Systemic risks of genetically modified crops: the need for new approaches to risk assessment

Background

European chemicals legislation (registration, evaluation, authorisation and restriction of chemical substances (REACH)) requires a broad assessment of chemicals with respect to, inter alia, their health-relevant properties. Due to the extreme number of substances to be assessed and the limited current toxicological knowledge on their respective properties, REACH implicitly requires a paradigm change: away from knowledge generated mainly from costly animal experiments towards the use of mechanistic findings. Moreover, effect mechanisms at the biochemical or cellular level are essential when conclusions shall be drawn about "new" endpoints and mixtures of xenobiotics. This study (funded by the German Federal Environment Agency) describes examples of biochemical processes in the mammalian organism and how xenobiotics interfere with them. Interference with physiological processes expected to lead to adverse health effects is characterised as "toxicity pathway". The study describes toxicological endpoints not usually covered in routine animal testing and the respective toxicity pathways.

Results and conclusions

Screening for chemicals which exert effects via common toxicity pathways and subsequently conducting targeted short-term tests may generate new information about the toxicity of chemicals without performing extensive substance-by-substance animal experiments. Information on common toxicity pathways may also provide input for the assessment of mixture effects. The U.S. Environmental Protection Agency is working intensely on this concept. It involves the use of enormous amounts of data on relevant biochemical and cellular processes, which are generated by "high-throughput screening" methods, and then are combined with substance-specific kinetic data, experimental apical test outcomes and modelling. Current limitations in the regulatory use of this integrated approach on risk assessment will be outlined.     

Multi-risk,multi-scale and multi-stakeholder – the contribution of a bow-tie analysis for risk management in the trilateral Wadden Sea Region

Risk management processes increasingly call for enhanced stakeholder participation, and aim to integrate different risk perceptions, concerns and interests. Frequently, this goal is driven by the increased complexity of risk management processes, as risk management processes continuously have to deal with multi-risk situations including impacts resulting from risks of natural hazards and risks caused by misguided social or economic development. Although stakeholder participation is required by different policies, major challenges still arise from the question of how to perform multi-stakeholder participation in practice. In order to find answers, we tested the so-called ‘bow-tie analysis’ as a potential tool to facilitate multi-stakeholder participation with a major effort on integrating stakeholders risk perceptions and interest in the risk management processes. The bow-tie analysis is a commonly used risk assessment technique (IEC 2009) to analyse cause-and-effect pathways of risks, but its application in multi-stakeholder processes in risk management of natural hazards, especially in a European context, is rather new. Using practical experiences from the trilateral Wadden Sea Region we demonstrate the bow-tie analysis’ contribution to coastal risk management processes in this coastal area by facilitating collaborative identification, comprehension and analysis of the management system. The use of a modified bow-tie analysis in collaboration with stakeholders from the Wadden Sea Region proved to be an appropriate framework for enhancing the understanding of risk management processes and fostered disclosure of different perceptions and concerns of multi-risk problematics. The bow-tie can be beneficial as a communication and co-construction tool in risk management processes in a multi-risk context.     

Hormonaktive Xenobiotika

Developmental and reproductive processes are most sensitive to the toxic effects of environmental chemicals. Especially alarming is the fact that many groups of industrial chemicals and pesticides are capable of disrupting the endocrine system in man and animals. Of great concern is the reduction in the sperm count in Europe, but also the worldwide increase in a great number of reproductive and developmental disturbances observed in both man and wildlife. A correlation to a high chemical burden has been demonstrated for many different animal species as well as for women. An important consideration in assessing the potential effects of environmental chemicals on the endocrine system is the time at which such an exposure occurs. In the adult organism, hormones initiate functional processes; these effects are usually transient. In early life, hormones control developmental processes and are capable of producing permanent changes in organ structure and function (organizational effects). Therefore, chemical disruption of hormonal functions during development can result in permanent functional changes of the afflicted organ.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

The power of simulating experiments

Addressing complex ecological research questions often requires complex empirical experiments. However, due to the logistic constraints of empirical studies there is a trade-off between the complexity of experimental designs and sample size. Here, we explore if the simulation of complex ecological experiments including stochasticity-induced variation can aid in alleviating the sample size limitation of empirical studies. One area where sample size limitations constrain empirical approaches is in studies of the above- and belowground controls of trophic structure. Based on a rule- and individual-based simulation model on the effect of above- and belowground herbivores and their enemies on plant biomass, we evaluate the reliability of biomass estimates, the probability of experimental failure in terms of missing values, and the statistical power of biomass comparisons for a range of sample sizes. As expected, we observed superior performance of setups with sample sizes typical of simulations (n = 1000) as compared to empirical experiments (n = 10). At low sample sizes, simulated standard errors were smaller than expected from statistical theory, indicating that stochastic simulation models may be required in those cases where it is not possible to perform pilot studies for determining sample sizes. To avoid experimental failure, a sample size of n = 30 was required. In conclusion, we propose that the standard tool box of any ecologist should comprise a combination of simulation and empirical approaches to benefit from the realism of empirical experiments as well as the statistical power of simulations.     

Decision-support tools for dynamic management

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.     

A controversy re-visited: Is the coccinellid Adalia bipunctata adversely affected by Bt toxins?

Background

The Cefic Mixtures Industry Ad-hoc Team (MIAT) has investigated how risks from combined exposures can be effectively identified and managed using concepts proposed in recent regulatory guidance, new advances in risk assessment, and lessons learned from a Cefic-sponsored case study of mixture exposures.

Results

A series of tools were created that include: a decision tree, a system for grouping exposures, and a graphical tool (the MCR-HI plot). The decision tree allows the division of combined exposures into different groups, exposures where one or more individual components are a concern, exposures that are of low concern, and exposures that are a concern for combined effects but not for the effects of individual chemicals. These tools efficiently use available data, identify critical data gaps for combined assessments, and prioritize which chemicals require detailed toxicity information. The tools can be used to address multiple human health endpoints and ecological effects.

Conclusion

The tools provide a useful approach for assessing risks associated with combined exposures to multiple chemicals.     

Modelling cadmium bioaccumulation in Gammarus pulex by using experimental design approach

Recently, although dynamic approaches have been used increasingly to describe metal bioaccumulation in aquatic organisms, the validation of such laboratory-derived modelling is rarely assessed under environmental conditions. The present study aims to evaluate and verify statistical and mathematical models for the bioaccumulation of cadmium (Cd) and to evaluate the suitability of Gammarus pulex as a biomonitor for Cd. To optimise Cd²⁺ ion bioaccumulation conditions a Box–Behnken design was used and whether G. pulex can be used as an estimated tool to assess aquatic quality was investigated. A Box–Behnken experimental design combined with response surface modelling (RSM) was employed for Cd²⁺ bioaccumulation in G. pulex. Independent variables including temperature, contact time and Cd²⁺ ion concentration significance and their interactions were tested using analysis of variance. The selected variables’ optimum values were obtained by solving the quadratic regression model along with by analysing the response surface contour plots. Based on Box–Behnken design, the applied model is significant because model F-value and R² were obtained as 5121.49, 0.9998, respectively. Bioaccumulation of Cd amount was analysed using electrothermal atomic absorption spectrophotometer. The obtained data suggest that G. pulex can be evaluated as Cd biomonitor.     

Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay

Ecosystem components interact in complex ways and change over time due to a variety of both internal and external influences (climate change, season cycles, human impacts). Such processes need to be modeled dynamically using appropriate statistical methods for assessing change in network structure. Here we use visualizations and statistical models of network dynamics to understand seasonal changes in the trophic network model described by Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] for the Chesapeake Bay (USA). Visualizations of carbon flow networks were created for each season by using a network graphic analysis tool (NETDRAW). The structural relations of the pelagic and benthic compartments (nodes) in each seasonal network were displayed in a two-dimensional space using spring-embedder analyses with nodes color-coded for habitat associations (benthic or pelagic). The most complex network was summer, when pelagic species such as sea nettles, larval fishes, and carnivorous fishes immigrate into Chesapeake Bay and consume prey largely from the plankton and to some extent the benthos. Winter was the simplest of the seasonal networks, and exhibited the highest ascendency, with fewest nodes present and with most of the flows shifting to the benthic bacteria and sediment POC compartments. This shift in system complexity corresponds with a shift from a pelagic- to benthic-dominated system over the seasonal cycle, suggesting that winter is a mostly closed system, relying on internal cycling rather than external input. Network visualization tools are useful in assessing temporal and spatial changes in food web networks, which can be explored for patterns that can be tested using statistical approaches. A simulation-based continuous-time Markov Chain model called SIENA was used to determine the dynamic structural changes in the trophic network across phases of the annual cycle in a statistical as opposed to a visual assessment. There was a significant decrease in outdegree (prey nodes with reduced link density) and an increase in the number of transitive triples (a triad in which i chooses j and h, and j also chooses h, mostly connected via the non-living detritus nodes in position i), suggesting the Chesapeake Bay is a simpler, but structurally more efficient, ecosystem in the winter than in the summer. As in the visual analysis, this shift in system complexity corresponds with a shift from a pelagic to a more benthic-dominated system from summer to winter. Both the SIENA model and the visualization in NETDRAW support the conclusions of Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] that there was an increase in the Chesapeake Bay ecosystem's ascendancy in the winter. We explain such reduced complexity in winter as a system response to lowered temperature and decreased solar energy input, which causes a decline in the production of new carbon, forcing nodes to go extinct; this causes a change in the structure of the system, making it simpler and more efficient than in summer. It appears that the seasonal dynamics of the trophic structure of Chesapeake Bay can be modeled effectively using the SIENA statistical model for network change.     

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species’ populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.     

A review on environmental distributions and risk management of phenols pertaining to the endocrine disrupting chemicals in Taiwan

Some phenols, including pentachlorophenol, dichlorophenol, alkylphenols (nonylphenol & octylphenol) and bisphenol-A, have been identified as endocrine disrupting chemicals (EDCs). These phenolic EDCs are extensively used in a wide range of household products, thus posing potential health risks for humans exposed to them. From the viewpoints of ecotoxicology, human health and regulations, it is urgent to restrict the emissions and releases of these estrogenic chemicals from the industrial processes and commercial products. This review article first focused on the physicochemical properties of phenolic EDCs and their industrial/commercial uses. Furthermore, their environmental distributions and regulatory frameworks for integrated risk management of these chemicals in Taiwan were conducted as a case study. Emphasis was thus put on the cross-ministerial joint venture (i.e., environment, health, agriculture, labor, and industry authorities), and the government policy on the risk management of EDCs. Finally, some recommendations for pollution prevention and toxicity reduction of phenolic EDCs were also addressed and analyzed to progress towards a sustainable society in Taiwan.     

Degradation of chemical alarm cues under natural conditions: risk assessment by larval woodfrogs

Summary. Many aquatic species use chemosensory information to assess predation risk. The cues used in such risk assessment can come either from the predator (predator odour) or from injured prey (alarm cues). The information conveyed through chemicals may, however, be inaccurate both spatially and temporally, as chemicals may persist in the environment long after the predator is gone. Thus, the level of accuracy of the cues for risk assessment may depend on the persistency of the chemicals in the habitat. Here, we investigated the persistency of alarm cues of a larval amphibian, the woodfrog (Rana sylvatica) in a ephemeral pond, their natural habitat. We introduced either alarm cues or control water in enclosed sleeves (~10 L) installed in the pond. The sleeve water was then sampled after 5 min and every two hours for eight hours. We used the behavioural response of woodfrog tadpoles to alarm cues as a bioassay to assess how long the alarm cues persisted in the environment. We found that tadpoles responded with an antipredator response to the pond water containing alarm cues 5 min after the injection of the cues in the sleeves but did not respond to that same pond water after two hours. Our results indicate that biodegradation and/or photodegradation of alarm cues in natural habitats might occur relatively quickly as the loss of a response to the cues in our experiment was independent of a dilution effect. This contrasts with previous laboratory results indicating that chemicals may be active after several hours.     

Promoting the use of BaP as a marker for PAH exposure in UK soils

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that frequently accumulate in soils. There is therefore a requirement to determine their levels in contaminated environments for the purposes of determining impacts on human health. PAHs are a suite of individual chemicals, and there is an ongoing debate as to the most appropriate method for assessing the risk to humans from them. Two methods predominate: the surrogate marker approach and the toxic equivalency factor. The former assumes that all chemicals in a mixture have an equivalent toxicity. The toxic equivalency approach estimates the potency of individual chemicals relative to the usually most toxic Benzo(a)pyrene. The surrogate marker approach is believed to overestimate risk and the toxic equivalency factor to underestimate risk. When analysing the risks from soils, the surrogate marker approach is preferred due to its simplicity, but there are concerns because of the potential diversity of the PAH profile across the range of impacted soils. Using two independent data sets containing soils from 274 sites across a diverse range of locations, statistical analysis was undertaken to determine the differences in the composition of carcinogenic PAH between site locations, for example, rural versus industrial. Following principal components analysis, distinct population differences were not seen between site locations in spite of large differences in the total PAH burden between individual sites. Using all data, highly significant correlations were seen between BaP and other carcinogenic PAH with the majority of r ² values > 0.8. Correlations with the European Food Standards Agency (EFSA) summed groups, that is, EFSA2, EFSA4 and EFSA8 had even higher correlations (r ² > 0.95). We therefore conclude that BaP is a suitable surrogate marker to represent mixtures of PAH in soil during risk assessments.     

基于umu遗传毒性效应的饮用水致癌风险评价的尝试

化学物质暴露是导致癌症发生的重要诱因,通过饮用水暴露导致的人类致癌风险在饮用水处理技术中日益引起重视.由于水中化学物质种类繁多、组成复杂,准确地检测每个致癌物质的浓度和毒性非常困难.为了控制饮用水的安全,根据DNA损伤诱导SOS反应而表达umuC基因这一基本原理建立的SOS/umu测试法,已经广泛应用于饮用水遗传毒性的检测.论文建立了基于umu遗传毒性效应的饮用水致癌风险评价方法,并对北方某水厂饮用水的遗传毒性进行了umu测试,计算了该地区饮用水的致癌风险,提出了可能的饮用水遗传毒性基准值.结果表明,该水厂常规工艺出水的致癌风险均值为1.55×10-6,存在一定的安全隐患;而深度处理工艺能有效地削减出水致癌风险均值至5.3×10-7,达到目前先进国家水质管理的要求,保障了饮用水的安全.样品中4-硝基喹啉-1-氧化物(4-NQO)的等当量浓度(TEQ4-NQO)0.0948μg·L-1可作为饮用水遗传毒性基准值。     

Phenotypic variations in the gills of the symbiont-containing bivalve Lucinoma aequizonata

The marine bivalve Lucinoma aequizonata (Lucinidae) maintains a population of sulfide-oxidizing chemoautotrophic bacteria in its gill tissue. These are housed in large numbers intracellularly in specialized host cells, termed bacteriocytes. In a natural population of L. aequizonata, striking variations of the gill colors occur, ranging from yellow to grey, brown and black. The aim of the present study was to investigate how this phenomenon relates to the physiology and numbers of the symbiont population. Our results show that in aquarium-maintained animals, black gills contained fewer numbers of bacteria as well as lower concentrations of sulfur and total protein. Nitrate respiration was stimulated by sulfide (but not by thiosulfate) 33-fold in homogenates of black gills and threefold in yellow gill homogenates. The total rates of sulfide-stimulated nitrate respiration were the same. Oxygen respiration could be measured in animals with yellow gills but not in animals with black gills. The cumulative data suggest that black-gilled clams maintained in the aquarium represent a starvation state. When collected from their natural habitat black gills contain the same number of bacteria as yellow gills. Also, no significant difference in glycogen concentrations of the host tissues was observed. Therefore, starvation is unlikely the cause of black gill color in a natural population. Alternative sources of nutrition to sulfur-based metabolism are discussed. Denaturing gradient gel electrophoresis (DGGE) performed on the different gill tissues, as well as on isolated symbionts, resulted in a single gill symbiont amplification product, the sequence of which is identical to published data. These findings provide molecular evidence that one dominant phylotype is present in the morphologically different gill tissues. Nevertheless, the presence of other phylotypes cannot formally be excluded. The implications of this study are that the gill of L. aequizonata is a highly dynamic organ which lends itself to more detailed studies regarding the molecular and cellular processes underlying nutrient transfer, regulation of bacterial numbers and host–symbiont communication. Received: 1 September 1999 / Accepted: 1 February 2000     

An integrated look at decision-making in bees as they abandon a depleted food source

While there has been considerable research on the behavioral processes that underlie animals’ ability respond to shifting rewards, it remains unclear how animals coordinate multiple processes over time. To investigate this, we compared the behavior of honeybees (Apis mellifera) and bumblebees (Bombus impatiens), in an open-ended search task. Bees were given brief access to a high-quality food source, which then became non-rewarding. Then, over an extended period, we examined (1) bees’ tendency to persist at the depleted site, (2) their tendency to return to a different low-quality food source where they had been foraging previously, (3) their tendency to return to the hive, and (4) how previous reward history influenced their tendency to shift among these options. Compared to bumblebees, honeybees were much slower to abandon the depleted site and were much more likely to make trips to the hive while bumblebees were much more likely to return to the familiar low-quality site. These observed species differences are interpreted in terms of evolved individual and social differences between these species. We show evidence of well-studied behavioral processes such as extinction, negative contrast effects, and reliance on a social group, and provide, for the first time, a picture of how these processes interact with one another as part of a common sequential decision-making process.     

Comparative in vitro metabolism of chloroxylenol,chlorophene, and triclosan with rat,mouse, and human hepatic microsomes

A number of studies have reported the presence of chlorinated phenols, commonly used as antiseptics, in the environment. Chloroxylenol, chlorophene, and triclosan are three such chemicals believed to have leached into water supplies through the wastewater treatment facilities. Understanding how these compounds are metabolized is important in determining the risks of chemical exposure. In this study, we compared the in vitro metabolism of these three chlorinated phenols with rat, mouse, and human liver microsomes. The structures of the metabolites formed during the microsomal reactions were identical when rat, mouse, and human liver extracts were used, but variations existed in the kinetics of the reactions.     

Detecting Lévy walks without turn designation

Many organisms have been reported to have movement patterns that are well approximated as Lévy walks. This is typically because distributions of straight line distances between consecutive significant turns in movement paths have heavy power law tails. This diagnostic tool has been called into question because there is currently no standard, unambiguous way to identify significant turns. Even if such a way could be found, statistical analyses based on significant turns cannot account for actual movements made between turns and as a consequence cannot distinguish between true Lévy walks and other fractal random walks such as Lévy modulated correlated random walks where organisms randomly meander rather than move in straight lines between consecutive reorientation events. Here, I show that structure functions (i.e. moments of net displacements made across fixed time intervals) can distinguish between different kinds of Lévy walks and between Lévy walks and random walks with a few scales such as composite correlated random walks and correlated random walks. Distinguishing between these processes will lead to a better understanding of how and why animals perform Lévy walks and help bridge the apparent divide between correlated random walks and Lévy walks. Structure functions do not require turn identification and instead take account of entire movement paths. Using this diagnostic tool, I bolster previous claims that honeybees use a movement strategy that can be approximated by Lévy walks when searching for their hive. I also show how structure functions can be used to establish the extent of self-similar behaviour in meandering Lévy walks.     

An ecological framework for contextualizing carnivore–livestock conflict

Carnivore predation on livestock is a complex management and policy challenge, yet it is also intrinsically an ecological interaction between predators and prey. Human–wildlife interactions occur in socioecological systems in which human and environmental processes are closely linked. However, underlying human–wildlife conflict and key to unpacking its complexity are concrete and identifiable ecological mechanisms that lead to predation events. To better understand how ecological theory accords with interactions between wild predators and domestic prey, we developed a framework to describe ecological drivers of predation on livestock. We based this framework on foundational ecological theory and current research on interactions between predators and domestic prey. We used this framework to examine ecological mechanisms (e.g., density-mediated effects, behaviorally mediated effects, and optimal foraging theory) through which specific management interventions operate, and we analyzed the ecological determinants of failure and success of management interventions in 3 case studies: snow leopards (Panthera uncia), wolves (Canis lupus), and cougars (Puma concolor). The varied, context-dependent successes and failures of the management interventions in these case studies demonstrated the utility of using an ecological framework to ground research and management of carnivore–livestock conflict. Mitigation of human–wildlife conflict appears to require an understanding of how fundamental ecological theories work within domestic predator–prey systems.