Geoscience Reference
In-Depth Information
complexity such as emergence, non-linearity, sensitivity and self-organisation
(Schneider et al., 1998). In examining the potential for sudden tipping points or
shifts in the global climate system, for example, researchers increasingly recognise
the potential for sensitivity and non-linearity while also inviting greater involvement
from various publics to answer questions that are beyond science, such as the poli-
tical, cultural and ethical ramifi cations of climate change (Rind, 1999; Schneider,
2004).
Conclusion
Complexity and environmental geography have much to offer each other. Algorith-
mic, deterministic and aggregate complexity offer a range of methods and concepts
to the study of environmental and human-environment systems. Environmental
geography, in turn, offers a host of real-world systems and theories with which to
test and expand complexity science. We can identify several areas of future research
that link these two fi elds. The contest between simplicity and complexity may be
perennial, but studies within environmental geography highlight the need to join
generalised hallmarks of complexity to fi eld-based observations. Experiments in
hydrology, geomorphology and land-cover change, for example, are leading the way
in establishing real-world examples of complexity science that go beyond use of
complexity as a metaphor or analog (Sivakumar, 2000; Crawford, 2005; Phillips,
2006). The same holds true for competing views on equilibrium and change in that
we can tie general complexity concepts to specifi c geographical examples, such as
the tug of war between ecological zones along ecotones (Malanson et al., 2006).
We can also triangulate among a range of quantitative and qualitative methods as
mixed method research becomes more popular (Phillips, 2004; Moss and Edmonds,
2005). The fi eld also offers a long history of research on scale as such and a deep
understanding of, and expertise in, many systems that span spatial and temporal
scales (Sheppard and McMaster, 2004). Thus, this is an exciting time for research
at the interface of complexity science and environmental geography.
BIBLIOGRAPHY
Aerts, J. C. J. H., Eisinger, E., Heuvelink, G. B. M. complexity and Stewart, T. J. (2003)
Using linear integer programming for multi-site land-use allocation.
Geographical Analysis
,
35(2), 148-69.
Allen, C. R. and Holling, C. S. (2002) Cross-scale structure and scale breaks in ecosystems
and other complex systems.
Ecosystems
, 5(4), 315-18.
Arthur, W. B. (1999) Complexity and the economy.
Science
, 284(5411), 107-9.
Bak, P. (1996)
How Nature Works: The Science of Self-Organized Criticality
. New York:
Copernicus Books.
Barabási, A.-L. and Bonabeau, E. (2003) Scale-free networks.
Scientifi c American
, 288(5),
50-59.
Batten, D. F. (2001) Complex landscapes of spatial interaction.
The Annals of Regional
Science
, 35(1), 81-111.
Bolliger, J., Sprott, J. C. and Mladenoff, D. J. (2003) Self-organization and complexity in
historical landscape patterns.
Oikos
, 100, 541-53.
Bousquet, F. and Le Page, C. (2004) Multi-agent simulations and ecosystem management: a
review.
Ecological Modelling
, 176(3-4), 313-32.
