EFFECTIVENESS OF ALTERNATIVE HEURISTIC ALGORITHMS FOR IDENTIFYING INDICATIVE MINIMUM REQUIREMENTS FOR CONSERVATION RESERVES

We compared the results of 30 heuristic reserve selection algorithms o n the same large data set. Twelve of the algorithms were for presence- absence representation goals, designed to find a set of sites to repre sent all the land types in the study region at least once. Eighteen al gorithms were intended to represent a minimum percentage of the total area of each land type. We varied the rules of the algorithms systemat ically to find the influence of individual rules or sequences of rules on efficiency of representation. Rankings of the algorithms according to relative numbers or areas of selected sites needed to achieve a sp ecified representation target varied between the full data set and a s ubset and so appear to be data-dependent. We also ran optimizing algor ithms to indicate the degree of suboptimality of the heuristics. For t he presence-absence problems, the optimizing algorithms had the advant age of guaranteeing an optimal solution but had much longer running ti mes than the heuristics. They showed that the solutions from good heur istics were 5-10% larger than optimal. The optimizing algorithms faile d to solve the proportional area problems, although heuristics solved them quickly. Both heuristics and optimizing algorithms have important roles to play in conservation planning. The choice of method will dep end on the size of data sets, the representation goal, the required ti me for analysis, and the importance of a guaranteed optimal solution. (C) 1997 Published by Elsevier Science Ltd.