A Spatio‐Temporal Exposure‐Hazard Model for Assessing Biological Risk and Impact

Abstract

We developed a simulation model for quantifying the spatio-temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio-temporal exposure-hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (biological risk assessment with R) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.

Extension of the spatially‐ and temporally‐explicit “briskaR‐NTL” model to assess potential adverse effects of Bt‐maize pollen on non‐target Lepidoptera at landscape level

“…The problem definition was described in the contract and we proposed a model formulation accordingly, based on the existing model briskaR for biological risk assessment (Walker et al, 2019).…”

“…The generic and flexible modeling framework that briskaR-NTL implements builds on the preexisting package briskaR, as defined in Walker et al (2019) and its supplementary material, and is made of four interacting compartments (Figure 1): 1. Landscape: a shapefile of sources (polygons of GM fields) and receptors (lines, points or polygons of host plant areas).…”

“…The spatial exposure-hazard model framework briskaR (biological risk assessment with R) (Leclerc et al 2018;Walker et al 2019, Baudrot et al 2020 enables to: (i) estimate NTL mortality at local/individual level as well as at landscape level; and (ii) assess whether risk mitigation scenarios can reduce the risk to an acceptable level. The framework has been used to evaluate the importance of considering spatially-explicit landscapes for assessing the impact of Bt-maize, and started developing a generic exposure-hazard model that would integrate the main factors driving the mortality of larvae of NTL.…”

Advances in Spatial Risk Analysis

“…Walker et al. () develop a spatiotemporal exposure‐hazard model, in which a dynamic model is built for quantifying the concentration of contaminants in space and time. The model is tested on a simulation study where the impact of genetically modified maize is assessed on nontargeted insects.…”

“…The results of this simulation include spatially explicit probabilistic estimates of subsidence magnitude and are used to create risk maps where areas with significant risk for subsidence are distinguished from low-risk areas. Walker et al (2019) develop a spatiotemporal exposure-hazard model, in which a dynamic model is built for quantifying the concentration of contaminants in space and time. The model is tested on a simulation study where the impact of genetically modified maize is assessed on nontargeted insects.…”