Tree improvement is considered an effective method to address the shrinking forest land-base in Alberta, Canada. It is also of great necessity to quantify the potential harvest from deployment of improved trees. However, the growth and yield models currently used in Alberta were originally developed based on growth measurements and projections from fire origin stands, and therefore, there is no widely accepted method to recognize the impact of managed stands, and even less information available to properly incorporate genetic gain in volume from tree improvement into managed stand models. Furthermore, there are considerable challenges associated with acceptance of an appropriate age-age correlation when selecting trees at a young age and projecting their anticipated increase in volume at rotations as long as 80–110 years.

White spruce (Picea glauca (Moench) Voss) and lodgepole pine (Pinus contorta Dougl.) are the most important commercial tree species in Alberta, and the focus of this study. Based on the most recent and comprehensive datasets from progeny trials from both species, two available age-age correlation equations, one developed by Lambeth (1980) and another by Rweyongeza (2016), were compared and adjusted. This study also explored a new method for age-age correlation prediction based on a sigmoid parabolic branch (SPB) equation.

The results show that the adjusted Lambeth equations, with re-estimated parameters for white spruce and lodgepole pine in Alberta, are the most robust for both species and should be further incorporated into the growth and yield models, based on cross-validation results at a relatively young age (7–31 years for white spruce and 6–30 years for lodgepole pine). The phenotypic age-age correlation shows no significant deviation from the genetic age-age correlation for white spruce and lodgepole pine in Alberta. The stand volume generated from the growth and yield projection system (GYPSY) using an age-age correlation from the adjusted Lambeth equations shows that white spruce has a higher age-age correlation and therefore, a higher percentage improvement in volume per hectare compared to lodgepole pine regardless of rotation age.

树木改良被认为是解决加拿大艾伯塔省森林面积不断缩小的有效方法。量化部署改良树木的潜在收获也非常必要。但是，阿尔伯塔省目前使用的生长和产量模型最初是根据生长测量和火源林的预测而开发的，因此，目前尚无公认的方法来识别受管理林的影响，甚至没有足够的信息来适当纳入从树木改良到管理林分模型的数量遗传增益。此外，在选择幼龄树木并预测其轮伐期预计长达80-110年时，接受适当的年龄-年龄相关性还面临着巨大的挑战。

白云杉（云杉云杉）和黑松（Pinus contorta Dougl。）是艾伯塔省最重要的商业树种，也是本研究的重点。基于两个物种的子代试验的最新和最全面的数据集，比较并调整了两个可用的年龄-年龄相关方程，一个由Lambeth（1980）建立，另一个由Rweyongeza（2016）建立。这项研究还探索了一种基于S型抛物线分支（SPB）方程的年龄相关性预测的新方法。

结果表明，经过调整的Lambeth方程，以及重新估计的艾伯塔省白云杉和黑松的参数，对于这两个物种都是最稳健的，并且应根据交叉验证的结果进一步纳入生长和产量模型。相对年轻的年龄（白云杉为7-31岁，黑松为6-30岁）。表型的年龄-年龄相关性显示与艾伯塔省的白云杉和黑松的遗传年龄-年龄相关性没有显着差异。使用调整后的Lambeth方程中的年龄-年龄相关性从生长和产量预测系统（GYPSY）生成的林分体积显示，白云杉具有更高的年龄-年龄相关性，因此，与小枝相比，每公顷体积的提高百分比更高松木不分年龄。