USING MEASURED DATA AND EXPERT OPINION IN A MULTIPLE OBJECTIVE DECISION SUPPORT SYSTEM FOR SEMIARID RANGELANDS
A Decision Support System (DSS) can be used to structure information in a way that leads to improved 
decision making for natural resources. The decisions will only be as good as the information on which they are based. As 
the applications of a DSS are outpacing the available databases and simulation models, there is an increasing reliance on 
expert opinion for information on resource management systems. As a result, the effect of information source on the 
outcome from the DSS is an important issue. This article compares the outcomes from a prototype DSS (P-DSS) developed 
by the USDA-ARS Southwest Watershed Research Center in Tucson, Arizona, when measured data and expert opinion are 
used to quantify eight decision criteria in the evaluation of four management systems (yearlong and rotation grazing, 
each with mesquite trees (Prosopis velutina Woot.) retained or removed) for semiarid rangelands. The decision criteria 
are sediment yield, channel erosion, runoff rate and quantity, rangeland condition, aboveground net production, and 
wildlife habitat for quail and javelina, although the analysis is not restricted to these criteria. When measured data are 
used to quantify the decision criteria, rotation grazing with mesquite removed is the preferred management system, 
whereas yearlong grazing is the preferred system when expert opinion is used. The experts also directly ranked the four 
management systems. The difference between the experts’ ranking and the P-DSS results based on expert inputs is a 
concern for future use of decision support system technology, particularly when information sources are blended.