Dendrocalamus Brandisii Bamboo Biomass Models for Carbon Accounting in Hainan, China

Bin Wu developed compatible biomass models for Dendrocalamus brandisii bamboo plantations in Sanya, Hainan, China. The dataset likely contains parameters and performance metrics for models predicting aboveground biomass of culms, branches, and leaves based on destructive sampling of 45 culms. The models were created using Seemingly Unrelated Regression to reduce discrepancies in carbon accounting.

Use Cases

• Predict total aboveground bamboo biomass based on diameter at breast height (DBH) and height.
• Estimate carbon sequestration capacity of Dendrocalamus brandisii plantations.
• Apply Tier-3 carbon monitoring protocols using compatible SUR models.
• Compare biomass partitioning between culm, branch, and leaf components.
• Support climate-adaptive management of bamboo plantations under similar edaphoclimatic conditions.

Strengths

• Models achieve high accuracy with R² > 0.9 for total aboveground biomass and culms.
• Compatible SUR models reduce discrepancy between summed components and total biomass to virtually zero.
• Based on destructive sampling of 45 culms from a managed plantation.
• Model performance was evaluated using 1,000 bootstrap iterations with out-of-bag predictions.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is limited to 2- and 3-year-old culms from a single plantation in Sanya.

Provenance

Source

figshare

Collection Method

Destructive sampling of 45 culms from a managed plantation, with modeling using weighted non-linear least squares and Seemingly Unrelated Regression.

Freshness

Last updated 2026-05-22 05:34:57; freshness should be verified.

Geography

Sanya, Hainan, China