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Refuges of non-Bt cotton are used to delay Bt resistance in the pink bollworm (Pectinophora gossypiella, Lepidoptera: Gelechiidae), a pest that eats cotton seeds. Contamination of refuges by transgenic Bt cotton could threaten the efficacy of such refuges by increasing the relative survival of larvae that carry alleles for Bt resistance. Here I compared contamination levels in refuges of varying configuration and distance from Bt. I found two types of contamination at low rates in refuges: outcrossing by Bt pollen and adventitious Bt plants. Unexpectedly, outcrossing did not differ between refuge configurations, and did not decrease as distance from Bt fields increased, perhaps because Bt plants in refuges acted as the main Bt pollen source. Bioassays, conducted to evaluate the impacts of contamination on pink bollworm resistance, indicated that Bt plants in refuges may increase the frequency of resistance alleles at a higher rate than outcrossing by Bt plants.

The within-field spatial distribution of F₁, F₂, and F₃ pink bollworm (PBW) (Pectinophora gossypiella Saunders) generations were modeled with Taylor's power law (TPL), Iwao's patchiness regression (IPR), and the geostatistical semivariogram. Kriging interpolation was used to grid data for the generation of isarithmic maps. Distributional patterns and movements within a field are displayed in a time series of three maps depicting density across the field. The sampling protocol was replicated in eight commercial cotton fields in south-central Arizona during 1985 and 1986. Permanent sample stations were situated throughout the fields on a regular grid pattern. Samples were collected during the peak larval population and handled so as to maintain the integrity of site-specific samples (spatially identified by X,Y coordinates). TPL and IPR could not be used satisfactorily to model the F₁ generation. TPL fit the observed F₂ and F₃ data better than IPR. Both methods predicted the F₂ to be more highly aggregated than the F₃. For a given precision, optimum sample size increased when TPL and IPR model parameters were incorporated into sample size formulae relative to a formula which assumed random distribution. Ninety-five percent of the modeled PBW distributions were autocorrelated in 2-dimensional space and shown to conform to regionalized variable theory by the successful application of geostatistics. The semivariogram models are in conceptual agreement with traditional models and represent a worthy alternative to traditional modeling methodology. The semivariogram models have a large nugget effect proportion (average = 67%) which, in combination with low PBW density in commercial fields, limits the applicability of geostatistics in this system. Isarithmic maps showed that F₁ larvae are either localized near a field edge or generally scattered throughout the field. No consistent inter-generational dispersal pattern was identified. The use of systematic grid sampling is most advantageous (relative to random sampling) when density and the spatial dependence of samples is high, or many samples can be taken. Systematic sampling and kriging estimation yielded more precise estimates than random sampling and classical statistics, but the advantage was buffered by low PBW densities and large nugget effect.

Background: The pink bollworm Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae) is one of the world's most important pests of cotton. Insecticide sprays and transgenic cotton producing toxins of the bacterium Bacillus thuringiensis (Bt) are currently used to manage this pest. Bt toxins kill susceptible insects by specifically binding to and destroying midgut cells, but they are not toxic to most other organisms. Pink bollworm is useful as a model for understanding insect responses to Bt toxins, yet advances in understanding at the molecular level have been limited because basic genomic information is lacking for this cosmopolitan pest. Here, we have sequenced, de novo assembled and annotated a comprehensive larval midgut transcriptome from a susceptible strain of pink bollworm. Findings: A de novo transcriptome assembly for the midgut of P. gossypiella was generated containing 46,458 transcripts (average length of 770 bp) derived from 39,874 unigenes. The size of the transcriptome is similar to published midgut transcriptomes of other Lepidoptera and includes up to 91 % annotated contigs. The dataset is publicly available in NCBI and GigaDB as a resource for researchers. Conclusions: Foundational knowledge of protein-coding genes from the pink bollworm midgut is critical for understanding how this important insect pest functions. The transcriptome data presented here represent the first large-scale molecular resource for this species, and may be used for deciphering relevant midgut proteins critical for xenobiotic detoxification, nutrient digestion and allocation, as well as for the discovery of protein receptors important for Bt intoxication.

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