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1 August 2011 Collective Animal Behavior
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We are social organisms, and we are always fascinated by other social creatures. Yet understanding how and why collective and social behaviors emerge proves to be a remarkable challenge. From H. G. Wells's concept of a “world brain” to William Morton Wheeler's “superorganism,” many theories have surfaced and tried to answer these questions. Successful investigation of collective systems can be achieved through two major steps: (1) linking different levels of organization and (2) applying a set of techniques suitable for the analysis of systems at many different physical scales. If we want to understand how an ant colony is able to find and exploit transient food resources, we need to understand ants' individual behavior, feedback mechanisms, individual- and colony-level decisions, cues, and signals and then to connect the different levels of organization together. Collective Animal Behavior is an excellent guide in showing us how this is possible.

What makes David Sumpter's book unique and worthwhile reading? Namely, the target audience is the scientist interested in social and collective phenomena. The book assumes that the reader has a sound, fundamental knowledge of science. Therefore, the subject matter reaches the current state of progress in the field immediately. Yet although Collective Animal Behavior is scholarly and insightful, it is also a very accessible and easy read. This accessibility largely stems from the honest, personal approach with which the author starts his book: “…anyone who works with me can confirm that I can be slightly single minded about how I do things” (p. ix). Sumpter has studied many interesting facets of collective behavior, and he is currently a professor at the Mathematics Institute of Uppsala University in Sweden. He, along with two collaborators, also has a blog on collective behavior to disseminate this field of research to the public.

The focus of the book is on how interactions between organisms produce group-level patterns, such as fish schools or spiders' social webs. Why do these interactions evolve? What mechanisms ensure that these patterns can be formed and maintained? Sumpter skillfully builds bridges between mechanistic and functional approaches. In his own words, “Mechanisms should not simply be considered as a way of obtaining parameters for the cost-benefit curves of functional models. Rather, we should aim to form functional explanations that fully account for the underlying mechanisms” (p. 11). Filled with examples of how considering both mechanism and functional explanations can lead to a much deeper understanding of biological phenomena, the book takes a refreshing view that piqued my interest and made reading an intellectual delight.

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The tool that Sumpter uses to present, analyze, and make us understand collective behavior is mathematical modeling. Models are excellent tools for deciphering fundamental dependencies between individual interactions and group-level patterns. Beyond demystifying biological phenomena, mathematical modeling also helps us search common cores of different biological systems, such as human applause and the synchronized flashing of fireflies. Models give us predictions that can be compared to field data or that can allow us to generate “what-if” scenarios that promote further research. The models presented in Collective Animal Behavior are simple and easy to understand—not solemn appendices or boxed texts that are tempting to pass over, but integrated parts of the biological story.

The content is well organized and covers nearly every aspect of collective behavior, starting with the questions of why and how animals form groups. A key advantage of living in a group is the ease of information transfer. How will this information transfer affect individual decisions? How will these individual decisions lead to adaptive colony-level patterns? How will these simple rules of thumb and individual decisions result in the spectacular movements of swarms and fish schools or make synchronization of behavior possible? We learn how ants and termites can build complex and intricate structures or form trail networks that are much larger than the individuals themselves. Later chapters present interesting generalizations on how social systems can self-regulate to avoid pitfalls such as congestion, and how complexity at the individual level affects the collective complexity. The book concludes by integrating two main themes: how different mechanisms of collective behavior evolved through natural selection and how, through mechanistic understanding, we gain insight into the function of biological systems.

Collective Animal Behavior provides an excellent synthesis of mathematical modeling and biology with experimental and theoretical studies. A few introductory chapters to the book could have captured more readers from the student population, but this volume does come with a homepage ( www.collective-behavior.com/Site/Home.html), and the author has generously made many of the models he constructed available to those who want to run their own simulations. If the author keeps this portal up to date and his blog active, I am confident that readers interested in collective behavior, modeling, artificial intelligence, behavioral ecology, and evolution will enjoy not just the book but the complete interactive package.

and Istvan Karsai "Collective Animal Behavior," BioScience 61(8), (1 August 2011). https://doi.org/10.1525/bio.2011.61.8.12
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