# A climate- and stage-sensitive stand growth and yield model of natural Larix gmelinii forests in northeast China

## TL;DR

This study creates a model to predict forest growth and carbon storage in Chinese larch forests, considering climate and forest development stages.

## Contribution

The novel contribution is a climate- and stage-sensitive model that improves predictions of forest growth and carbon stocks in natural Larix gmelinii forests.

## Key findings

- The stage-sensitive model outperformed baseline models in predicting volume and carbon stocks.
- At Stage 3, predicted volume and carbon stocks dropped by 15% due to climate aridity and ontogenetic transitions.
- The model captures structural and carbon dynamics that conventional models miss.

## Abstract

Understanding the complex interactions between climate change and stand developmental dynamics in forest growth and carbon sequestration is essential for implementing sustainable management under climate change and for supporting China’s dual-carbon goals. Using data from 243 permanent national forest inventory plots (each 0.0667 ha in size), this study developed a climate- and stage-sensitive forest growth and yield model (FGYM) for natural Larix gmelinii forests in Northeast China. The model incorporates the De Martonne aridity index (MAI) to represent climatic water availability and the stand developmental stage index, categorized into Stage 1 (early), Stage 2 (middle), and Stage 3 (late), to capture the intrinsic biological progression of forest structure. It simultaneously simulates (i) stand basis structure attributes, (ii) timber yields across different assortments, and (iii) carbon stocks in different tree components and end-use categories. Comparative analyses demonstrated that the stage-sensitive model outperformed the baseline models, revealing pronounced stage- and climate-dependent divergences in stand volume and carbon stock trajectories. For a representative stand [age = 100 years, site class index (SCI) = 16 m], the stage-sensitive model predicted 2.96% higher volume and 3.11% higher carbon stocks at Stage 2, but 15.02% and 15.70% lower values at Stage 3, indicating strong sensitivity to ontogenetic transitions and increasing climatic aridity. Across all combinations of MAI, SCI, and developmental stage, the FGYM consistently captured structural and carbon dynamics that the conventional model did not reproduce. Our findings highlight that integrating both climatic drivers and developmental heterogeneity substantially enhances model accuracy and ecological realism, providing a robust tool for assessing the future productivity and carbon sequestration potential of L. gmelinii forests under future climate change scenarios.