The Movement Ecology of an Agricultural Pest, Navel Orangeworm, Amyelois transitella

Tracking the movement of small organisms is of tremendous importance to understanding the ecology of populations, communities, and ecosystems. However, it remains one of the most difficult challenges facing the field of movement ecology. This dissertation focuses on the movement of an agricultural pest, the navel orangeworm (Amyelois transitella, NOW). I first examined intercrop movement of NOW between two agricultural commodities, almonds and walnuts. By using protein markers and an enzyme-linked immunosorbant assay technique to detect markers on recaptured moths, I demonstrated significant male NOW movement (up to 300 meters) and no significant directional preferences of movement based on crop, season, or wind velocity. However, protein marker contamination of control moths within traps was significant, limiting our ability to detect movement patterns. In addition, the scale of this study may have been too small to capture larger scale directional patterns of movement. In order to overcome some of the observed challenges of protein marking techniques for small organisms, I developed and tested an intrinsic marking technique for tracking NOW using dietary fatty acid profiles as a biomarker. This was accomplished by analyzing fatty acids from NOW moths raised on two different host plants with significantly different fatty acid profiles. Using this data a linear discriminant analysis model was developed and validated to distinguish NOW based on their larval host plant. Results showed that NOW fatty acid profiles are strikingly similar to those of their host plant. Therefore fatty acids can act as a valuable intrinsic marking technique for tracking small organisms, avoiding many of the drawbacks of external markers, and providing a useful tool for the study of movement ecology. Fatty acid tracking is effective for small organisms, but does not determine movement paths, direction, or distance of movement in a localized setting. In order to draw meaningful conclusions from localized movement data using intrinsic marking techniques, I developed a Gaussian-based dispersal model. This model was applied to field-caught NOW moths from three sites in the central valley of California. Average movement distance was estimated to be about 50 m per generation at two sites and about 600 m per generation at the third site. The study demonstrates that probability-based dispersal models combined with intrinsic marking techniques provides a useful tool for both tracking and understanding the localized movement capabilities of small organisms