Interpretation of Ecosystem Level Impacts

The measurement of the current status of an ecosystem and the assumption that recovery is the likely outcome once the stressor is removed may not hold up to careful scrutiny given new developments in the study of population dynamics and ecosystems. First, it is crucial to know the dynamical aspects of the systems we are studying, and second, as with the weather, it may prove inherently impossible to predict the futures of ecosystems. 

the apparent recovery or movement of dosed systems towards the reference case may be an artifact of our measurement systems that allow the n-dimensional data to be represented in a two-dimensional system. In an n-dimensional sense, the systems may be moving in opposite directions and simply bypass similar coordinates during certain time intervals. Positions can be similar but the n-dimensional vectors describing the movements of the systems can be very different. One-time sampling indexes are likely to miss these movements or incorrectly plot the system in an arbitrary coordinate system. 

The apparent recoveries and divergences may also be artifacts of our attempt to choose the best means of collapsing and representing n-dimensional data into a two- or three-dimensional representation. In order to represent such data, it is necessary to project n-dimensional data into three or 

These principles also apply to spatial distributions of populations as reported by Hassell et al. (1991). In a study using host-parasite interactions as the model, a variety of spatial patterns were developed using the Nicholson-Bailey model. Host-parasite interactions demonstrated patterns ranging from static crystal lattice patterns, spiral waves, chaotic variation, or extinction with the appropriate variation of only three parameters within the same set of equations. The deterministically determined patterns could be extremely complex and not distinguishable from stochastic environmental changes. 

Given the perhaps chaotic nature of populations, it may not be possible to predict species presence, population interactions, or structural and functional 

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