Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum.

This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species.

Case Study Part 2: Probabilistic modelling of long-term effects of pesticides on individual breeding success in birds and mammals.

Long term exposure of skylarks to a fictitious insecticide and of wood mice to a fictitious fungicide were modelled probabilistically in a Monte Carlo simulation. Within the same simulation the consequences of exposure to pesticides on reproductive success were modelled using the toxicity-exposure-linking rules developed by R.S. Bennet et al. (2005) and the interspecies extrapolation factors suggested by R. Luttik et al. (2005). We built models to reflect a range of scenarios and as a result were able to show how exposure to pesticide might alter the number of individuals engaged in any given phase of the breeding cycle at any given time and predict the numbers of new adults at the season's end.

Case Study Part 1: How to calculate appropriate deterministic long-term toxicity to exposure ratios (TERs) for birds and mammals.

In the European Union, first-tier assessment of the long-term risk to birds and mammals from pesticides is based on calculation of a deterministic long-term toxicity/exposure ratio (TER(lt)). The ratio is developed from generic herbivores and insectivores and applied to all species. This paper describes two case studies that implement proposed improvements to the way long-term risk is assessed. These refined methods require calculation of a TER for each of five identified phases of reproduction (phase-specific TERs) and use of adjusted No Observed Effect Levels (NOELs) to incorporate variation in species sensitivity to pesticides. They also involve progressive refinement of the exposure estimate so that it applies to particular species, rather than generic indicators, and relates spraying date to onset of reproduction. The effect of using these new methods on the assessment of risk is described. Each refinement did not necessarily alter the calculated TER value in a way that was either predictable or consistent across both case studies. However, use of adjusted NOELs always reduced TERs, and relating spraying date to onset of reproduction increased most phase-specific TERs. The case studies suggested that the current first-tier TER(lt )assessment may underestimate risk in some circumstances and that phase-specific assessments can help identify appropriate risk-reduction measures. The way in which deterministic phase-specific assessments can currently be implemented to enhance first-tier assessment is outlined.

Intake estimation of polychlorinated dibenzo-p-dioxins, dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) in salmon: the inclusion of uncertainty.

Dioxins and dioxin-like PCBs are given toxic equivalency factors (TEFs) in order to calculate the combined toxic equivalence (TEQ) of these contaminants in a sample of food. This study calculates the probability of an average consumer exceeding the recommended tolerable daily intake of 1-4 pg WHO-TEQ kg(-1) bw day(-1) as the amount of salmon in the diet is increased. Probabilistic risk analysis is used to account for the known uncertainties in this calculation. When the TEF uncertainty was excluded with no salmon consumption, the background dietary intake ranged from 1.36 to 1.78 pg TEQ kg(-1) bw day(-1). A weekly consumption of three standard salmon portions resulted in a 36% chance of exceeding the upper limit of the TDI. Inclusion of the TEF uncertainty increased the background dietary intake range from 2.1 to 4.4 pg TEQ kg(-1) bw day(-1), and the weekly consumption of one salmon portion resulted in a 79% chance of the average consumer exceeding the upper TDI. The most important factors contributing to the uncertainty in these results were, in order of magnitude, the TEF for PCB 126 and the sampling uncertainty (sample size) followed by the measurement uncertainty of PCB 126. We recommend that it is more important to increase sample size and produce more precise estimates in the TEF than to improve analytical accuracy.