Managing insect pests in mosaic landscapes of bioenergy and conventional cropping systems in the U.S. Gulf Coast

Wednesday, November 18, 2015: 10:24 AM
200 I (Convention Center)
Yubin Yang , Texas A&M AgriLife Research, Beaumont, TX
Lloyd T. (Ted) Wilson , Texas A&M AgriLife Research, Beaumont, TX
T.E. Reagan , Dept. of Entomology, Louisiana State University, Baton Rouge, LA
Julien M. Beuzelin , Dean Lee Research Station, Louisiana State University AgCenter, Alexandria, LA
Jing Wang , Texas A&M AgriLife Research, Beaumont, TX
With plentiful rainfall, abundant land, and mild winters, the U.S. Gulf Coast is among the geographic regions with the highest potential for production of dedicated cellulosic bioenergy crops, especially energy cane and high biomass sorghum. The two most destructive crop pests in the region are Mexican rice borer and sugarcane borer, which also attack graminaceous bioenergy crops. The expected large-scale production of bioenergy crops will significantly impact the abundance of different plant inhabiting insects, and will require modification of existing pest management programs. The overall goal of this research is to build a landscape-wide pest management program that will mitigate insect pest pressures and damage to bioenergy crops in interaction with conventional crops in the U.S. Gulf Coast region. Critical data on the biological, ecological, and economic impact of major pests and diseases have been obtained. Program activities include landscape-wide plant and pest phenological surveys, multi-crop field and greenhouse bionomics experiments, and pest density/yield response studies. An integrated system predicting the potential impact of IPM practices on stem borers and economic sustainability are being developed. Forecasts of sugarcane borer and Mexican rice borer population dynamics are based on a cohort-based distributed maturation method. Major components of the pest population model include age-stage-specific development, survival, reproduction, and overwintering of pests, as well as plant yield response to injury. The system features crop models predicting phenological stages and yield for energy cane, biomass sorghum, and rice. When combined with results from field experiments and greenhouse studies, simulation analyses will identify optimal pest management tactics for individual fields and regional multi-use landscapes.