Boll Weevil Regional Management

Literature Review

Boll weevil management has historically been addressed on a field-by-field basis. Although analytical tools have not been available to address the regional management of highly dispersive pests such as the boll weevil, the recent development of geographic information systems (GIS) holds particular promise in this area. Initially a tool of geologists and geographers, geostatistical analyses and GIS are increasingly used to develop regional management programs for arthropods due to their capacity to analyze spatial interactions between arthropods and their biotic and abiotic

environment. Johnson & Worobec (1988) used these methods to correlate area-wide grasshopper densities with spatial representations of rainfall and monthly hours of sunlight. Johnson (1989) used GIS to correlate grasshopper densities with soil type based on analyses of the interaction between previous years' densities. Gage et al. (1990) predicted areas of severe forest defoliation in Michigan due to Gypsy Moth, and explained 79% of the variability  in   infestation  intensity  using  a  spatially-oriented  GIS  

model. Along these lines, Liebhold et al. (1991) used geostatistics to characterize spatial dependency of gypsy moth eggs in New England forests. Wiygul & Smith (1989) computerized maps and data relating cotton fields to recognizable landmarks, surrounding vegetation,  insecticide applications,   and boll weevil trap counts,  while Wiygul et al. (1990) described the linking of pheromone trap densities of overwintered boll weevils to nearby vegetation. McCoy et al. (1992) incorporated boll weevil trap densities, ground cover, cotton planting date, and soil type into a GIS database and represented these as spatial features to compliment a boll weevil eradication program. GIS and geostatistical analyses have tremendous potential for increasing our understanding of the spatial relationships between arthropods and their habitats.

Systems modeling has been shown to be of use for addressing strategic hypotheses concerning the optimization of weevil management (Curry et al. 1980, Gutierrez et al. 1981, Feldman & Curry 1983, Gutierrez & Daxl 1984, Schoolfield 1983, Talpaz et al. 1978). Although strategic modeling has primarily been the approach used in modeling boll weevil management, this has not been the case with cotton modeling in general. In a review of the literature, 248 publications were identified on modeling the growth and development of cotton and its response to agronomic, climatic, and pest variables. Whereas many of these papers have a strategic orientation, nearly as many focus on the tactical or day-to-day field level management of cotton. While strategic modeling has been an

invaluable aid in focusing research efforts on relevant biological processes, and improving our knowledge of ecosystem theory and pest management principles, tactical modeling must be credited with extending scientific modeling principles to the field level management of cotton. Our own research on cotton system modeling has focused on developing mechanistic-based crop and pest simulation models to address both the strategic and tactical aspects of management (Blood & Wilson 1978, Gutierrez & Wilson 1989, Gutierrez et al. 1987, Hearn et al. 1981, Ives et al. 1984, Plant & Wilson 1986, Plant et al. 1990, Trichilo & Wilson 1993, Wilson 1989, Wilson & Gutierrez 1980, Wilson et al. 1983, 1987, 1991, 1992).

Modeling efforts have greatly expanded our understanding of the biology, ecology, and management of cotton arthropods, and have provided unique insight, generally unavailable through more conventional research. However, because existing cotton crop and pest models do not account for migration from field to field or dispersal to and from overwintering habitats, it is questionable as to whether they are suitably structured for addressing the management of a highly dispersive insect such as the boll weevil. To adequately address regional boll weevil management, an appropriate model would require the biological detail collectively inherent in several of the above models, but would differ conceptually by containing a spatial element for the seasonal movement of weevils from one habitat to another.

Document Author:

Photos:

Revised: