A cosmic view of ‘tundra gardens’: satellite imagery provides a landscape-scale perspective of Arctic fox ecosystem engineering

Abstract

AbstractAnimal ecology has benefitted greatly from advancements in remote sensing technology and data availability in recent decades. Most animal ecology studies using remote sensing data have focused on assessing how environmental characteristics shape animal abundance, distribution, or behavior. But the growing availability of high-resolution remote sensing data offers new opportunities to study how animals, in turn, shape ecosystems. We use high-spatiotemporal resolution Sentinel-2 satellite imagery to evaluate the effects of Arctic fox (Vulpes lagopus) denning activity on vegetation. Arctic fox dens are characterized with unique vegetation relative to the surrounding area, presumably due to decades of nutrient accumulation and bioturbation. We use an imagery-derived metric (NDVI) to compare maximum plant productivity and plant phenology patterns on Arctic fox dens vs. reference sites, i.e., points generated within areas of preferred denning habitat as predicted from a habitat selection analysis. We show that high-resolution satellite imagery can be used effectively to quantify the effects of Arctic fox denning activity on vegetation. Plant productivity and the rate of green up were both greater on fox dens compared to reference sites. Productivity on these preferred-habitat (reference) sites was lower than average productivity on the tundra (i.e., random sites), indicating that foxes primarily establish dens in low-productivity areas. Our findings support previous studies that proposed Arctic foxes function as ecosystem engineers in low Arctic ecosystems by converting sites of low productivity into sites of high productivity through their denning activity. Plant productivity was unrelated to recent den occupancy patterns, indicating fox denning activity has long-term legacy effects on plants that last well beyond the lifetime of foxes. We add to the growing body of literature that recognizes predators can be drivers of landscape heterogeneity and influence ecosystem dynamics through patch-scale pathways, such as by concentrating nutrients into localized areas. Our study demonstrates the efficacy of using remote sensing technologies to advance our understanding of the functional roles that predators specifically, and animals generally, occupy in ecosystems.