Abstract
The western corn rootworm is an invasive species to Europe and is a major agricultural pest that causes widespread economic and yield losses to maize producers. The Gompertz curve was originally used to model human population mortality. It is a sigmoidal curve where the beginning and end of a period shows the slowest time for growth, and adequately describes observed dynamics of many phenomena. We propose the use of the Gompertz function in a Bayesian Hierarchical framework to model the emergence dynamics of the western corn rootworm beetle. The proposed model includes the use of climatic variables to assess how weather can influence the observed dynamics. We apply the model to Austrian monitoring data collected in 2004–2015.
Highlights
The western corn rootworm is an invasive species to Europe and is a major agricultural pest that causes widespread economic and yield losses to maize producers
We investigated the effect of climate covariates such as temperature and precipitation on the Western Corn Rootworm (WCR) beetle emergence dynamics
It was of interest to see how climate variables such as temperature and precipitation as well as the maize production intensity affected the observed emergence dynamics
Summary
The western corn rootworm is an invasive species to Europe and is a major agricultural pest that causes widespread economic and yield losses to maize producers. Climate change and globalisation, i.e. global trade and transport of agricultural products, are among the most important drivers for the spread of invasive species and their introduction to new environments[1,2]. One such an invasive species is the Western Corn Rootworm (WCR; Diabrotica virgifera virgifera) beetle, a univoltine (one generation per growing season) leaf beetle, which is known to cause massive crop yield losses to Zea mays maize crops[3,4]. Emergence dynamics of the WCR beetle can be described with sufficient accuracy by a parametric curve, such as, for example, the Gompertz curve
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