ABSTRACT
Over the past 40 years, a new multidisciplinary field of study has emerged which is characterized by at least two major changes in the way some scientists treat systems. First, it is increasingly accepted that we cannot fully understand the laws that govern a system simply by studying its parts, nor can we fully understand the behaviour of the parts without placing them in the context of the larger system in which they are embedded. This realization, which has arisen as we face the limits of reductionist science, has given rise to the development of new models and methods that facilitate the study of systems across multiple scales of organization. Second, the notions of equilibrium and predictability in natural systems, developed in the nineteenth century and continuously pursued until far into the twentieth century, are being rejected in favour of models that embrace variability, diversity, continual change, adaptation and some level of unpredictability as the status quo. Traditional analytical models that assume a stable equilibrium are being replaced by new approaches that facilitate the exploration of a system’s natural range of variation and its possible emergent responses to changing external conditions. The implications of this new field, now known as complexity science, are manifest across disciplines, fundamentally changing the way we study, analyse and perceive natural systems (Waldrop, 1992; Lewin, 1999; Cho, 2009; Mitchell, 2009).
