Christopher M. Holmes

AGRICULTURAL INTENSITY AND LANDSCAPE STRUCTURE: INFLUENCES ON THE MACROINVERTEBRATE ASSEMBLAGES OF SMALL STREAMS IN NORTHERN GERMANY

The present study aimed to relate aquatic macroinvertebrate community composition to agricultural intensity and landscape structure. A total of 360 streams were investigated within the Aller river basin in northern Germany. The study area is typical of central German arable agricultural regions, but the small streams were of low dilution potential. These streams were characterized for abiotic parameters (including modeled potential for diffuse inputs from agricultural sources) and macroinvertebrate communities, with data collected over a 17-year period. Spray drift potential did not correlate with community composition. In contrast, the relative index of runoff potential (RP) was negatively correlated with various measures of taxonomic richness and abundance. Community composition also was correlated with environmental parameters, including stream width, clay content of sediment, and presence of dead wood in sediment. The abundance of sensitive species decreased significantly during the main period of agrochemical use at sites of high RP but completely recovered by the following spring. Long-term decreased taxonomic richness and a shift to ecologically robust species also were observed at sites of high RP. The results suggest that long-term alterations in community measures probably were associated with factors related to runoff input. Nevertheless, the community composition remained reasonably rich and even. Landscape structure also appeared to influence community structure. Abundance of sensitive species remained significantly enhanced, even at sites of high RP, when forested reaches were present in upstream reaches. These probably provided a source of organisms for downstream recolonization and amelioration of effects at high RP.

Eco-epidemiology of aquatic ecosystems: Separating chemicals from multiple stressors

A non-toxic environment and a good ecological status are policy goals guiding research and management of chemicals and surface water systems in Europe and elsewhere. Research and policies on chemicals and water are however still disparate and unable to evaluate the relative ecological impacts of chemical mixtures and other stressors. This paper defines and explores the use of eco-epidemiological analysis of surveillance monitoring data sets via a proxy to quantify mixture impacts on ecosystems. Case studies show examples of different, progressive steps that are possible. Case study data were obtained for various regions in Europe and the United States. Data types relate to potential stressors at various scales, concerning landscape, land-use, in-stream physico-chemical and pollutant data, and data on fish and invertebrates. The proxy-values for mixture impacts were quantified as predicted (multi-substance) Potentially Affected Fractions of species (msPAF), using Species Sensitivity Distribution (SSD) models in conjunction with bioavailability and mixture models. The case studies summarize the monitoring data sets and the subsequent diagnostic bioassessments. Variation in mixture toxic pressures amongst sites appeared to covary with abundance changes in large (50-86%) percentages of taxa for the various study regions. This shows that an increased mixture toxic pressure (msPAF) relates to increased ecological impacts. Subsequent multi-stressor evaluations resulted in statistically significant, site-specific diagnosis of the magnitudes of ecological impacts and the relative contributions of different stress factors to those impacts. This included both mixtures and individual chemicals. These results allow for ranking stressors, sites and impacted species groups. That is relevant information for water management. The case studies are discussed in relation to policy and management strategies that support reaching a non-toxic environment and good ecological status. Reaching these goals requires not only focused sectoral policies, such as on chemical- or water management, but also an overarching and solution-focused view.

Developing a foundation for eco‐epidemiological assessment of aquatic ecological status over large geographic regions utilizing existing data resources and models

Eco-epidemiological studies utilizing existing monitoring program data provide a cost-effective means to bridge the gap between the ecological status and chemical status of watersheds and to develop hypotheses of stressor attribution that can influence the design of higher-tier assessments and subsequent management. The present study describes the process of combining existing data and models to develop a robust starting point for eco-epidemiological analyses of watersheds over large geographic scales. Data resources from multiple federal and local agencies representing a range of biological, chemical, physical, toxicological, and other landscape factors across the state of Ohio, USA (2000-2007), were integrated with the National Hydrography Dataset Plus hydrologic model (US Environmental Protection Agency and US Geological Survey). A variety of variable reduction, selection, and optimization strategies were applied to develop eco-epidemiological data sets for fish and macroinvertebrate communities. The relative importance of landscape variables was compared across spatial scales (local catchment, watershed, near-stream) using conditional inference forests to determine the scales most relevant to variation in biological community condition. Conditional inference forest analysis applied to a holistic set of environmental variables yielded stressor-response hypotheses at the statewide and eco-regional levels. The analysis confirmed the dominant influence of state-level stressors such as physical habitat condition, while highlighting differences in predictive strength of other stressors based on ecoregional and land-use characteristics. This exercise lays the groundwork for subsequent work designed to move closer to causal inference.

How does crop type influence risk from pesticides to the aquatic environment

National-level risk mapping was undertaken to identify specific situations within England with the greatest potential for impacts on aquatic biodiversity from normal agricultural use of pesticides. Calculations of exposure via spray drift and drainflow were differentiated by landscape type, region, and crop and then compared with toxicity to the indicator organisms Daphnia magna and algae. The approach incorporated regional-level information regarding pesticide usage derived from farm visits. Risk was calculated for individual water bodies and then aggregated and mapped for each of 5,760 individual catchments ranging in area up to 248 km2. Type of crop adjacent to water was the major driver for risk, and orchards were identified as the crop associated with the greatest potential risk to the aquatic environment. Crops such as cereals, oilseeds, and potatoes are more widely grown in England but have potential risk an order of magnitude smaller than that for orchards. Several of the pesticides that contribute most to risk have been withdrawn from use since collection of the most recent usage data. Driven by crop distribution, surface waters adjacent to orchards in the midwest and southeast of England are predicted to be most at risk of ecological impacts from agricultural pesticide use. This information can be used in targeting monitoring campaigns designed to protect the aquatic environment.

Prospective aquatic risk assessment for chemical mixtures in agricultural landscapes

Abstract Environmental risk assessment of chemical mixtures is challenging because of the multitude of possible combinations that may occur. Aquatic risk from chemical mixtures in an agricultural landscape was evaluated prospectively in 2 exposure scenario case studies: at field scale for a program of 13 plant‐protection products applied annually for 20 yr and at a watershed scale for a mixed land‐use scenario over 30 yr with 12 plant‐protection products and 2 veterinary pharmaceuticals used for beef cattle. Risk quotients were calculated from regulatory exposure models with typical real‐world use patterns and regulatory acceptable concentrations for individual chemicals. The results could differentiate situations when there was concern associated with single chemicals from those when concern was associated with a mixture (based on concentration addition) with no single chemical triggering concern. Potential mixture risk was identified on 0.02 to 7.07% of the total days modeled, depending on the scenario, the taxa, and whether considering acute or chronic risk. Taxa at risk were influenced by receiving water body characteristics along with chemical use profiles and associated properties. The present study demonstrates that a scenario‐based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. Environ Toxicol Chem 2018;37:674–689.

Prospective mixture risk assessment and management prioritizations for river catchments with diverse land uses

Abstract Ecological risk assessment increasingly focuses on risks from chemical mixtures and multiple stressors because ecosystems are commonly exposed to a plethora of contaminants and nonchemical stressors. To simplify the task of assessing potential mixture effects, we explored 3 land use–related chemical emission scenarios. We applied a tiered methodology to judge the implications of the emissions of chemicals from agricultural practices, domestic discharges, and urban runoff in a quantitative model. The results showed land use–dependent mixture exposures, clearly discriminating downstream effects of land uses, with unique chemical “signatures” regarding composition, concentration, and temporal patterns. Associated risks were characterized in relation to the land‐use scenarios. Comparisons to measured environmental concentrations and predicted impacts showed relatively good similarity. The results suggest that the land uses imply exceedances of regulatory protective environmental quality standards, varying over time in relation to rain events and associated flow and dilution variation. Higher‐tier analyses using ecotoxicological effect criteria confirmed that species assemblages may be affected by exposures exceeding no‐effect levels and that mixture exposure could be associated with predicted species loss under certain situations. The model outcomes can inform various types of prioritization to support risk management, including a ranking across land uses as a whole, a ranking on characteristics of exposure times and frequencies, and various rankings of the relative role of individual chemicals. Though all results are based on in silico assessments, the prospective land use–based approach applied in the present study yields useful insights for simplifying and assessing potential ecological risks of chemical mixtures and can therefore be useful for catchment‐management decisions. Environ Toxicol Chem 2018;37:715–728.