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

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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
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article

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

Luise Quoß, Annika M. Zuleger, Henrique M. Pereira, Miguel N. Bugalho et al.
1 citations
Science of Remote Sensing
Remote Sensing and LiDAR Applications
0.80
article

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

Luise Quoß, Annika M. Zuleger, Henrique M. Pereira, Miguel N. Bugalho, Luís Borda‐de‐Água, Filipe S. Dias, Martina Marei Viti
article en
1 citations

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, 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

Science of Remote SensingVol. 12
University of Lisbon (PT), Universidade do Porto (PT), German Centre for Integrative Biodiversity Research (DE), Martin Luther University Halle-Wittenberg (DE)
Openalex Percentile: Top 24%
Remote Sensing and LiDAR Applications
0.80
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