The impact of anthropogenic climate change on forest health and growth has been identified as a key issue with respect to the sustainability of forest management in British Columbia (MoFR 2006). A recent analysis of the potential effects of climate change on tree distribution suggests that important timber species including white spruce and lodgepole pine may lose suitable habitat and suffer adversely from a combination of warming trends and reduced growing season precipitation. In contrast, species such as Douglas fir and Ponderosa pine may actually expand their range and potentially show improved growth rates in parts of their range (Hamann and Wang 2006). Recent dendroclimatological studies along elevation gradients in the North Cascade Range found that both lodgepole pine and Douglas-fir responded differently to climate factors depending on elevation (Case and Peterson 2007; Case and Peterson 2005). At high elevation, trees responded positively to increased temperatures, while at low elevations trees showed a negative response to growing season max temperature and a positive correlation with growing season precipitation. White spruce has shown variable responses to temperature variables but generally positive responses precipitation particularly in drier parts of its range (Andalo et al. 2005; Wilmking et al. 2004; Johnson and Williamson).
While tree growth has been shown to be correlated to climate variables, the direct or indirect causal factors are often less clear. Climate can influence nutrient dynamics and subsequently productivity through its impact on organic matter decomposition rates. Recent litter decomposition studies have shown that temperature and soil moisture influence mass loss and mineralization rates (Trofymow et al 2002; Prescott et al. 2004)
Modelling tools are required to help forest planners navigate the potential implications of climate change on timber supply through the use of scenario analysis and case studies. Although detailed physiological models have been useful in exploring climate impacts on tree growth and ecosystem processes, they are often data intensive and difficult to apply for management related applications (e.g. Grant et al. 2005; Grant et al. 2006). To be effective for guiding management, such tools must be able to capture the current understanding of the effect of specific climate variables on ecosystem processes governing forest growth, but still be practical for estimating impacts on tangible projections of forest growth and yield and other ecosystem values (Landsberg 2003; MoFR 2006).
Here we propose the further development of the FORECAST model to give it the capability to explicitly represent the potential impacts of climate change on forest growth and development. FORECAST is an ecosystem-based, stand-level, forest management model designed using a hybrid approach drawing upon both mechanistic and empirical modelling techniques (see below). The development of the FORECAST family of models has been supported by various provincial and federal funding sources for more than 20 years. Most recently funding has focused on model testing and validation in a range of forest types (see Blanco et al. 2007; Seely et al., in press; Bi et al. 2007; Welham et al. 2007), the development of spatially explicit versions of the model for applications in complex silviculture systems (see Seely 2005), and the development of a companion forest hydrology model (ForWaDy) to evaluate effects of alternative climate scenarios on tree water stress.
Tree growth in the FORECAST model is presently limited by light and nutrient availability. The proposed linkage with ForWaDy will provide a third feedback on tree growth rates based on a climate-driven quantification of tree water stress. Moreover, the simulation of soil and litter moisture content in ForWaDy will facilitate a climate-based representation of organic matter decomposition and associated nutrient mineralization rates. These develo ...
Seely, Brad A., Welham, Clive; Blanco, Juan A.; Lo, Yueh-Hsin. 2009. GYMP: Representation of climate change impacts on forest growth in FORECAST. Forest Investment Account (FIA) - Forest Science Program. Forest Investment Account Report. FIA2009MR010
Topic: FLNRORD Research Program
Keywords: Forest, Investment, Account, (FIA), British, Columbia
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