Modelling the effects of climate on site productivity of white pine plantations

Abstract

Ninety-three dominant or co-dominant white pine (Pinus strobus L.) trees were sampled from 93 plots (one tree per plot) in even-aged monospecific plantations at 31 sites (three plots per site) across Ontario, Canada. Stem analysis data collected from these trees were used to develop and evaluate stand height models. The effects of site and climate on site productivity were examined by incorporating site and climate variables into a stand height model. Including climate variables improved the fit statistics of the stand height model for white pine. A covariance structure (AR(1)) was used to address autocorrelation in the data. Similarly, a variance function was used to account for heteroscedasticity. Stand heights were predicted for four areas (middle, easternmost, westernmost, and southernmost parts of Ontario where white pine were sampled) for the period 2021 to 2080 under two emissions trajectories known as representative concentration pathways (RCPs), with each reflecting different levels of heat at the end of the century (i.e., 2.6 and 8.5 W·m–2). At the end of the 2021 to 2080 growth period, projected heights were shorter by 7% for the southern parts and taller by 9.8% for the middle parts of Ontario under both climate change scenarios compared with those under a no change scenario. However, there was no pronounced difference in projected heights under both climate change scenarios and the no change scenario for the other two areas evaluated. The resulting height growth models can be used to estimate stand heights for white pine plantations in a changing climate. Using the same model, the site index of a plot or stand can be estimated by calculating height at a given base (index) age. In the absence of climatic data, the model fitted without climate variables can be used to estimate stand heights and site indices.