Biol. Bull. 202: 245-246. (June 2002)
© 2002 Marine Biological Laboratory
Introduction
Diana E. J. Blazis
The Center for Advanced Studies in the Space Life Sciences, Marine Biological Laboratory, Woods Hole, Massachusetts 02543
This workshop, entitled "The Limitations of Self-Organization in Biological Systems," was sponsored by the Center for Advanced Studies in the Space Life Sciences, at the Marine Biological Laboratory. The focus of the workshop was on self-organization, which is defined as "a process [through] which pattern at the global level of a system emerges solely from numerous, [local] interactions among lower level components of the system" (Camazine et al., 2001). This broad definition, which has its roots in physics, drove the workshop’s examination of the concept, its utility, its limitations as a principle for understanding patterns that appear in biological systems during such activities as schooling in fish, foraging in bees, and nest-building in termites.
Scott Camazine (Pennsylvania State University), chair of the workshop, collaborated with other workshop participants in posing a series of questions intended to frame the discussion. I describe some of the questions below and point to the papers in this volume that address them.
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What is self-organization? When is self-organization used?
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During the workshop, substantial discussion focused on the definition of self-organization and when it operates. Anderson (this volume) presents a theoretical exploration of self-organization and related concepts. Key characteristics of self-organization include positive and negative feedback loops, multiple interactions, stochasticity and randomness. These processes lead to so-called "emergent behaviors," multistability, and robustness. Many in the group, such as Cole (this volume) observed that self-organization occurs widely among biological systems, and at many levels.
Systems that generate these characteristics of self-organization include Turing patterns, postulated in 1952 by Alan Turing in the context of physical and chemical systems. Stationary patterns arise via reaction-diffusion mechanisms, e.g., when mixtures of chemicals react with one another while drifting at different rates through a medium. Reaction-diffusion systems were considered throughout the workshop as mechanisms that can account for pattern formation in inorganic systems (such as the Belousov-Zhabotinsky reaction) and organic systems (zebra stripes, termite nests, and more). As Theraulaz et al. discussed at the workshop and demonstrated recently (Theraulaz et al., 2002), a theoretical model constructed using assumptions based on reaction-diffusion mechanisms can account for a well-defined behavior in social insects: the formation of cemeteries by ants.
Seeley (this volume) suggests that particular circumstances favor the self-organized system. Specifically, a biological system composed of a large number of subunits that lack the mechanisms of communication and computation required for centralized control is likely to be self-organized, regardless of the complexity of the individual subunits.
One theme of workshop discussion concerned the interaction between self-organization and individual behaviors. Deneubourg et al. (1999) have argued that self-organization and individual complexity need not be mutually exclusive. Levels of organization can interact. Roces (this volume) discusses collective foraging in leaf-cutting ants. These ants cut vegetation into small fragments that constitute the precursor for the colony’s food; the fragments are processed by symbiotic fungi in the nest’s fungus garden. When desirable food sources are discovered by individual ants, they are harvested and cut into especially small pieces, which causes intense recruitment of additional ants to harvesting activity. Thus a greater number of ants carry smaller loads, which are returned more rapidly to the nest, stimulating even further recruitment and, eventually, maximal harvesting.
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What are the perturbations (e.g., environmental or internal stressors, growth or damage during development) that potentially affect self-organization? How do biological systems take advantage of and compensate for these perturbations?
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Social organisms took front stage as the group grappled with this set of questions. Ants again are heuristic model organisms. For example, Detrain et al. (this volume) use ant societies to examine the effects of environmental factors on collective patterns; they suggest that changes in the environment can generate diverse foraging patterns. Jeanne and Bouwma (this volume) show that an internal stressor—the size of the group—affects nest-building in social wasps. They demonstrate that the morphology of the nest varies quantitatively and qualitatively with nest size and propose that this relationship arises as a consequence of self-organizing processes. Deneubourg et al. (this volume) show that multiple patterns of aggregation in social insects can emerge from changes in a single parameter: in their example, resting time. Self-organization also appears to be important in determining herd size in large mammalian herbivores, such as roe deer or kangaroo; the process of herd formation is described both theoretically and with field observations by Gerard et al. (this volume).
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Does self-organization interact with evolution to produce behavioral complexity?
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The consensus of the group was that natural selection and self-organization are complementary mechanisms. Cole (this volume) argues that biological self-organized systems are expressions of the hierarchical character of biological systems and are, therefore, both the products of, and subject to, natural selection. However, some self-organized patterns, for example, the wave fronts of migrating herds, are not affected by natural selection because, he suggests, there is no obvious genetic connection between the global behavior (the wave front) and the actions of individual animals. Hemelrijk (this volume) also explores the interaction of natural selection with self-organized systems. Using simulations that combine representations of individual selection, self-organization, and group selection, Hemelrijk documents the evolution of despotic societies from egalitarian ones. She supports these theoretical results with examples from insect and non-human primate societies.
Teasing apart the roles of evolution, self-organization, and individual behavior in biological pattern formation is a task that requires a common framework, as demonstrated by Parrish and colleagues (this volume). An important question emerging is whether spatial patterns are biologically significant or are epiphenoma (a theme also echoed by Cole [this volume]).
Throughout the workshop, participants warned against naïve attempts to emulate the activity of natural systems in the generation of spatial and temporal patterns. Self-organized systems can be remarkably inefficient; those emulating such systems may need to turn to central controllers to improve performance. Moreover, as participant Carl Anderson noted, self-organized systems can respond nonadaptively to environmental conditions, as for example, when ants develop group circling behaviors instead of effective foraging patterns. Throughout, participants such as Walter Tschinkel and Tom Seeley cautioned against overreliance on the notion that subunits or individual social insects are necessarily "simple." Tschinkel noted that it is important to "identify the behaviors, interactions, signals and cues" that the subunits actually use. Moreover, different mechanisms can give rise to the same phenotype or pattern. Thus the predictive power of a mechanism or mechanisms must be used to develop testable hypotheses about the function of complex systems.
The Center for Advanced Studies in the Space Life Sciences (CASSLS) was established in 1995 through a cooperative agreement between the Marine Biological Laboratory and the Life Sciences Division of the National Aeronautics and Space Administration. The Center acts as an interface between NASA and the basic science community, promoting interactions and discussion in areas that are of mutual interest.
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Literature Cited
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Anderson, C.2002. Self-organization in relation to several similar concepts: are the boundaries to self-organization indistinct?
Biol. Bull.202
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–255.[Abstract/Free Full Text]
Camazine, S., J. L. Deneubourg, N. R. Franks, J. Sneyd, E. Bonabeau, and G. Theraulaz. 2001.
Self-organization in Biological Systems. Princeton University Press, Princeton.
Cole, B. J.2002. Evolution of self-organized systems.
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–261.[Abstract/Free Full Text]
Deneubourg, J., S. Camazine, and C. Detrain.1999. Self-organization or individual complexity: a false dilemma or a true complementarity. Pp.401
–407 in
Information Processing in Social Insects, C. Detrain et al., eds. Birkhä user Verlag, Basel.
Deneubourg, J. L., A. Lioni, and C. Detrain.2002. Dynamics of aggregation and emergence of cooperation.
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–267.[Abstract/Free Full Text]
Detrain, C., and J.-L. Deneubourg.2002. Complexity of environment and parsimony of decision rules in insect societies.
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–274.[Abstract/Free Full Text]
Gerard, J.-F., E. Bideau, M.-L. Maublanc, P. Loisel, and C. Marchal.2002. Herd size in large herbivores: encoded in the individual or emergent?
Biol. Bull.
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–282.[Abstract/Free Full Text]
Hemelrijk, C. K.2002. Self-organization and natural selection in the evolution of complex despotic societies.
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–288.[Abstract/Free Full Text]
Jeanne, R. L., and A. M. Bouwma.2002. Scaling in nests of a social wasp: a property of the social group.
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–295.[Abstract/Free Full Text]
Parrish, J. K., S. V. Viscido, and D. Grünbaum.2002. Self-organized fish schools: an examination of emergent properties.
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–305.[Abstract/Free Full Text]
Roces, F.2002. Individual complexity and self-organization in foraging by leaf-cutting ants.
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–313.[Abstract/Free Full Text]
Seeley, T. D.2002. When is self-organization used in biological systems?
Biol. Bull.
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–318.[Abstract/Free Full Text]
Theraulaz G., E. Bonabeau, S. C. Nicolis, R. V. Solé, V. Fourcassié, S. Blanco, R. Fournier, J. L. Joly, P. Fernández, A. Grimal, P. Dalle, and J. L. Deneubourg.2002. Turing-like patterns in ant colonies.
Proc. Natl. Acad. Sci. (In press).
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