Deconstructing the control of the spotted alfalfa aphid Therioaphis maculata. (14th May 2013)

• Record Type: Journal Article
• Authors: Gutierrez, Andrew Paul; Ponti, Luigi
• Is Part Of: Agricultural and forest entomology. Volume 15:Number 3(2013:Aug.)
• Page Start: 272
• Page End: 284
• Publication Date: 2013-05-14
• Subjects: Insect pests -- Control -- Periodicals; Agricultural pests -- Control -- Periodicals; Forest insects -- Control -- Periodicals; 632.7
• DOI: 10.1111/afe.12015
• Languages: English
• ISSNs: 1461-9555

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p> <list list-type="order"> <list-item> <p>The control of insect pests and other taxa may be a result of many factors that are difficult to separate and quantify. Introduced parasitoids, host plant resistance, pathogens and native predators led to the successful control of the spotted alfalfa aphid (SAA; <italic>Therioaphis maculata</italic> Monell) in California and elsewhere, although the relative contribution of each factor remained largely unknown.</p> </list-item> <list-item> <p>The relative contribution of each control factor was estimated using a weather‐driven physiologically‐based demographic system model consisting of alfalfa, SAA, its three exotic parasitoids [<italic>Aphelinus semiflavus</italic> Howard, <italic>Praon palitans</italic> Muesebeck and <italic>Trioxys complanatus</italic> (Quilis)], a native coccinellid beetle [<italic>Hippodamia convergens</italic> (Guérin‐Menéville)], a fungal pathogen [<italic>Erynia neoaphidis</italic> Remaudière & Hennebert (Zygomycetes: Entomophthorales)] and host plant resistance (<italic>HPR</italic>). Daily weather data for the period 1995–2006 from 142 locations in Arizona and California were used to drive the model.</p> </list-item> <list-item> <p>The factors were introduced to the model singly or in combination to assess their effects in suppressing simulated SAA populations using SAA‐days m<sup>−2</sup> year<sup>−1</sup> (i.e. density) as the metric of control.</p> </list-item> <list-item> <p>Data from selected runs were mapped using the geographic information system <sc>grass</sc> (http://grass.osgeo.org). The simulation data across all factor combinations, years and locations were summarized using linear multiple regression, with the dependent variable being log<sub>10</sub> SAA‐days m<sup>−2</sup> year<sup>−1</sup> and the independent variables being the presence–absence (0, 1) of the various factors and their interactions. Marginal analysis of the regression model (∂<italic>y</italic>/∂<italic>x</italic><sub><italic>i</italic></sub>) enabled separation of the average effects of the different factors (<italic>x<sub>i</sub></italic>) given the average effects of the other factors.</p> </list-item> <list-item> <p>Alone, each factor failed to control SAA, as did combinations of the parasitoids and coccinellid predation. Control was predicted across all ecological zones only when all mortality factors were included. The marginal analysis suggests that the order of importance of the mortality factors is <italic>HPR</italic> > coccinellid beetles <italic>> T. complanatus > P. palitans > A. semiflavus ></italic> the fungal pathogen. The variability of control by coccinellid beetles and the fungal pathogen was high and hence unreliable.</p> </list-item> </list> </p> </abstract>