Wednesday, December 12, 2007
D0556

Within-tree southern pine beetle mortality rates in relation to tree and stand variables, and their impact on SPBMODEL predictions

Marita P. Lih, mplih@charter.net1, James D. Smith, jdsmith@fs.fed.us2, Andrew Birt, abirt@tamu.edu3, Robert N. Coulson, r-coulson@tamu.edu3, James M. Guldin, jguldin@fs.fed.us2, and Fred M. Stephen, fstephen@uark.edu1. (1) University of Arkansas, Department of Entomology, 319 Agriculture Building, Fayetteville, AR, (2) USDA Forest Service, Forest Health Protection, 2500 Shreveport Hwy, Pineville, LA, (3) Texas A&M University, Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, Department of Entomology, College Station, TX

Southern pine beetle (SPB) (Dendroctonus frontalis) is a multivoltine insect with as few as three or as many as nine overlapping generations per year. During periods of epidemic populations, SPB infestations, or spots, may grow to cover hundreds of hectares. However, most infestations remain much smaller, and many die before they are even detected by the forest manager.

SPBMODEL is a southern pine beetle population dynamics simulation model that was developed using data collected from SPB infestations during the warmer months of the year (i.e., June-October). SPBMODEL provides short-term (up to 92 days) predictions of spot growth (i.e., tree mortality) in existing infestations. The simulation model includes three regression equations that use tree and stand variables and day of the year in calculating the values of within-tree beetle mortality rates.

SPB population and spot-growth data are currently available that allow expansion of the regression analyses to include the full year, and concomitant exploration of seasonal associations between SPB, their host trees, and their forest environment. To date, SPBMODEL has not successfully predicted spot growth in the winter and spring. These analyses will be used to refine within-tree beetle mortality rates in the model, and may enhance our ability to provide reliable estimates of spot growth throughout the year. Incorporation of available data into the model, and validation of the revised model’s performance over a broad range of conditions expands the model’s capabilities and enhances the forest pest manager’s ability to assess potential growth and impact of existing SPB infestations.



Species 1: Coleoptera Curculionidae (Scolytidae) Dendroctonus frontalis (southern pine beetle)