Deconstructing the control of the spotted alfalfa aphid Therioaphis maculata

Abstract

1 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; Therioaphis maculata Monell) in California and elsewhere, although the relative contribution of each factor remained largely unknown. 2 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 [Aphelinus semiflavus Howard, Praon palitans Muesebeck and Trioxys complanatus (Quilis)], a native coccinellid beetle [Hippodamia convergens (Guérin-Menéville)], a fungal pathogen [Erynia neoaphidis Remaudière & Hennebert (Zygomycetes: Entomophthorales)] and host plant resistance (HPR). Daily weather data for the period 1995-2006 from 142 locations in Arizona and California were used to drive the model. 3The factors were introduced to the model singly or in combination to assess their effects in suppressing simulated SAA populations using SAA-days m −2 year −1 (i.e. density) as the metric of control. 4 Data from selected runs were mapped using the geographic information system grass (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 10 SAA-days m −2 year −1 and the independent variables being the presence-absence (0, 1) of the various factors and their interactions. Marginal analysis of the regression model (∂y/∂x i ) enabled separation of the average effects of the different factors (x i ) given the average effects of the other factors. 5 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 HPR > coccinellid beetles > T. complanatus > P. palitans > A. semiflavus > the fungal pathogen. The variability of control by coccinellid beetles and the fungal pathogen was high and hence unreliable.

Biology and trophic interactions of lucerne aphids

“…Focus should be placed on incorporating multi‐trophic interactions into long‐term field studies, as opposed to short‐term glasshouse studies, using mixed or various individual cultivars. Gutierrez and Ponti () identified host plant resistance as the most important mortality factor of SAA in California. They also predicted that, alone, each mortality factor failed to control SAA, whereas successful control was achieved by a combination of factors.…”

Tritrophic analysis of the prospective biological control of brown marmorated stink bug, Halyomorpha halys, under extant weather and climate change

“…This point was made by Toko et al (2019) who opined in review of the highly successful biological control program against cassava mealybug (Phenococcus manihoti Matile-Ferrero, Hemiptera: Pseudococcidae) in sub-Saharan Africa that the system model (Gutierrez et al 1993) demonstrated that the encyrtid parasitoid Apanogyrus lopezi Howard reduced mealybug populations by 90%, while indigenous lady beetles cut occasional peak mealybug populations by 20%, a result that no field study could have demonstrated. A well-parameterized PBDM was used to analyze the biological control of the spotted alfalfa aphid (Therioaphis maculata Buckton, Hemiptera: Aphididae) across the disparate ecological zones of California by the combined time and place action of parasitoids, disease, and coccinellid predators (Gutierrez and Ponti 2013a). Tritrophic PBDM analyses of the biological control of invasive pest species, include vine mealybug (Planococcus ficus (Signoret); Gutierrez et al 2008), glassy-winged sharpshooter (Homalodisca vitripennis (Germar); Gutierrez et al 2011), Asian citrus psyllid (Diaphorina citri Kuwayama; Gutierrez and Ponti 2013b), coffee berry borer (Hypothenemus hampei (Ferrari); Cure et al 2020) and others.…”

“…PBDMs capture the biology of the interacting species making their predictions independent of time, place, and detection records, and fall under the ambit of time varying life tables (Gutierrez 1996). This bioeconomic modeling paradigm (Regev et al 1998) has a long history in assessing the geographic distribution and relative population dynamics of invasive species (Gutierrez and Baumgärtner 1984;e.g., Gutierrez 1996;Gutierrez and Ponti 2013a;Ponti et al 2021; see supplementary information).…”

The coffee agroecosystem: bio-economic analysis of coffee berry borer control (Hypothenemus hampei)

“…Econometric marginal analysis is best done with extensive field data 85 , but such data may be difficult to collect and is prohibitively expensive (e.g., coffee). However, simulation data generated by a well parameterized, fieldvalidated mechanistic models can provide a highly suitable alternative because the results can be compared to limited field data 86,87 . Our PBDM system developed to simulate the growth and development of coffee, the dynamics and infestation levels of coffee berry borer (CBB) and the action of four parasitoids of CBB is based on extensive data [21][22][23][24] and provide a very suitable platform for including the effects of cultural practices such as harvest (H), cleanup of abscised berries (CU) and the time intervals between these activities, and the effects of sprays of insecticide and of biopesticides of two fungal pathogens and two nematode parasites.…”