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United States Department of Agriculture

Agricultural Research Service


Location: Exotic and Invasive Weeds Research

2013 Annual Report

1a. Objectives (from AD-416):
1. Complete statistical analysis on yellow starthistle field study. 2. Complete computer model parameterization. 3. Complete journal articles on joint research.

1b. Approach (from AD-416):
1. Field data collected during 2007 and 2008 will be statistically evaluated and summary graphics prepared. 2. Statistically significant biological parameters will be developed and incorporated into an existing hermes model of yellow starthistle growth. 3. Both field data on yellow starthistle growth and model development and application will be published in peer reviewed journals. Documents Grant with UC Santa Cruz.

3. Progress Report:
No new research was conducted on this project since 2012. The principal investigator has left the University of California and now works at the University of Florida, Gainesville. Significant accomplishments, however, have been achieved over the entire lifespan of the project that address objectives 2 and 3 of the parent project. This effort led to the development of a predictive model of yellow starthistle growth and development and a further model of one of its key insect natural enemies, Cheatorellia succinea. This model was developed using both spatial and temporal dynamic methodologies that allow the estimation of invasive weed growth and natural enemy synchrony over complex landscapes with extremely dynamic driving variables such as temperature and light levels. These models estimate biological activity of the key components on an hourly basis through years of simulation. Further experimentation and analysis led to the development of a mechanistic set of methods that allow the prediction of Photosynthetic Active Radiation (PAR) across northern California, with adjustment parameters so that it could be used at any location, worldwide. The prediction of PAR is important, as it is an environmental parameter that is rarely measured in standard weather stations yet is essential in predicting plant growth and development. These models are being used to assess the biological control of invasive plant species and other integrated pest management methods.

4. Accomplishments

Last Modified: 10/18/2017
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