Project Number: 5303-21220-003-07
Project Type: Reimbursable

Start Date: Feb 15, 2007
End Date: Feb 14, 2008

Objective:
Evaluate the relationship between Lygus density in a focal cotton field and the prevalence of important alternative Lygus habitats in the landscape.

Approach:
The analyses will consist of a series of multiple regressions. For our dependent variable (Lygus density) we will use three estimation approaches. First, we will use sweep-sample estimates of mean Lygus densities observed during five periods of the growing season: (i) 20 May-10 June; (ii) 10-30 June; (iii) 1-15 July; (iv) 16-31 July; and (v) 1-15 August. Second, we will use exactly the same Lygus estimates, but will remove from the data set any observations made for fields after they were treated to suppress Lygus. Finally, we will use the total number of pesticide applications made over the course of the growing season to suppress Lygus as an indirect measure of Lygus density. The independent variables will be measures of the relative abundance of each of five habitat types (foothill habitat; alfalfa; safflower; cotton; other) found within successive concentric `doughnuts¿ centered on the focal cotton field (e.g., see Carrière et al. 2001, 2004, 2005, Thies et al. 2003). Successive doughnuts will be defined at radii of 1, 2, 3, 4, 5, 7, 10, 15, 20, 30, and 40 kilometers. The most challenging aspect of this analysis will be to calculate the plant community composition of the concentric doughnuts. This will be accomplished in two ways. First, digital crop maps are available for Kern County for 2001-2005. We anticipate that approximately 25% of our database will consist of fields in Kern County, and thus, at a minimum, we will be able to complete the objective using this subset of the database. Second, we will attempt to produce a digital crop map for the entire valley using remote sensing images (see requests for Landsat Images and Space Imaging Ikonos data). To interpret the remote sensing images, we will obtain ranch maps from our cooperating growers. Once digitized, these ranch maps will serve as `ground truth points¿ that will allow us to classify the remotely sensed imagery into the habitat types of interest (Ortigosa et al. 2000); this will be done using Geographic Information System (GIS) technology, using a principal components analysis. The spatial delimitation of the foothill plant communities will be entered manually. The size of our database, even if restricted to Kern County, should provide good statistical power to assess the relative importance of the different features of the crop and natural habitat mosaic surrounding commercial cotton fields. The spatial scale over which putative source and sink habitats shape Lygus densities in nearby cotton will provide growers with information that should be useful in designing the spatial arrangement of fields or identifying the needed spatial scale for effective regional Lygus management efforts. Finally, the approach proposed here should be readily extended to studying the landscape ecology of other pests studied with consultant-generated data. Documents Trust with UC Davis. Log 30084.