Allometric Equations for Estimating Carbon Stored by Individual Trees in a Radiata Pine Stand
Radiata pine (Pinus radiata D. Don) is New Zealand’s dominant plantation species, supporting carbon sequestration under the national Emissions Trading Scheme. However, existing stand-level carbon models cannot estimate individual tree carbon stocks which are often required for modern remote sensing-based forest inventories. This study developed comprehensive allometric equations for predicting tree-level carbon in radiata pine using an extensive dataset of 894 trees spanning ages 1–42 years across eight New Zealand locations. We fitted 12 models predicting stem wood, bark, branch, and foliage biomass from varying combinations of tree height, diameter at breast height, stand age, stand density and wood density. Models incorporating both height and diameter achieved excellent accuracy for stem wood and bark (R2 > 0.99, log-transformed scale), while inclusion of age, stand density and wood density substantially improved crown component predictions (R2 = 0.95 for branches and 0.93 for foliage). Biomass predictions were converted to carbon using component-specific and age-dependent carbon fractions derived from New Zealand radiata pine, avoiding biases from generic conversion factors. The resulting equations provide a tiered system accommodating different data availability levels and are directly compatible with LiDAR-derived tree attributes. These models provide a robust framework for accurate individual-tree carbon estimation, supporting both operational plantation management and robust carbon accounting across New Zealand’s radiata pine estate.
Authors
- Mark O. Kimberley (ORCID: https://orcid.org/0000-0003-2890-0871)
- Michael S. Watt (ORCID: https://orcid.org/0000-0001-6752-9134)
Institutions
- Statistics New Zealand (NZ)
- Scion (NZ)
- Université Bourgogne Franche-Comté (FR)
Publication Details
- Journal
- Forests
- Published
- 2025-12-31
- DOI
- https://doi.org/10.3390/f17010061
- Citations
- 1
- Primary Topic
- Forest ecology and management
- Type
- article
- Field-Weighted Citation Impact
- 2.31
Funders
- Ministry of Business, Innovation and Employment