Friday, August 7, 2009

PS 80-49: Toward a complete model of radial growth in Pinus edulis: the effects of CO2 and prior years

C. Susannah Tysor, Northern Arizona University, Amy V. Whipple, Northern Arizona University, and George W. Koch, Northern Arizona University.


Pinus edulis (piñon pine) is found across 35% of the Colorado Plateau and is a foundation species in the piñon-juniper woodlands of the Southwest. Piñon pine mortality in the recent drought has been high and climate change models forecast a warmer future for the region, which will increase piñon pine water stress.  In order to predict the fate of piñon pine, we must understand how various climatic factors influence piñon growth. Tree rings provide a climate sensitive record of growth ideal for exploring the relationship between growth and climate.  We used 78 piñon pine trees cored at Red Mountain in northern Arizona in 1998 to predict tree ring width and piñon pine mortality, using variables including available moisture, growing season length, tree age, growth in prior years, and [CO2] in a hierarchical Bayes modeling structure.  As a first step towards the full model, tree ring width in the prior year and [CO2] was considered in a lag 1 year autoregressive model of mean yearly ring width with [CO2] as a linear covariate.

As a linear covariate, [CO2] is related to tree ring width with slope 0.019 (95% Credible Interval (CI) 0.015 to 0.024) and intercept -5.5 (95% CI -6.88 to -4.07).  Tree ring width increases with [CO2] and [CO2] explains the overall increasing trend in average yearly ring width better than available moisture (as Palmer Drought Severity Index values) or growing season length (as the number of days/year with an average of 5°C or higher).  The autocorrelation coefficient is 0.49 (95% CI 0.30 to 0.68), suggesting a strong effect of growth in the prior year on growth in the subsequent year.  The model successfully predicts yearly average ring width, though ring width is overestimated in extremely dry years.  As other factors and more data are incorporated into the model, ring width predictions should improve along with our understanding of piñon growth.  We plan to consider the ramifications of various climate change scenarios for piñon pine with this model and compare the responses of trees that have survived to those that have died in the recent drought. As recent experiments indicate that piñon pine mortality can arise from drought-induced carbon starvation, the contribution of increasing [CO2] to growth could be very important to predicting piñon pine survival.