Environmental Monitoring

Environmental Monitoring
   


An approach, which is useful for thinking about management, is that of Soft Systems Methodology (SSM). This approach, based on business models, starts with a systems view (like ecology) but includes all the players in the issues, specifically incorporating the social aspects. The participants in the process create a "root definition" using the "CATWOE" mnemonic to assist in including all relevant aspects of concern:

  • C ustomers
  • A ctors
  • T ransformation (desired outcomes)
  • W eltanschauung (or world view)
  • O wners
  • E nvironment (all aspects relevant to problem - social, physical etc)


The process recognises explicitly the roles of all players in the "problem" and moves toward coherent action. The outcome I believe is focused on what is achievable and moving in the desired direction, rather than imposing a scientifically correct solution regardless of acceptability. An analogy I have utilised is that "you can't steer a ship unless it is moving".

An example based on catchment management is presented in Levy and Synnott (1993). The root definition they arrived at was "A system subscribed to and owned by state and local government agencies, landholders, and the community to implement ICM policies, recognising the need for sustainable development within economic and political constraints for current and future generations " and the rich picture is shown below. The intention is not to model "reality" but to clarify the processes of management and effective intervention.

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A similar structured approach is that of the "cause-effect" or "fishbone" diagrams . Having identified the desired outcome(s) all factors that contribute to that outcome (positively or negatively) are identified. Linkages between factors are identified to create a coherent overview of the relations that exist between causal factors and the outcome(s). Any information, site specific or generic, that is relevant is tagged to the factors and used to identify priorities taking into account short and long term implementation or effects, visibility, cost-effectiveness, etc. This approach can assist a critical path analysis ensuring that actions are undertaken in a sequence and timing to optimise effectiveness.



Ecological and conceptual models can be used to visualise and define the interactions involved and lead to an understanding of the system, proposed intervention and expected outcomes. Mind experiments can be undertaken to ask "what if...?" to assess the robustness of the model, the key parameters for sampling, and the statistical basis of the program.



A recent workshop noted:
"Conceptual models:

  • provide a framework for organizing our knowledge in order to help us understand how systems function;
  • represent what we think we know and don't know, but may be based on incorrect assumptions because we don't know enough;
  • are dynamic and evolve with increased understanding;
  • take different forms, depending on the modeller, the purpose and the audience;
  • with respect to bay-delta species or ecosystems, are mostly implicit, i.e., not well documented and not available to other than the modeller him/herself.


The process of thinking through the model and discussing the model with peers is more important than the model itself".

Be aware of the implications of scale and the usefulness of your models in the context of your problem and the design of your program.

When we think about defining "the problem" we also need to consider the kind(s) of designs (and outcomes) we might want, or be willing to accept. One of the key issues is the extent of inference that is justified by our analysis. I discuss the elements of Experimental design elsewhere but there is a difference in whether we define the problem as (say) an investigation into a single GPT or a number of different GPTs in different catchments. A single upstream/downstream design cannot, by definition, have the strength of inference of a multiple study (so long as the larger study is designed well).


   
 

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