Mapping herbivore-accessible biomass across a heterogeneous mountain landscape using multisensor high-resolution UAV data

Abstract

Herbivore-accessible biomass (HAB), defined as aboveground biomass under 2 m, including leaves and soft branches, is a key metric for understanding ecosystem function, but remains poorly quantified. We estimated HAB across diverse habitats in the Peneda-Gerês National Park using high-resolution NDVI, LiDAR, topography and field data. Generalized Additive Mixed Models (GAMMs) revealed habitat-specific effects of NDVI and vegetation height, as well as terrain, and structural metrics across plant types. Models were evaluated using hold-out cross-validation on a 20 % subset of the field data. The total HAB model performed well (Deviance Explained = 0.77, RMSE20 = 172.38 g/m2), while the shrub model performed slightly worse (Deviance Explained = 0.71, RMSE20 = 410.21 g/m2), and the herbaceous model exhibited a moderate fit and accuracy (Deviance Explained = 0.69, RMSE20 = 34.25 g/m2). Average total HAB was 1.31 ± 0.83 tons/ha, dominated by shrubs (1.02 tons/ha) compared to herbaceous HAB (0.14 tons/ha). HAB density varied by habitat, highest in shrublands (up to 1.83 ton/ha) and lowest in oak forests (0.85 tons/ha), while agricultural areas supported the most herbaceous HAB (0.68 tons/ha). These values are substantially lower than shrub biomass estimates reported in other studies (e.g., up to 30 tons/ha), reflecting our focus on live biomass <2 m. Prediction uncertainty was low (CV: 22–34 %), improving on other studies reporting up to 190 %, and highlighting the strength of combining spectral and structural data for fine-scale forage estimation. This study provides the first spatially explicit HAB estimates for the area, supporting herbivore ecology and management.