logic is programmed for computer calculation. 

 In the latter case, the intent is to simulate 

 complex systems which usually involve non- 

 linear relationships, random components, and 

 time varying events. 



Computer simulations are applicable to prob- 

 lems of the type where management can influ- 

 ence the system's behavior. The purpose of 

 simulating a management system is to test 

 the impact on variables of interest within par- 

 ticular management policies, before such 

 policies are implemented, and influence the 

 real system. Here, the simulation performs the 

 important function of providing infoi'mation 

 about the possible consequences over time of 

 various alternative management policies. Thus, 

 it provides answers to the managers' questions 

 which are of an if-then type. The computer 

 program is an if-then calculator. Systems 

 could be simulated using paper and pencil, but 

 computers can carry out these calculations 

 more efficiently. 



Simulation should be viewed as an iterative 

 problem-solving technique which involves four 

 stages: (1) problem definition, (2) mathe- 

 matical modeling, (3) refinement and testing 

 of the resulting model, and (4) creative design 

 and execution of simulation experiments to 

 provide information relevant to the manage- 

 ment problem. In Figure 1, arrows indicate 

 that the general sequence is from problem 

 definition to application, but the reverse arrows 

 indicate that the process is iterative, or learn- 

 ing in nature. A prior stage might have to 

 be repeated on the basis of information acquir- 

 ed during a subsequent stage of the modeling 

 process. 



Problem definition is fundamental to build- 

 ing a simulation model. This study's inter- 

 disciplinary team, composed of biologists and 

 agricultural systems analysts. Initially met 

 to determine the types of questions the model 

 was to answer. The questions fell into three 

 categories: 



1. Biological questions involving the dynam- 

 ics of the deer population. 



2. Economic questions involving the value 

 or worth of certain events and occurrences 

 within the system. 



3. Management questions which affect the 

 biological system and have economic and 

 social consequences. 



problem-solving process. 



In its present form, the model construction 

 cuts across all three types of questions, and 

 should be viewed as the first generation model 

 of a sequence of models which, hopefully, will 

 be able to answer these questions at more 

 sophisticated levels. This first generation model 

 is essentially a population simulator capable 

 of answering questions mainly of a biological 

 nature, but provides output for management 

 questions — in particular, hunting strategies. 

 Other sections of the output could easily be 

 given economic interpretation. The second 

 generation model will include economic vari- 

 ables such as losses due to deer damage to 

 agricultural and forest lands, and gains, such 

 as hunter expenditure and the value of venison. 

 The proposed third generation model will in- 

 clude a management component which would 

 be capable of evaluating management strate- 



123 



