3. Systems Concepts
3.1. The systems approach
3.1.1. The nature of the problem in pest management
3.1.1.1. We are dealing with a very complex system
  • Multi-pest -- secondary, tertiary, etc. interactions

  • Large number of variables to consider

  • Many levels of organization

  • Time and space must be considered
3.1.1.2. We are aiming for a sophisticated level of management
  • Predictive

  • Quantitative

  • Multifactor control -- optimization
3.1.1.3. The context is important -- ecological, economic and social considerations
3.1.2. Origins and development of the systems approach
3.1.2.1. Arose out of the need for linking anti-aircraft guns to radar for the purpose of shooting down airplanes during World War II
3.1.2.2. Methodology developed by engineers (e.g. the Apollo program)
3.1.2.3. Adopted by biologists (principally ecologists) in the 60's
3.1.2.4. Applied to agricultural problems (IPM) in the 70's
3.1.3. Definition of the "systems approach" -- a combination of all that follows (The whole is greater than the sum of its parts.)
3.1.3.1. Methodology for solving complex problems
3.1.3.2. Planning and management
3.1.3.3. Interdisciplinary teamwork
3.1.3.4. Organization of physical and human resources (from planning to operation)
3.1.3.5. Formalized quantitative concepts (mathematics)
3.1.3.6. Disciplined non-quantitative thinking
3.1.3.7. Computers
3.1.3.8. Modeling and simulation technology
3.1.3.9. Optimization technology
3.1.4. The systems approach is capable of handling complex problems with trade-offs in performance criteria (as opposed to single problem/single solution)
3.1.5. Jargon
3.1.5.1. System -- a set of interacting elements
  • We arbitrarily define our system by defining its boundary (system/environment dichotomy)

  • The boundary depends on our objectives

  • Example:

3.1.5.2. System component = element = subsystem
3.1.5.3. System structure -- how components interact
3.1.5.4. Input = stimulus
3.1.5.5. Output = response
3.1.5.6. Behavior of system -- time series of responses
3.1.5.7. State of system -- the condition of the system at any point in time
3.1.5.8. Resolution (hierarchy of levels)
Example:

3.2.6. System analysis, management, design
3.2.6.1. Analysis -- observe or measure response to given stimulus
e.g. Measure plant growth as a function of temperature

3.2.6.2. Management (control) -- adjust stimulus to achieve desired response

e.g. adjust temperature to achieve desired plant growth response
3.2.6.3 Design -- alter structure of system to achieve desired response under a given set of stimuli

e.g. select cultivar to give desired growth response under given climatic conditions
3.2.7. The systems approach as a problem solving methodology
3.2.7.1. Definition of the problem
  • Needs analysis -- consider all people and institutions; identify conflicting needs

  • System identification -- system/environment dichotomy
3.2.7.2 Define objectives
  1. Determine desired performance of system

    • Ojectives must relate to needs

    • Evaluation criteria must be established

  2. Set priorities

  3. Objective mapping

    • Objectives occur in hierarchies

    • At any level you look up to see where you are going and look down to see what must be accomplished to get where you are
3.2.7.3. Abstract modeling
  • Representation of real system

  • Identify components, constraints, parameters, input variables, output variables

  • Are inputs uncontrollable? Should they be monitored?

  • Are inputs controllable? Should they be controlled or monitored?

  • Determine level of resolution
3.2.7.4. Implementation
  • Generate alternatives

  • Design a system in such a way that it can be managed
3.2.7.5. Performance evaluation
  1. Social, political, economic analysis

  2. Weigh costs and benefits

  3. Recycle through system -- closed loop

    • Feedback -- change in a variable that causes a change in that same variable at some future time

    • Iterative -- go through the cycle repeatedly
3.2. Modeling

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