Climatic Effects on Site Productivity of Red Pine Plantations

Climatic effects on site productivity of red pine (Pinus resinosa Aiton) plantations were examined. A stand height/site index equation with climate variables incorporated in the height growth model was developed from stem analysis data. These data were collected from 90 dominant or co-dominant red pine trees sampled from even-aged monospecific plantations located on 30 sites (3 trees per site) broadly distributed across Ontario, Canada. The stand height equation was fit using a nonlinear mixed-effects approach. Climatic effects on site productivity were examined by regressing site index against commonly reported climate variables. Three site-specific climate attributes explained 63% of the variability in observed site index. These climate variables were examined to be incorporated into the stand height growth models. However, only two climate variables-growing season total precipitation (GSTP) and growing season mean temperature (GSMT)-were significant in the model without random effects and autocorrelation. In the presence of random effects and autocorrelation, however, only GSMT remained significant in the model. Stand heights were predicted for three randomly selected locations (eastern, western, and southern Ontario) for the growth periods 2011 to 2040 and 2041 to 2070 under two (2.6 and 8.5 Watts/m(2)) emissions trajectories known as Representative Concentration Pathways (RCPs). At the end of both growth periods, projected heights were reduced under both climate change scenarios (compared to those under a no-climate-change scenario) at all locations. Under both scenarios, the decrease in height growth was more pronounced in the south than in the east or west. The developed height growth models can be used to estimate stand heights for red pine plantations in a changing climate. Using the same models, site index of a plot/stand can also be estimated by calculating height at a given base (index) age. In the absence of climate data, the model fitted without climate variables can be applied to estimate stand heights and site indices.