparing for Spruce Budworm in Maine: Decision Support and Strategies to Reduce Impacts

The spruce budworm (SBW), a native pest that has periodic outbreaks every 30 to 50 years, is a dominant factor in the decisions that are made regarding managing forests in Maine. Managing for SBW in between outbreaks is critical to reduce the impacts of the next outbreak, and it is equally important to have a strong understanding of the land that is being managed so that managers can quickly adapt their management plans during an outbreak to minimize losses due to insect damage. Good progress towards achieving both of these goals is made by having a strong decision support system (DSS) that helps managers understand where on their land they will have the biggest problem with SBW so that they can attempt to mitigate the effects of SBW before the outbreak and more quickly react when the outbreak starts. This project adapts an existing SBW DSS from New Brunswick, Canada, and applies it to the lands of CFRU cooperators helping them be better prepared for the next SBW outbreak. For more information, see the proposal here.