Rural System's

Modern Wild Faunal Resource System Management
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An Opinion: System Failures and Future Developments

I have spent 30 years trying to build bridges between computer uses and natural resource management, damage management being one part. One part of that was suggesting a systems approach. That has many meanings. I've programmed, paid programmers, lectured, and worked with graduate students. There is much computer use now (2002), not much among natural resource agency staff, so I sense that much of my time was wasted. I judge success based on outcomes, not the process.

I labored under the premise that if computer models for resource issues could be built, then data would become available to fill in the boxes, to be the system input. I also preached that the program or model should be developed first, by experienced people, then the data collected based on analyses done about the sensitivity of the model to each type of data. Why collect come data at high cost when it contributes little or nothing to changing the final results (such as dollars from wool or bushes of clean soybeans)? I never got a model built first; funding groups wanted to get busy in the field. Another reason for failure (I should have seen it) was that I never got all the needed data - and never would!

Even the simplest functional population model requires at least sex (2 categories), age (3 categories), weights (2), reproductive status (2), average young, and breeding age. Therefore, solid numbers about 26 things are needed for such a model to produce a solid estimate. (Of course, there are many reasons for modeling not discussed here.) The chances of knowing 26 things about any population , even those few that are intensively studied, are very small. The reason is that the costs are high and they keep coming. The numbers change before they can be summarized and entered into the model.

I'm not complaining. I'm reporting a perceived failure and I want to suggest what I plan to include in my future efforts. Perhaps some will join me. I plan to continue to model, to use the computer as a way to "think through" the enormously complex and complicated wild animal damage problems we have. I plan to continue to write simple programs to help analyze data (for example, the daily catch, not delaying until the end of the month or the end of the project). I'll make more general models (for example, a population estimate, plus and minus 10 percent; a likely proportion of females, plus and minus 5 percent; and a likely birth rate, plus and minus 5 percent). This is not very sophisticated analyses, but it is tedious and very inefficient to do over and over . . . and therefore it won't be done and decisions will not be informed by the results. We're in the business of deciding and getting better at it. The computer can help. I can suggest what are minimum data and what data we should get first, given the need and likely cost of doing so.

Perhaps I was brought-up in the wrong era, the era of well-funded science and great confidence in science. That has changed and so the future seems more clear than in the recent muddled period. The elements of the new strategy are:

  1. Model
  2. Use available data and past studies
  3. Respect expert observations
  4. Use best estimates plus or minus a reasonable amount
  5. Use data on areas, temperature, precipitation, etc. (the abiotic factors) to refine general principles (e.g., how animal weight varies with latitude)
  6. Narrow areas of study so that data collection is manageable
  7. Confine data collection to the minimum indicated by models, then expand in increments only as it seems necessary
  8. Concentrate system performance measures that can be readily valued in the marketplace, then expand to include other outputs or factors only to the extent that they cover the risks or limits of uncertainty about the monetary estimates.
  9. Feedforward is essential. Go beyond forecasting and prognosticating such as those by the World Future Society and make changes today that reflect confidence in the things foreseen.

Most of those things in the list are part of a systems approach.

  1. An "approach" is a paradigm, scheme, or large pattern of operation. It is not spatial as in "approach the dog with a big stick."
  2. "Get it all together" is a need; how to do so is a serious, major question.
  3. How anyone "gets it all together" is of interest. Clearly some people, some groups, do it better than others.
  4. The characteristics of those who do it best should be learned and copied.
  5. A systems approach is useful.
  6. General systems theory is basic to the approach.
  7. If not the best approach, the challenge is to all interested to present an equal or better approach and all of its characteristics and comparisons.
  8. A systems approach to wildlife management has two fundamental actions, analysis and design.
  9. The systems approach invariably includes inputs, processes, objectives, feedbacks, feedforward, and context!
  10. "Analysis" implies description, take apart, detail, investigate, and measure. "Design" implies develop blueprints, plan, prescribe, supervise, implement and manage.
  11. To "design" requires stating objectives.
  12. Managers design. They should start with objectives. Objectives are criteria for "goodness". Criteria are the essence of epistemology (also known as criteriology).
  13. Do not start with "problems". Problems exist in the gap between objectives and the actual situation.
  14. There are 7 types of objectives. They need to be learned. "Goals" and "objectives" are synonymous. "Types" explain past conflicts in the means of these words. Suggestion: Use "objectives" throughout.
  15. The types:
    1. General,
    2. Fundamental,
    3. Success Criteria,
    4. Constraints (or Policies),
    5. Primary,
    6. Action-like, and
    7. Futuristic.
  16. Maximizing present-discounted value is in primary use throughout natural resource fields. It is a type 3 objective.
  17. Where monetary values are difficult to get, maximizing a benefit-to-cost (B/C) ratio is useful.
  18. Express benefits using

    B = (DVES(R) P I T

    where

    <
  19. Express costs, C, as the total present discounted cost of any and all activities, programs, and projects over the planning period.
  20. To maximize Q* is a reasonable basis for deciding on when a manager is doing well. Promotion, praise, and raises can be based on Q* where

    Q* = [1.0 - (QA - Q) / Q] x 100 QA is the actual score; Q is the stated desired condition; Q* is the "score" being perfect at 100.

  21. An alternative view is the negative feedback equation

    Qt + 1 = Q - (1-C)(Qt-Q)

    Where Q is the desired state (e.g., 2361 units produced per year), Qt the current production, Qt+ 1 the next production (usually next year) and C is the amount of control (e.g., 0.05) a manager can have over reducing the difference.

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    Last revision February 8, 2008.