Study on branch growth of Larix olgensis based on climatic factors

To investigate the effects of stand conditions and climatie factors on branch growth, as well as the dynamic patterns of branch growth over time.

This study utilized branch attribute data from 584 branch samples of 45 sampled artificial Larix olgensis trees in Mengjiagang forest farm, Heilongjiang Province, with 20 years of climatic data from the same region. By reparameterizing the base model and conducting model validation, an optimal mixed-effects model for annual branch growth increment was constructed.

The results demonstrated that incorporating branch age, branch insertion depth, tree diameter at breast height (DBH), stand basal area per hectare, summer average temperature, and summer precipitation significantly improved the model's predictive capability. The findings revealed a complex mechanism by which stand conditions and climatic factors influence branch growth. Within a certain range, increases in summer average temperature and summer precipitation promoted branch growth, indicating that warm and humid climatic conditions are conducive to branch development. However, increases in stand density-related indicators significantly suppressed annual branch growth increment, reflecting the negative impact of intensified resource competition on individual growth. Branch growth exhibited significant temporal heterogeneity in response to environmental and stand conditions. Under the same climatic conditions, the annual branch growth increment peaked in the second year, then gradually declined, and stabilized after 16 years. This pattern suggests that early-stage branch growth is highly sensitive to hydrothermal conditions, while growth potential gradually diminishes with branch age due to physiological aging mechanisms and the overall resource-carrying capacity of the stand.

The effects of summer average temperature and precipitation on branch growth followed similar trends. The constructed mixed-effects model significantly enhances the predictive capability for branch growth. The results not only deepen the understanding of the dynamic patterns of branch growth but also provide a theoretical foundation for formulating scientific forest management strategies in the context of global climate change.