Ecological complexity is a multidisciplinary field of research that borrows tools and concepts from the core disciplines of complex systems science (physics, mathematics, computer science) as a means of studying the relationships between pattern and process in natural systems. Complexity theory differs from other analytical approaches in that it is based upon a conceptual model in which entities exist in a hierarchy of interrelated organizational levels (Figure 1). Whereas in conventional approaches systems are described at only one level of organization (e.g., community or nation, but not both simultaneously), complexity theory provides a framework in which the relationships between constructs at different hierarchical levels can be accommodated.
Figure 1: The typical conceptual model of a complex system (from Parrott, L. 2002)
The study of ecological complexity treats an ecosystem as a complex system. Complex systems are typically described by the age-old phrase “the whole is more than the sum of the parts”. We have defined a complex system as “a network of many components whose aggregate behavior is both due to, and gives rise to, multiple-scale structural and dynamical patterns which are not inferable from a system description that spans only a narrow window of resolution” (Parrott and Kok, 2000). Essential characteristics of a complex system include: local interactions between individual components, feedbacks between processes occurring at different scales, amplification of minor variations in initial conditions, and the emergence of patterns in the absence of a global controller. Typical examples of complex systems include: ecosystems, economies, transportation networks and neural systems.
Research in complex systems studies has shown that many complex systems, whether they are ecosystems, brains or social systems, share common structural and dynamical properties. Recurrent themes include: power law scaling, self-organized synchrony between components, and the emergence of stable structures that dissipate energy. Much of the research in ecological complexity involves the analysis of ecological data to see to what extent ecosystems share these common properties with other complex systems.
The combination of local interactions and feedback loops between different hierarchical levels in a complex system gives rise to self-organised structural, spatial, and temporal signatures that are neither completely ordered (equivalent to a uniform spatial pattern or temporal equilibrium) nor disordered (random or chaotic). This class of structure and dynamics is extremely difficult to characterise and currently there exist very few tools that are appropriate for the description of complex signatures in ecosystems. Understanding how such signatures (which are often universal amongst all complex systems) arise is even more difficult. The key challenges in the field of ecological complexity include, therefore: 1) the development of appropriate descriptive measures to quantify the structural, spatial, and temporal complexity of ecosystems; and, 2) the identification of the mechanisms that generate this complexity, through modelling and field studies.
Understanding the nature and origins of complexity in ecosystems will ultimately improve our ability to manage and restore natural systems. New methods of ecosystem management and ecological engineering must accept the dynamic nature of ecosystems and incorporate concepts such as self-organisation, emergence and adaptation into intervention practices.
See our page on measuring complexity for more information about how ecological complexity can be quantified.
Journals on ecological complexity
Ecological Complexity (Elsevier)
This journal, published since 2004, is the leading forum for the publication of articles on all aspects of ecological complexity.
Ecological Informatics (Elsevier)
This journal covers state-of-the-art approaches to ecological modelling and data analysis and is a good forum for the publication of quantitative work in ecological complexity.
Journal of Theoretical Biology (Elsevier)
This journal publishes on all aspects of theoretical biology, but often contains articles on non-linear dynamics in ecological systems or on spatiotemporal modelling.
Ecological Modelling (Elsevier)
This journal is the standard forum for the publication of ecological models and their applications. While not specifically oriented towards ecological complexity, many of the articles describe models that apply complex systems approaches (e.g., individual or agent-based modelling).
Recommended reading:
Parrott, L., Meyer, W. 2012. Future Landscapes: Managing within complexity. Frontiers in Ecology and the Environment, 10(7): 382–389 doi:10.1890/110082.
Anand M., Gonzalez A., Guichard F., Kolasa J., Parrott L. Ecological Systems as Complex Systems: Challenges for an Emerging Science. Diversity. 2010; 2(3):395-410.
Parrott, L. 2010. Measuring ecological complexity. Ecological Indicators, 10:1069-1076.
Parrott, L. 2002. Complexity and the limits of ecological engineering. Transactions of the ASAE, 45(5): 1697-1702.
Solé, R. and Goodwin, B. 2000. Signs of Life: How Complexity Pervades Biology. Basic Books: NY.
Levin, S. 1999. Fragile Dominion: Complexity and the Commons. Perseus Books: NY
