Global Map of Leaf Maximum Carboxylation Rate Derived from 6,386 Field Measurements

6,386 in situ measurements of the maximum carboxylation rate of Rubisco (Vcmax) were compiled with leaf nitrogen, phosphorus, and mass per area data. Jingchun Fang used machine learning to generate a global Vcmax map and identify its primary drivers, published on figshare in May 2026. The predicted map shows strong agreement with three existing products (R² ≥ 0.74) and performed best against independent field data.

Use Cases

• Improve Vcmax parameterization in terrestrial biosphere models based on the described leaf nutrient and soil pH predictors.
• Analyze global patterns of photosynthetic capacity based on the machine-learning-generated global Vcmax map.
• Study the joint regulation of leaf carboxylation rate by climate, soil, and leaf nutrients as described in the dataset.
• Validate other global Vcmax products using the independent field data referenced in the description.

Strengths

• Based on 6,386 in situ field measurements, providing a substantial empirical foundation.
• The generated map shows strong agreement (R² ≥ 0.74) with three existing global products.
• Uses machine learning to integrate leaf nutrient, soil property, and climate data as joint regulators.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is 466.2 KB, indicating a limited scope, likely a single raster file.
• Row count is unknown, which may limit suitability assessment for large-scale statistical analysis.

Provenance

Source

Jingchun Fang via figshare.

Collection Method

Compiled from 6,386 in situ measurements and processed with machine learning.

Freshness

Last updated 2026-05-11 15:04:17; freshness should be verified.

Geography

Global