Precision agriculture reveals crop-yield footprints associated with distance to natural-seminatural habitats

Context Modern agricultural expansion has simplified landscapes and reduced natural and semi-natural habitats (NSNH), potentially disrupting ecological processes supporting crop production. Many of these processes are distance-dependent, potentially leaving spatial footprints in crop yield that vary with landscape context. Yet, their influence on crop yields at sub-field scales remains poorly understood. Precision agriculture offers opportunities to address this gap. Objective To evaluate how sunflower distance-to-NSNH - yield relationships vary across landscape contexts within contrasting landscape settings using precision agriculture data. Methods High-resolution yield-monitor data (∼700,000 observations) from 54 yield maps (Pampas, Argentina) were combined with landscape metrics derived from land-cover products, and distance-yield relationships were analysed using mixed-effects models. These relationships were evaluated across gradients of NSNH cover (landscape context) and between zones representing contrasting landscape settings. Results and conclusions Distance-yield relationships were non-linear, varied with landscape context, and differed between landscape settings. In simplified landscapes, yields declined beyond a few hundred meters from NSNH, with steeper declines under higher NSNH cover. In the more complex landscape setting, where NSNH were more abundant and distances to habitat were shorter, yield responses were weak across the observed NSNH gradient. These patterns may reflect distance-mediated ecological processes associated with NSNH, although their observational nature precludes attribution to specific mechanisms. Expanding the dataset across broader landscape gradients would strengthen the mechanistic interpretation of these patterns. Significance Precision agriculture can help identify crop-yield footprints consistent with distance-mediated ecological processes at sub-field scales, improving understanding of landscape-crop interactions and supporting ecologically informed landscape management.