Assessing prediction errors of generalized tree biomass and volume equations for the boreal forest region of west-central Canada

Aboveground tree biomass and volume are required inputs to models that estimate carbon budgets and ecosystem productivity. Generalized equations are often used to estimate biomass and volume when local equations are unavailable. This study determined whether there was a concomitant increase in prediction error from increasing levels of equation generalization. Local site, generalized regional, and generalized national allometric equations were compared for 10 species distributed across 119 sites in a region defined by west-central Canada. This study employed regression fit statistics and two prediction error metrics, the average prediction error (APE) from the prediction error sum of squares (PRESS) statistic and mean prediction bias. The APE was 9, 12, and 25 kg of biomass per tree for local site, generalized regional, and national equations, respectively. The mean prediction bias for biomass and volume were statistically similar between local level and generalized regional equations across all species. Predictions from generalized national equations were statistically similar for 5 of 10 species when compared with those from local site and generalized regional equations. While local site equations were most accurate for a given site, results indicate that generalized regional equations will produce reasonable estimates of biomass and volume at sites in this region of Canada.