Applying a mechanistic model to predict interacting effects of chemical exposure and food availability on fish populations.

The potential environmental impacts of chemical exposures on wildlife are of growing concern. Freshwater ecosystems are vulnerable to chemical effects and wildlife populations, including fish, can be exposed to concentrations known to cause adverse effects at the individual level. Wild fish populations are also often subjected to numerous other stressors simultaneously which in temperate climates often include sustained periods of food limitation. The potential interactive effects of chemical exposures and food limitation on fish populations are however difficult to establish in the field. Mechanistic modelling approaches can be employed to help predict how the physiological effects of chemicals and food limitation on individuals may translate to population-level effects. Here an energy budget-individual-based model was developed and the control (no chemical) model was validated for the three-spined stickleback. Findings from two endocrine active chemical (EAC) case studies, (ethinyloestradiol and trenbolone) were then used to investigate how effects on individual fecundity translated into predicted population-level effects for environmentally relevant exposures. The cumulative effects of chemical exposure and food limitation were included in these analyses. Results show that effects of each EAC on the population were dependent on energy availability, and effects on population abundance were exacerbated by food limitation. Findings suggest that chemical effects and density dependent food competition interact to determine population responses to chemical exposures. Our study illustrates how mechanistic modelling approaches might usefully be applied to account for specific chemical effects, energy budgets and density-dependent competition, to provide a more integrated evaluation of population outcomes in chemical risk assessments.

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.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides.

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

Relationship between physicochemical properties and maximum residue levels and tolerances of crop-protection products for crops set by the USA, European Union and Codex.

Residues on foodstuffs resulting from the use of crop-protection products are a function of many factors, e.g. environmental conditions, dissipation and application rate, some of which are linked to the physicochemical properties of the active ingredients. Residue limits (maximum residue levels (MRLs) and tolerances) of fungicides, herbicides and insecticides set by different regulatory authorities are compared, and the relationship between physicochemical properties of the active ingredients and residue limits are explored. This was carried out using simple summary statistics and artificial neural networks. US tolerances tended to be higher than European Union MRLs. Generally, fungicides had the highest residue limits followed by insecticides and herbicides. Physicochemical properties (e.g. aromatic proportion, non-carbon proportion and water solubility) and crop type explained up to 50% of the variation in residue limits. This suggests that physicochemical properties of the active ingredients may control important aspects of the processes leading to residues.

Effect of homo-beta-proline and other heterocyclic GABA analogues on GABA uptake in neurons and astroglial cells and on GABA receptor binding.

Two groups of GABA (gamma-aminobutyric acid) analogues, one comprising derivatives of beta-proline and the other compounds structurally related to nipecotic acid, were investigated as potential inhibitors of high-affinity GABA transport in neurons and glial cells, as well as displacers of GABA receptor binding. In addition to cis-4-hydroxynipecotic acid, which is known as a potent inhibitor of GABA uptake, homo-beta-proline was the only compound which proved to be a potent inhibitor of glial as well as neuronal GABA uptake. IC50 values for GABA uptake into glial cells and brain cortex "prisms" were 20 and 75 micro M, respectively, and the IC50 value obtained for GABA uptake into cultured neurons was 10 micro M. A kinetic analysis of the action of homo-beta-proline on GABA uptake into cultured astrocytes and neurons showed that this compound acts as a competitive inhibitor of GABA uptake in both cell types. From the apparent Km values, Ki values for homo-beta-proline of 16 and 6 micro M could be calculated for glial and neuronal uptake, respectively. This mechanism of action strongly suggests that homo-beta-proline interacts with the GABA carriers. Furthermore, homo-beta-proline also displaced GABA from its receptor with an IC50 value of 0.3 micro M. The cis-4-hydroxynipecotic acid analogues, cis- and trans-4-mercaptonipecotic acid, had no inhibitory effect on glial or neuronal GABA uptake. Other SH reagents, PCMB, NEM and DTNB, were shown to be relatively weak inhibitors of GABA uptake into cultured astrocytes, suggesting that SH groups are not directly involved in the interaction between GABA and its transport carrier.