Elizabeth A. Hobson

Behavioral flexibility and species invasions: the adaptive flexibility hypothesis

Behavioral flexibility is an important adaptive response to changing environments for many animal species. Such plasticity may also promote the invasion of novel habitats by introduced species by providing them with the ability to expand or change their ecological niche, a longstanding idea with recent empirical support. At the individual level, flexibility may arise through innovation, in which an individual invents a new behavior, or through social learning, in which an individual adopts a behavior used by others. There is increasing evidence that the adaptive value of these two modes of learning, and the overall expression of behavioral flexibility, may vary with social and environmental context. In this paper, we propose that invasive species may change the degree to which they express behavioral flexibility in an adaptive manner during the different stages of invasion. Specifically, the “adaptive flexibility hypothesis” predicts that the expression of behavioral flexibility, and thus the diversity of behaviors observed in a population, will be high during the initial stage of introduction into a novel environment due to innovation, followed by a decline in behavioral diversity during the establishment and growth of a founding population due to social learning of successful behavioral variants. We discuss several alternatives to this hypothesis and suggest empirical and theoretical tests of these hypotheses. This “adaptive flexibility hypothesis” suggests that a more nuanced approach to the study of the behaviors employed by individuals in populations at different invasion stages could generate new insight into the importance of such flexibility during species invasions, and the evolution of behavioral plasticity in general

An analytical framework for quantifying and testing patterns of temporal dynamics in social networks

Change is fundamental to all social systems. Temporal dynamics are critical in understanding how relationships form and change over time but rarely are studied explicitly in animal groups. Social network approaches are useful in describing association patterns and provide promising tools for investigating the dynamics of change in social structure but have rarely been used to quantify how animal associations change over time. In this study, we describe and test a framework for temporal analysis of social structure. We propose an analytical framework of methods that integrates across social scales and comparatively analyses change in social structure across multiple types of social association. These methods enable comparisons in groups that differ in size and are flexible to allow application to weighted and unweighted networks, where ties can be directed or undirected, and relationships can be symmetric or asymmetric. We apply this analytical framework to temporal social network data from experimentally formed captive groups of monk parakeets, Myiopsitta monachus, to both evaluate our analysis methods and characterize the social structure of this species. We compared dynamics of dyadic network formation, ego network formation and global network stabilization patterns across neutral, affiliative and agonistic associations. We found that social structure of captive monk parakeets formed and stabilized over a short period, but patterns differed by social association type. We also found evidence for consistency in the temporal dynamics of formation and stabilization of social structure between replicate social groups. Our analysis methods successfully identified change in social structure that corresponded well with qualitative observations. This framework is likely to be useful in characterizing patterns of temporal dynamics in social structure in longitudinal data in wide variety of social systems and species. 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Social Feedback and the Emergence of Rank in Animal Society

Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference.

The socioecology of Monk Parakeets: Insights into parrot social complexity

ABSTRACT In many species, individuals benefit from social associations, but they must balance these benefits with the costs of competition for resources. Understanding how these competing factors generate diversity in social systems is a major goal of behavioral ecology, but one that has been hampered by a lack of basic data quantifying many aspects of social structure and associations. Although parrots are generally assumed to have complex social groups, few studies have quantitatively examined these assumptions about parrot social structure. We critically assessed 4 assumptions about parrot socioecology using data from captive and wild groups of Monk Parakeets (Myiopsitta monachus). We evaluated (1) whether pairs are the fundamental unit of parrot social structure, (2) the patterns and extent of fission–fusion dynamics, (3) patterns of aggression and dominance hierarchy structure, and (4) whether individuals share foraging information. We found evidence that supported pairs as the fundamental unit of social structure, although these close associates were not always heterosexual breeding pairs and were sometimes trios. Fission and fusion of subgroups were common, and the amount of fission–fusion dynamics varied across flock types and by fission–fusion dimension, but the amount of variation among dimensions was consistent across replicate captive social groups. Despite these levels of fission–fusion dynamics, study of aggressive interactions in our 2 captive groups indicated that dominance hierarchies existed. Hierarchies were moderately linear (0.7) but not steep (<0.1). Finally, we found no evidence that Monk Parakeets share foraging information among groups through active vocal recruitment to foraging flocks. We compared these patterns with those documented for other species of parrots and other cognitively complex large-brained species. We consider the implications of our results for the study of the evolution of complex sociality and highlight several future directions for parrot socioecology research.

Social tipping points in animal societies

Animal social groups are complex systems that are likely to exhibit tipping points—which are defined as drastic shifts in the dynamics of systems that arise from small changes in environmental conditions—yet this concept has not been carefully applied to these systems. Here, we summarize the concepts behind tipping points and describe instances in which they are likely to occur in animal societies. We also offer ways in which the study of social tipping points can open up new lines of inquiry in behavioural ecology and generate novel questions, methods, and approaches in animal behaviour and other fields, including community and ecosystem ecology. While some behaviours of living systems are hard to predict, we argue that probing tipping points across animal societies and across tiers of biological organization—populations, communities, ecosystems—may help to reveal principles that transcend traditional disciplinary boundaries.

Theory Meets Empiry: A Citation Network Analysis

According to a recent survey, ecologists and evolutionary biologists feel that theoretical and empirical research should coexist in a tight feedback loop but believe that the two domains actually interact very little. We evaluate this perception using a citation network analysis for two data sets, representing the literature on sexual selection and speciation. Overall, 54%-60% of citations come from a papers own category, whereas 17%-23% are citations across categories. These cross-citations tend to focus on highly cited papers, and we observe a positive correlation between the numbers of citations a study receives within and across categories. We find evidence that reviews can function as integrators between the two literatures, argue that theoretical models are analogous to specific empirical study systems, and complement our analyses by studying a cocitation network. We conclude that theoretical and empirical research are more tightly connected than generally thought but that avenues exist to further increase this integration.

Edge weight variance: population genetic metrics for social network analysis

We present novel metrics for analysis of weighted social networks that focus explicitly on the distribution of edge weights at hierarchical scales from node to egonet to community and to the network as a whole. The formulae are adapted from existing measures, originally developed in the context of population genetics to analyse variance in gene frequencies at different levels of organization. Our metrics, including ‘effective degree’ (by analogy to effective number of alleles), ‘concentration’ (by analogy to the inbreeding coefficient), ‘observed’ and ‘expected edge weight diversity’ (by analogy to observed and expected gene diversity) and F statistics allow one to partition the variance in edge weights among hierarchical levels of organization within networks. They provide a quantitative method for addressing issues as diverse as disease transmission, social complexity, the spread of learned behaviours and the evolution of cooperation. We illustrate the utility of these new metrics by applying them to three empirical social networks: long-tailed manakins, Chiroxiphia linearis , monk parakeets, Myiopsitta monachus , and mountain goats, Oreamnos americanus .