DEBtox theory and matrix population models as helpful tools in understanding the interaction between toxic cyanobacteria and zooplankton

Effect of dissolved organic matter on the bioavailability and toxicity of cadmium in zebrafish larvae: Determination based on toxicokinetic-toxicodynamic processes

The presence of dissolved organic matter (DOM) strongly influences the bioavailability of metals in aquatic environments; however, the association between the binding activities and the concentrations of DOM compositions is not well documented, leading to uncertainties in metal toxicity assessment. We creatively quantify the mitigation and acceleration effects of DOM compositions on cadmium (Cd) bioaccumulation and toxicity in zebrafish larvae using abiotic ligand (ABLs) and biotic ligand (BLs) in a toxicokinetic-toxicodynamic (TK-TD) model. The BL-TK-TD model could accurately predict the protective effect of fulvic acid while overestimating the complexing capacity of citric acid. The model also could successfully simulate the protective effects of native DOM in most cases from 32 natural water bodies in China. The observed LC50 values of Cd showed a peak effect for the native DOM fraction comprising hydrophilic acidic contents (3.55 ± 0.44 mg L ^- 1) in natural water from 32 sites. The BL-TK-TD model provides practically useful information to identify the effect of different DOM compositions on metal bioavailability and toxicity in aquatic environments and guides future water management policies aimed at controlling aquatic heavy metal pollution.

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Assessment of selenium toxicity on the life cycle of Caenorhabditis elegans

Selenium (Se) is a growing problem of global concern. Se can cause adverse effects on reproductive systems, which have been linked to declines in animal populations. The soil nematode Caenorhabditis elegans (C. elegans) is a ubiquitous soil organism that is increasingly utilized as a model organism in aquatic and soil toxicology. In the present study, the experimental data for individual body length, survival rate, brood size, and hatching rate were used to evaluate the possible effects of selenite [Se(IV)] on C. elegans. A stage-classified matrix model was applied to the experimental data to provide information on the population dynamics of C. elegans and to assess the Se(IV)-affected asymptotic population growth rate. Estimates of the survival probability showed significant decreases in survival at all stages when C. elegans was exposed to Se(IV). The growth probability of C. elegans in the L1 stage showed the most significant decline, from 0.11 h(-1) (for the control) to 0.04 h(-1) [for exposure to 3 mM Se(IV)]. These results showed that Se(IV) has a profound impact on C. elegans population dynamics. The asymptotic population growth rate (λ) was found to range from 1.00 to 0.64 h(-1) for increasing Se(IV) concentrations, implying a potential risk of population decrease for C. elegans exposure to a Se(IV)-contaminated environment. Our study shows how a mechanistic view based on the Se(IV) effects on the soil nematode C. elegans can promote a life cycle toxicity assessment. An important implication of this analysis is that mathematical models can be used to produce a population stage structure, to give clarity to the analysis of the key population-level endpoint (the asymptotic population growth rate) of population dynamics, and to evaluate the influences for the response of other species to environmental Se. These models sequentially provide candidate environmental criteria for the evaluation of the population impact of Se.

Microcystin accumulation in cladocerans: first evidence of MC uptake from aqueous extracts of a natural bloom sample

Bioaccumulation of microcystins (MC) in zooplankton has been shown in several studies, mainly in field samples. A few studies, however, have demonstrated MC bioaccumulation in laboratory experiments. Although ingestion of cell-bound MC is considered the main route of MC accumulation, another important source is the MC from the dissolved fraction (DMC). This study reports the accumulation of DMC from aqueous extracts of natural bloom samples in three cladoceran species: Moina micrura, Daphnia laevis and Daphnia similis. Animals were exposed for 96 h to aqueous extracts of lyophilized matter from two bloom samples from Colombian reservoirs in different concentrations (25-1000 mg DW L(-1)). Analysis by HPLC-MS detected MC-LR in these samples at concentrations of 434-538 μg g(-1). For the analysis of MC in animal tissues the samples were homogenized and sonicated in methanol:water (75%) and analyzed by ELISA. Results showed that the animals uptake of MC increased with increasing exposure concentrations of aqueous extracts, with M. micrura and D. laevis clones presenting the highest MC concentrations in their tissues (up to 1170-1260 μg g(-1)) while D. similis the lowest (184 μg g(-1)). This study shows, for the first time, that MC uptake from dissolved fraction by zooplankton is possible, not only from the ingestion of seston or cell-bound MC as previously demonstrated.

Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams

For the first time, we combine concepts of theoretical food web modeling, the metabolic theory of ecology, and ecological stoichiometry with the use of functional trait databases to predict the coexistence of invertebrate taxa in streams. We developed a mechanistic model that describes growth, death, and respiration of different taxa dependent on various environmental influence factors to estimate survival or extinction. Parameter and input uncertainty is propagated to model results. Such a model is needed to test our current quantitative understanding of ecosystem structure and function and to predict effects of anthropogenic impacts and restoration efforts. The model was tested using macroinvertebrate monitoring data from a catchment of the Swiss Plateau. Even without fitting model parameters, the model is able to represent key patterns of the coexistence structure of invertebrates at sites varying in external conditions (litter input, shading, water quality). This confirms the suitability of the model concept. More comprehensive testing and resulting model adaptations will further increase the predictive accuracy of the model.