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Social learning is a primary mechanism for information acquisition in social species. Despite many benefits, social learning may be disadvantageous when independent learning is more efficient. For example, searching independently may be more advantageous when food sources are ephemeral and unpredictable. Individual differences in cognitive abilities can also be expected to influence social information use. Specifically, better spatial memory can make a given environment more predictable for an individual by allowing it to better track food sources. We investigated how resident food-caching chickadees discovered multiple novel food sources in both harsher, less predictable high elevation and milder, more predictable low elevation winter environments. Chickadees at high elevation were faster at discovering multiple novel food sources and discovered more food sources than birds at low elevation. While birds at both elevations used social information, the contribution of social learning to food discovery was significantly lower at high elevation. At both elevations, chickadees with better spatial cognitive flexibility were slower at discovering food sources, likely because birds with lower spatial cognitive flexibility are worse at tracking natural resources and therefore spend more time exploring. Overall, our study supported the prediction that harsh environments should favour less reliance on social learning. 

ABSTRACT Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the ‘spatial–social interface’ as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial–social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density‐dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial–social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial–social interface.