D.T. Price, R. Hall, F. Raulier, M. Lindner, B. Case, P. Bernier
Given that some impacts of climate warming are being observed across Canada (the current drought in Alberta and Saskatchewan being only one example), and that climate model projections indicate larger, systematic changes occurring within the next 50-100 years, sustainable management of Canada’s forest resources will need to take the effects of such changes into account. The most immediately observable impacts are likely to be changes in species productivity, competition and survival. Estimating these impacts will be critical for the development of adaptation and mitigation strategies.
This project attempts to assess these potential impacts on western boreal forest ecosystems using a suite of process models applied to detailed spatial data sets. In principle, the models must first be calibrated and tested by running them with data representative of current climate conditions for the study area. Only when this has been achieved with acceptable results should the effects of possible future climates be investigated using scenario data (ideally derived from global climate model simulations).
Current models of stand productivity generally employ traditional growth and yield (G&Y) modeling based on plot-level measurements of tree growth. Because local climate is a major determinant of environmental conditions at all forest sites, yield forecasts based on such models are likely to be inaccurate if appreciable changes in climate do occur. In the worst cases, the predictions of future yield could be completely incorrect. An alternative approach is to develop process-based growth models that use physiological and physical principles to relate stand growth to climate. The Canadian Forest Service’s Laurentian Forestry Centre (LFC) is at the forefront in developing and testing this approach. LFC is leading a project termed ECOLEAP (Extended COllaboration for Linking Ecophysiology And Forest Productivity) (http://www.cfl.forestry.ca/ECOLEAP), in which forest net primary productivity (NPP) issimulated mechanistically, and then mapped at the landscape scale using spatial data.
The project reported here, and referred to as ECOLEAP-West, builds on this initiative for two ecologically-distinct study regions within Alberta and Saskatchewan, respectively. Process-based models to estimate NPP were driven by spatial data sets including digital elevation, soils, satellite remote sensing, and interpolated climate. These NPP estimates were then compared to site-level productivity estimates derived from field measurements at permanent sample plots inthe Foothills Model Forest (FMF) study area in Alberta. The aim was to establish an acceptable level of agreement between the different estimates of NPP, and then apply the process-based models to the Saskatchewan study region. The end products should include tools to assess forest productivity under both present-day and plausible future climates, and to investigate the effects of forest management options to adapt to climate change. Preliminary results indicate that forest management can have significant effects on productivity, species composition and carbon sequestration.