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United States Department of Agriculture

Agricultural Research Service

Research Project: ECOLOGICALLY-BASED PEST MANAGEMENT STRATEGIES FOR WESTERN COTTON

Location: Pest Management and Biocontrol Research

Title: Threshold choice and the analysis of protein marking data in long distance dispersal studies.

Authors
item Sivakoff, Frances -
item Rosenheim, Jay -
item Hagler, James

Submitted to: Methods in Ecology and Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 11, 2010
Publication Date: February 1, 2011
Citation: Sivakoff, F.S., Rosenheim, J.A., Hagler, J.R. 2011. Threshold choice and the analysis of protein marking data in long distance dispersal studies. Methods in Ecology and Evolution. 2:77–85.

Interpretive Summary: A valuable technique in the study of insect movement is protein marking, a quantitative method where individuals are categorized as marked or unmarked based on the amount of foreign protein detected by a protein-specific enzyme-linked immunosorbent assay (ELISA). Whether individuals are considered marked or not is dependent on a threshold value chosen by the experimenter. The traditionally employed method of choosing the threshold accepts some risk of false positives, wherein an unmarked individual is misclassified as marked. The error rate associated with this method relies on assumptions violated by most ELISA data. We examine the effect of violating these assumptions on the false positive rate. In long-distance dispersal studies where the ratio of unmarked to marked insects is high, false positives can result in incorrect estimates of insect movement abilities. Using simulations, we demonstrate that the conventional method for choosing a threshold: (i) masks the presence of false positives, (ii) results in a 10-fold higher than expected false positive rate, and (iii) relies on assumptions of normality that are rarely satisfied; non-normality produces further increases in false positive rates. We introduce a new procedure for choosing a threshold that decreases the incidence of false positives and allows data to be corrected for anticipated rates of false positives. This methodology should enhance researcher confidence in the data generated from long distance dispersal studies using protein marking techniques.

Technical Abstract: 1. A valuable technique in the study of insect movement is protein marking, a quantitative method where individuals are categorized as marked or unmarked based on the amount of foreign protein detected by a protein-specific enzyme-linked immunosorbent assay (ELISA). 2. Whether individuals are considered marked or not is dependent on a threshold value chosen by the experimenter. The traditionally employed method of choosing the threshold accepts some risk of false positives, wherein an unmarked individual is misclassified as marked. The error rate associated with this method, which was adopted from the rubidium marking literature, relies on assumptions violated by most ELISA data. 3. We examine the effect of violating these assumptions on the false positive rate. In long-distance dispersal studies where the ratio of unmarked to marked insects is high, false positives can result in incorrect estimates of insect movement abilities. 4. Using simulations, we demonstrate that the conventional method for choosing a threshold: (i) masks the presence of false positives, (ii) results in a 10-fold higher than expected false positive rate, and (iii) relies on assumptions of normality that are rarely satisfied; non-normality produces further increases in false positive rates. 5. We introduce a new procedure for choosing a threshold that decreases the incidence of false positives and allows data to be corrected for anticipated rates of false positives. This methodology should enhance researcher confidence in the data generated from long distance dispersal studies using protein marking techniques.

Last Modified: 4/16/2014
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