Satellite-derived NDVI predicts forage availability in a wild ungulate system: validation using field-collected vegetation biomass on a temperate grassland
Year: 2025
Type: preprint
Abstract: Satellite-derived vegetation indices (VIs) provide a powerful means to quantify habitat variation in long-term ecological studies, but their reliability as proxies for forage availability in wild herbivore populations remains underexplored. We used three decades of Landsat satellite imagery (1991–2023) to generate a 30m resolution dataset of a proxy measure for annual vegetation greenness – the Normalized Difference Vegetation Index (NDVI) – for the Isle of Rum, Scotland, home to a long-term study of wild red deer (Cervus elaphus). We validated the NDVI data against field-collected vegetation biomass data and compared it with a coarser-resolution (500m) MODIS Enhanced Vegetation Index (EVI) metric. Landsat NDVI was positively correlated with both biomass and EVI, supporting its ecological relevance as a measure of forage availability. All three metrics have increased over the last three decades, indicating a long-term greening trend, with the higher resolution Landsat dataset revealing a variation in the rate of change among vegetation types, including grassland habitats preferred by deer. These findings suggest an increase in foraging availability over time and offer a possible mechanism underpinning observed demographic shifts, such as earlier calving. Our approach provides a transferable framework for integrating satellite data with individual-based field studies, demonstrating how remote sensing can enhance ecological inference in long-term wildlife research.
Institution: University of Edinburgh
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Zero hunger
Open Access status: gold
OpenAlex ID: W4413376846