Abstract
The southern pine beetle (Dendroctonus frontalis Zimmerman) is one ofthe major forest insect pests in the United States. Although beetle populations may be so low during nonepidemic years that their presence can be detected only by specialists, major infestations occur at irregular intervals causing widespread damage to southern pine forests. In 1976, one of a series of years with major outbreaks, the southern pine beetle (SPB) is estimated to have caused more than $130 million in damage to southeastern woodlands. (1) Costs of replacing lost growing stock and of control and salvage operations are significant for local, state, and federal governments, but private landowners and industry, the principal owners of small forest lots, must also bear a large share of these costs. An important dimension to limiting damage from infestations is the ability to forecast the time and place oftheir occurrence so that timely action can be taken to prevent or to control outbreaks. This paper describes multiple regression models designed to identify relationships between the location and severity of SPB infestations and variations in climate. The study focuses upon the analysis of selected data from North Carolina and Arkansas. Previous attempts to construct predictive regression models have relied mainly upon data from Texas and Louisiana and have forecast either annual numbers of infestations for large areas or monthly totals for small areas. (2) The research described here is an effort to form monthly models for comparatively small multi-county regions using several climatic variables not previously examined. These models differ from earlier efforts, therefore, with
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