The reality of management, as any manager (like every "schoolboy"?) knows, is that real life is complex. There is no attempt to outline all the problems a manager faces, leaving the particular (lack of support within and between organisations, lack of resources, politics, etc etc) to the individual, but a focus on some more general issues about the limits to knowledge and the implications for policy and action. These address issues relate to:
indeterminacy in ecological systems
ignorance of ecological processes
uncertainty as we attempt to utilise non-point source controls.
Lack of determinacy in ecological systems
"Ecosystems are not simple, tightly regulated or balanced." Underwood (1999)
"Some management problems are ecologically complex because many different components interact directly and indirectly, and socially complex because multiple user groups often have conflicting goals that involve multiple components of the system." Johnson, (1999)
Both authors criticise the assumption of equilibrium that lies at the heart of much ecological thinking. Harris(1996) believes there are important implications for managers, noting "...we are dealing with naturally variable systems and that surprises will always occur. Predictions at any level can only be probabilistic. ... we must learn to look beyond the noise and the system dynamics (the trees) for the wood of the rules governing the system function. ... the dynamic approach requires a more sophisticated view of water quality than mere concentrations and ratios."
Risk and uncertainty are integral to environment management and there are at least two dimensions to risk determination (Hoffman and Hammonds, 1994):
determination of the "true" value for a contaminant etc where the end point is fixed (a sampling problem)
assessing the critical points in an unknown distribution of values such as exposure of, and toxicity to, individuals (a modeling problem). Uncertainty is compounded when the same stressor might operate at different concentrations via different mechanisms.
Lack of knowledge about ecological processes
This can occur in two ways:
Clearly the lack of knowledge about variability in particular systems or appropriate scales for experimental design limit the confidence that studies will be robust and statistically sound. The lack of general ecological theories which can provide explicit hypotheses for particular cases is a consequence of the failure of reductionism; ie simple cause effect relationships which can be explicitly described. While it is tempting to address both of these issues by limiting the scale of the experiment Wynne (1992) has argued that it is not possible to eliminate uncertainty and indeterminacy by manipulation of scale. In practice any ecological study is going to result in such limited information that the kind of certitude available in many other experimental systems will not be available.
The lack of certainty as we attempt to utilise non- point source controls.
All forms of pollution control and environment management have moved from "end of pipe" to include source or non-structural controls. While there are clear philosophical reasons for this the costs of these alternatives are not necessarily reduced (and seldom quantified) and the uncertainties in achieving the desired outcomes increase. Wynne (1992) has argued this is a result of:
The argument is that moving control "upstream" exposes not just more uncertainty but different kinds of uncertainty. The debate is, therefore, fundamentally shifted from the purely technical to the social with a need to examine closely the scientific assumptions and values behind the models.
Friend and Hickling (1987) argue that there are three kinds of uncertainty in decision-making:
Uncertainties about the working environment ("we need more information")
Uncertainties about related decisions ("we need more co-ordination")
Uncertainties about guiding values ("we need clearer objectives")
These uncertainties change through time as the program is implemented; this is an important aspect of the old saying "you can't steer a ship unless it is moving". You cannot resolve all the uncertainties by planning; what becomes important is not necessarily what you might predict at the beginning. The role of adaptive management is to steer this moving ship, keeping it on track while navigating the unknown and the unpredictable.