Mapping herbivore-accessible biomass across a heterogeneous mountain landscape using multisensor high-resolution UAV data
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, RMSE 20 = 172.38 g/m 2 ), while the shrub model performed slightly worse (Deviance Explained = 0.71, RMSE 20 = 410.21 g/m 2 ), and the herbaceous model exhibited a moderate fit and accuracy (Deviance Explained = 0.69 , RMSE 20 = 34.25 g/m 2 ). 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. • Estimated herbivore-accessible biomass (HAB) using UAV data across diverse habitats • Integrated multi-source remote sensing for habitat-specific biomass modeling • Applied GAMMs to capture complex, non-linear biomass–environment relations • Provided habitat-specific HAB estimates supporting herbivore foraging studies • Established baseline HAB data for the Peneda-Gerês National Park ecosystems
Authors
- Luise Quoß (ORCID: https://orcid.org/0000-0002-9910-1252)
- Annika M. Zuleger (ORCID: https://orcid.org/0000-0003-4057-7595)
- Henrique M. Pereira (ORCID: https://orcid.org/0000-0003-1043-1675)
- Miguel N. Bugalho (ORCID: https://orcid.org/0000-0002-7081-657X)
- Luís Borda‐de‐Água (ORCID: https://orcid.org/0000-0002-0802-6235)
- Filipe S. Dias (ORCID: https://orcid.org/0000-0002-3082-7135)
- Martina Marei Viti (ORCID: https://orcid.org/0000-0002-9392-9948)
Institutions
- University of Lisbon (PT)
- Universidade do Porto (PT)
- German Centre for Integrative Biodiversity Research (DE)
- Martin Luther University Halle-Wittenberg (DE)
Publication Details
- Journal
- Science of Remote Sensing
- Published
- 2025-10-04
- DOI
- https://doi.org/10.1016/j.srs.2025.100302
- Citations
- 1
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.80