Abstract
The floodplain forests in West Kazakhstan’s Urals are challenging to study due to complex growth patterns. Existing tables estimate the trunk volume and wood size but lack comprehensive data for effective forest management. A developed research methodology focuses on creating growth and productivity models for forest-forming species across diverse forest types. Multidimensional linear growth models, with dummy variables for species and forest types, offer reliable insights into the average height and diameter changes at different ages. These models facilitate statistical analyses of asynchronous growth with high reliability. Three-level growth models detail regression lines for individual forest-forming species within specific forest types. This article illustrates the construction of a model for black poplar stands in a central floodplain’s medium-level conditions. Furthermore, it highlights the potential for a regional planting classification based on average height gradients at the base age of stands. The presented methodology aims to address the challenges in forest management and forestry in the region.