title: Modeling Green Peach Aphid populations exposed to elicitors inducing plant resistance on peach
Creators: name: Lanzoni, Alberto
name: Camastra, Francesco
name: Ciaramella, Angelo
name: Staiano, Antonino
name: Burgio, Giovanni
Publisher: name: Friedrich-Schiller-Universität Jena
Year: 2018
Subjects: subject: elicitors
subject: laminarin
subject: matrix population model
subject: genetic algorithm
subject: inverse problem
subject: 004
subject: 570
subject: 580
subject: 590
subject: 600
subject: 630

description: Matrix Population Models (MPMs) are not commonly used to simulate arthropod population dynamics with applications to pest control assessment in agricultural context. However, an increasing body of studies are prompting the finding of optimization techniques to reduce uncertainty in matrix parameters estimation. Indeed, uncertainty in parameters estimates may lead to significant management implications. Here we present a case study where MPMs are used for assessing the efficacy of treatment with elicitors inducing plant resistance against pathogen, such as laminarin, for the control of the Green Peach Aphid (Myzus persicae Sulzer) populations on peach. Such demographic approach could be particularly suitable to study this kind of compounds, which are mainly characterized by causing sub-lethal effects rather than acute mortality. An artificially assembled system [1] was arranged since it is well suited to follow the fate and behavior of a population exposed to elicitors activating chemical defense in plant. The obtained data, consisting of population time series, were used to generate a stage-classified projection matrix. The general model used to simulate population dynamics consists of a matrix containing i) survival probabilities (the probability of growing and moving to the next stage and the probability of surviving and remaining in the same stage), and ii) fecundities of the population. Most of the used methods for estimating the parameter values of stage-classified models rely on following cohorts of identified individuals [2]. However, in this study the observed data consisted of a time-series of population vectors where individuals are not distinguished. The relationship between the observed data and the values of the matrix parameters that produced the series involves an estimation process called inverse problem. Since all demographic analyses rely on how much the estimated parameters of the matrix are able to represent population dynamics, a Genetic algorithm for inverse parameter estimation was used in order to find a better model fit for the observed stage class distributions. These results were compared to those obtained by the quadratic programming method [3] used for determining the set of parameters that minimizes the residual between the collected data and the model output. REFERENCES: 1. Macfadyen, S., Banks, J.E., Stark, J.D., Davies, A.P., 2014. Using semifield studies to examine the effects of pesticides on mobile terrestrial invertebrates. Annu. Rev. Entomol. 59, 383-404. 2. Caswell, H., 2001. Matrix population models, second ed. Sinauer Associates Inc., Massachusetts. 3. Wood, S.N., 1994. Obtaining birth and mortality patterns from structured population trajectories. Ecol. Monogr. 64, 23-44.
description: ICEI 2018 : 10th International Conference on Ecological Informatics- Translating Ecological Data into Knowledge and Decisions in a Rapidly Changing World