Combining Time-Stamped Insect Sampling With eDNA-Metabarcoding of Guano to Reconstruct Community Interactions.

Abstract

Understanding the temporal dynamics of predator-prey interactions is the basis for predicting behavioral responses to climate or other environmental changes. Bats, as generalist apex predators, can provide a holistic view on ecosystem health, because their diet integrates signals from diverse insect communities and rapidly reflects environmental change. However, most molecular diet studies lack the temporal resolution needed to infer hunting strategies and prey choice mechanisms, because guano-derived species lists cannot be meaningfully interpreted without knowing when and what potential prey were available. Previous research has typically analyzed eDNA metarcoding data or insect activity patterns separately, limiting insights into mechanisms underlying prey selection. This study combines eDNA metabarcoding of bat guano with metabarcoding of time-stamped insect samples collected using automated Malaise traps to investigate the foraging ecology of long-eared bats (<i>Plecotus</i> sp.). Guano-derived prey communities most closely resemble insect bulk samples captured between 22.00 and 6.00, with species-specific differences in peak foraging times and prey composition. We further detected distinct prey-selection patterns between two closely related species, <i>Plecotus auritus</i> and <i>Plecotus austriacus</i>, consistent with their individual hunting strategy. Our findings demonstrate that adding a temporal axis to molecular diet analysis enables direct inference of prey selection and foraging behavior from guano. This integrative approach advances biodiversity monitoring and offers a tool box for conservation planning under changing environmental conditions. Our findings demonstrate that adding a temporal axis to molecular diet analysis enables direct inference of prey selection and foraging behavior from guano. This integrative approach advances biodiversity monitoring and offers a tool box for conservation planning under changing environmental conditions.