Further mismeasures of animal contests: a new framework for assessment strategies

Competition for resources is a ubiquitous feature of life, and a central topic in behavioral ecology. Organisms use assessment strategies to resolve contests, which can be delineated into two broad categories by the information individuals use to make decisions: mutual assessment (MA) or self-assessment (SA). Most research hitherto has worked to bin a species into one of these categories. In this review, we discuss the limitations of this approach and provide solutions. We posit that assessment strategies do not need to be fixed within a species, individuals, or interactions, and that many organisms should adjust their assessment strategy as the environment, opponent, and opportunities for information gathering change. We show that assessment strategies are an individual-level characteristic, can vary within and between contests, and are not mutually exclusive. We argue that MA is the midpoint along a spectrum of self only and opponent only assessment. We discuss the effects of resource distribution, demographics, experience, information transfer, and ontogeny on assessment strategy evolution and behavior. We conclude by providing empirical guidelines and an example with a simulated dataset. Animals engage in contests for resources like food, space, and mates. We present a theoretical framework for understanding how individual animals in a population resolve these conflicts based on three information sources: themselves, their opponent, and the contested resource. We propose an updated statistical approach for empiricists, the efficacy of which we demonstrate with simulated data.