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A Note on Wildlife Information Systems

This unit may support the Species Specific Management concept as well as the Wildland Knowledge Base enterprise.

Information is needed in decision making. It is the chief input to any decision system. Little more important than the other parts of the decision-making system, information remains very important.

The parts of a system often need review:

Wildlife resource decision making, if done well, requires enormous amounts of information.

For example, if there are 500 large creatures in a state and 200 critical factors about each, then there are merely 100,000 things that the average manager must begin to master. Withj needed information on the atmosphere, hydrosphere, lithosphere and a few other components of the biosphere (namely all of the plants and at least 50,000 insects, there are clearly enormous information needs.

I judge that the average faunal resource management decision should require the involvement of at least 80 factors. I judge that less than three "chunks" (21 pieces of information) of information are used in 95% of the decisions. Thus the chances of most decisions being wrong (at least sub-optimal) are very great.

To use all of the needed information is, until recently, unrealistic. For example, consider that a decsion is to be reached in three days. In three days there are only about 2500 available action minutes for a hard-working individual. If one "fact" is gotten and utilized at the rate of 1 per minute (silly, but try the assumption) only 30 species (with their 80 factors each) can be included. This is a very small group, a small part of even a very simple ecosystem. Failure to be adequately inclusive is assured.

There needs to be a way to begin improvement ... or admit to failure ... or the sillyness of continuing to try to complete a task that clearly cannot be achieved. How might we begin?

• We categorize the decisions as done by Buffington in his PhD dissertation. This gives structure to inputs and allows us to see some priorities for building a data base.
• We see that everything occurs in some space, so we build a GIS. The name is wrong but we need much more than geographic information, only geographic coordinates for all types of information. That must include human populations data (US Census), economic data, legal data (the laws and regulations differ greatly bu counties,regions, and states), and all observations have to have a date ... for everything is changing and we need to create transition tables (e.g., ecological succession, forest aging, and building decay.) Strangely over many years, administrators have prevented human population and economic data from being placed in a "resource" data base. These are major factors affecting wild animal, forests, and other uses but unless they are included within a system, there is great difficulty extracting, adjusting units, and presenting them together (simple correlations, for example).
• We clarify decision making in the agency or company. It probably has no more than 3 common patterns and fits (1) breakeven analyses, (2)simple maximizing (or minimizing), and (3) linear programming. Without clear objectives (the usual case), simulations may be adequate, then choices made from among the contrived runs.
• We develop primeness maps (probable suitability over time for each species) (continually improved as GPS-coded field observations and research add to knowledge).
• We include these with out wildlife information systems (e.g., those of the Conservation Management Institute of Virginia Tech or like that developed for New Mexico).
• Utilize the core essentials of:
  • Occurrence in the state and identification information
  • Status (legal, game, threatened, etc.)
  • County-level species ddata
    • Distribution by administrative units
    • General distribution
    • Site specific distribution
  • Food habits
  • Species environmental associations
  • Life history information
  • Management practices
  • References

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This Web site is maintained by R. H. Giles, Jr.
Last revision January 17, 2000.