The insights provided by theories of self-organization have many practical implications, both for ecology and for conservation. The sharp end ofthe conservation debate often hinges on the question ofwhich areas and which sites to conserve. If ecosystems consist of random collections of species, then one site in a landscape is as good as another. All that matters is to preserve representative populations of each species. However, if the ecosystems consist of self-organized communities, in which the species are adapted to depend on one another for survival, then whole communities need to be conserved.
Closely related to the above issue is that the tendency for randomly constructed food webs to be unstable raises questions about the long-term viability of artificially created communities in which translocated species are introduced into new areas. Self-organization is evident even in artificial ecosystems. In biosphere 2, for instance, a closed, experimental environment designed to emulate natural ecosystems, the environment was found to favor species that collect more energy and internal processes led to unexpected problems, such as runaway depletion of oxygen levels.
The need to understand self-organization is important when considering altered ecosystems. For instance, it is usually not possible to carry out experiments to determine the long-term effects of current ecological management practices such as translocation of populations, controlled burning or allocation of reserves and wilderness areas. This problem makes simulation modeling a potentially crucial tool of ecological theory and practice. New methods of field observation are also appearing. For instance, the need to understand landscape fragmentation has led to studies of connectivity in landscapes, both field based, and using data from remote-sensing and geographic information.
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