Forest Intelligence

Gold

1km

One-off

Plot

2026

This indicator characterizes the functional properties of a forest based on plant traits linked to resource acquisition, growth, and nutrient use. Understanding these functional characteristics provides insight into how vegetation is structured and how forests may respond to environmental conditions. For businesses, this information helps translate complex ecological data into an accessible understanding of forest characteristics, supporting more informed assessment and communication of forest ecosystems.

Forest Intelligence is based on the global plant functional trait dataset developed by Moreno-Martínez et al. (2026), which integrates TRY plant trait observations, GBIF species-occurrence records, and remote-sensing-derived fractional plant functional type (PFT) information. The dataset provides community-level estimates of Specific Leaf Area (SLA), Leaf Nitrogen Concentration (LNC), and Leaf Phosphorus Concentration (LPC), together with statistical descriptors of their distributions, including mean and variability. For each forest polygon, Forest Intelligence extracts the corresponding trait statistics and contextualizes them against ecologically comparable reference environments, including WWF ecoregions, biomes, and Köppen climate zones. A deterministic rule-based framework then translates the quantitative trait information and its relative position within these reference distributions into four interpretable dimensions: Growth Strategy, Functional Diversity, Growth Potential, and Nutrient Conditions. Predefined interpretation rules and text templates convert these classifications into concise, standardized ecological insights. This approach maintains traceability from the final narrative back to the underlying trait measurements while accounting for ecological differences between forest systems.