The EFSA quantitative approach to pest risk assessment – methodological aspects and case studies

A new method for pest risk assessment and the identification and evaluation of risk‐reducing options is currently under development by the European Food Safety Authority (EFSA) Plant Health Panel. The draft method has been tested on pests of concern to the European Union (EU). The method is adaptable and can focus either on all the steps and sub‐steps of the assessment process or on specific parts if necessary. It is based on assessing changes in pest population abundance as the major driver of the impact on cultivated plants and on the environment. Like other pest risk assessment systems the method asks questions about the likelihood and magnitude of factors that contribute to risk. Responses can be based on data or expert judgment. Crucially, the approach is quantitative, and it captures uncertainty through the provision by risk assessors of quantile estimates of the probability distributions for the assessed variables and parameters. The assessment is based on comparisons between different scenarios, and the method integrates risk‐reducing options where they apply to a scenario, for example current regulation against a scenario where risk‐reducing options are not applied. A strategy has been developed to communicate the results of the risk assessment in a clear, comparable and transparent way, with the aim of providing the requestor of the risk assessment with a useful answer to the question(s) posed to the EFSA Plant Health Panel. The method has been applied to four case studies, two fungi, Ceratocystis platani and Cryphonectria parasitica, the nematode Ditylenchus destructor and the Grapevine flavescence dorée phytoplasma. Selected results from these case studies illustrate the types of output that the method can deliver.     

How does the Emerald Ash Borer (Agrilus planipennis) affect ecosystem services and biodiversity components in invaded areas?

Environmental risk assessment (ERA) is an important component of risk analysis for plant pests and invasive alien species (IAS), and a standardized and consistent methodology has recently been developed for evaluating their impact on ecosystem services and biodiversity. This paper presents the application of this innovative methodology for ERA to Agrilus planipennis, the emerald ash borer, which causes significant mortality to Fraxinus (ash) species in forests and urban areas of North America (here: USA and Canada, excluding Mexico) and Russia. The methodology follows a retrospective analysis and summarizes information and observations in invaded areas in North America and Russia. Uncertainty distributions were elicited to define quantitatively a general pattern of the environmental impact in terms of reduction in ecosystem provisioning, supporting and regulating services, and biodiversity components. The environmental impacts of A. planipennis are time‐ and context‐dependent, therefore two time horizons of 5 and 20 years after introduction and two ecosystems (urban and forest) were considered. This case study shows that the quantitative assessment of environmental impacts for IAS is both possible and helpful for decision‐makers and risk managers who have to balance control costs against potential impacts of IAS.     

Modelling diapause termination and phenology of the Japanese beetle,Popillia japonica

We deve?loped a mechanistic, stage-structured model simulating the phenology of Popillia japonica. The model simulates the influence of soil temperature on the larval diapause termination and on the development rate function of post-overwintering larvae and pupae. Model parameters are estimated based on literature evidence for pupae development and on a parameterisation process that allows estimating parameters for larval diapause termination and for the development rate function (and the related uncertainty) of post-overwintering larvae. Data used for model parameterisation and validation refer to time-series adult trap catches collected during the P. japonica monitoring programme performed by the Phytosanitary Service of Lombardy Region within the infested area in Lombardy (Italy) from 2015 to 2019. A total of 12 randomly selected locations are used to estimate biologically realistic model parameters (parameterisation dataset). We applied a Jackknife nonparametric resampling procedure on the parameterisation dataset to quantify uncertainty associated with parameters’ estimates. Parameterised model is then validated on time-series adult trap catches data referring to a different set of 12 randomly selected locations (validation dataset) surveyed in Lombardy. The model successfully predicted the beginning of adult emergence and the overall curve of adult emergence in the validation dataset. The model presented can support the definition of the best timing for the implementation of monitoring and control activities for the local and the area-wide management of P. japonica.

     

Physiologically based demographic models streamline identification and collection of data in evidence‐based pest risk assessment

The distribution and abundance of species that cause economic loss (i.e., pests) in crops, forests or livestock depends on many biotic and abiotic factors that are thought difficult to separate and quantify on geographical and temporal scales. However, the weather‐driven biology and dynamics of such species and of relevant interacting species in their food chain or web can be captured via mechanistic physiologically based demographic models (PBDMs). These models can be implemented in the context of a geographic information system (GIS) to predict the potential geographic distribution and relative abundance of pest species given observed or climate change scenarios of weather. PBDMs may include bottom‐up effects of the host on pest dynamics and, if appropriate, the top‐down action of natural enemies. When driven by weather, PBDMs predict the phenology, age structure and abundance dynamics at one or many locations enabling the distribution of the interacting species to be predicted across wide geographic areas. PBDMs are able to capture relevant ecosystem complexity within a modest number of measurable parameters because they use the same ecological models of analogous resource acquisition and allocation processes across all trophic levels. The use of these analogies makes parameter estimation easier as the underlying functions are known. This is a significant advantage in cases where the biological data available to build an evidence base for pest risk assessment is sparse.