Toward harmonizing ecotoxicity characterization in life cycle impact assessment.

Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems on a global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted by the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modeling chemical exposure of organisms and the resulting ecotoxicological effects for use in LCIA. The outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice of exposure and effect modeling in ecotoxicity characterization. These changes will reflect the current science and ensure the stability of recommended practice. Recommendations must work within the needs of LCIA in terms of 1) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, 2) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and 3) yielding results that are additive across substances and life cycle stages and that will allow a quantitative expression of damage to the exposed ecosystem. We describe the current framework and discuss research questions identified in a roadmap. Primary research questions relate to the approach toward ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, we give metals a special focus, including consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. Environ Toxicol Chem 2018;37:2955-2971. © 2018 SETAC.

The microbiome of Folsomia candida: an assessment of bacterial diversity in a Wolbachia-containing animal.

The springtail Folsomia candida is an important model organism for soil ecology, ecotoxicology and ecogenomics. The decomposer activities of soil invertebrates like Folsomia depend on their relationship with microbial communities including gut symbionts. In this paper, we apply high-throughput sequencing to provide a detailed characterization of the bacterial community associated with parthenogenetic F. candida. First, we evaluated a method to suppress the amplification of DNA from the endosymbiont Wolbachia, to prevent it from interfering with the identification of less abundant operational taxonomic units (OTUs). The suppression treatment applied was effective against Wolbachia and did not interfere with the detection of the most abundant OTUs (59 OTUs, contributing over 87% of the reads). However, this method did affect the inferred community composition. Significant differences were subsequently observed in the composition of bacterial communities associated with two different strains of F. candida. A total of 832 OTUs were found, of which 45% were only present in one strain and 17% only in the other. Among the 20 most abundant OTUs, 16 were shared between strains. Denaturing gradient gel electrophoresis and clone libraries, although unable to capture the full diversity of the bacterial community, provided results that supported the NGS data.

Ecotoxicogenomic assessment of diclofenac toxicity in soil.

Diclofenac is widely used as nonsteroidal anti-inflammatory drug leaving residues in the environment. To investigate effects on terrestrial ecosystems, we measured dissipation rate in soil and investigated ecotoxicological and transcriptome-wide responses in Folsomia candida. Exposure for 4 weeks to diclofenac reduced both survival and reproduction of F. candida in a dose-dependent manner. At concentrations ≥ 200 mg/kg soil diclofenac remained stable in the soil during a 21-day incubation period. Microarrays examined transcriptional changes at low and high diclofenac exposure concentrations. The results indicated that development and growth were severely hampered and immunity-related genes, mainly directed against bacteria and fungi, were significantly up-regulated. Furthermore, neural metabolic processes were significantly affected only at the high concentration. We conclude that diclofenac is toxic to non-target soil invertebrates, although its mode of action is different from the mammalian toxicity. The genetic markers proposed in this study may be promising early markers for diclofenac ecotoxicity.

Integrating transcriptomics into triad-based soil-quality assessment.

The present study examined how transcriptomics tools can be included in a triad-based soil-quality assessment to assess the toxicity of soils from riverbanks polluted by metals. To that end, the authors measured chemical soil properties and used the International Organization for Standardization guideline for ecotoxicological tests and a newly developed microarray for gene expression in the indicator soil arthropod Folsomia candida. Microarray analysis revealed that the oxidative stress response pathway was significantly affected in all soils except one. The data indicate that changes in cell redox homeostasis are a significant signature of metal stress. Finally, 32 genes showed significant dose-dependent expression with metal concentrations. They are promising genetic markers providing an early indication of the need for higher-tier testing of soil quality. During the bioassay, the toxicity of the least polluted soils could be removed by sterilization. The gene expression profile for this soil did not show a metal-related signature, confirming that a factor other than metals (most likely of biological origin) caused the toxicity. The present study demonstrates the feasibility and advantages of integrating transcriptomics into triad-based soil-quality assessment. Combining molecular and organismal life-history trait stress responses helps to identify causes of adverse effects in bioassays. Further validation is needed for verifying the set of genes with dose-dependent expression patterns linked with toxic stress.

Assessment of structure and function in metal polluted grasslands using Terrestrial Model Ecosystems.

Ecosystem effects of metal pollution in field situations are hard to predict, since metals occur often in mixtures and links between structural (organisms) and functional endpoints (ecosystem processes) are not always that clear. In grasslands, both structure and functioning was suspected to be affected by a mixture of copper, lead, and zinc. Therefore, the structural and functional variables were studied simultaneously using Terrestrial Model Ecosystems (TMEs). Comparing averages of low- and high-polluted soil, based on total metal concentrations, did not show differences in structural and functional variables. However, nematode community structure (Maturity Index) negatively correlated with metal concentrations. Next to that, multivariate statistics showed that enchytraeid, earthworm and, to lesser extent, nematode diversity decreased with increasing metal concentrations and a lower pH in the soil. Bacterial CFU and nematode biomass were positively related with decomposer activity and nitrate concentrations. Nitrate concentrations were negatively related to ammonium concentrations. Earthworm biomass, CO(2) production and plant yield were not related to metal concentrations. The most metal-sensitive endpoint was enchytraeid biomass. In all analyses, soil pH was a significant factor, indicating direct effects on organisms, or indicating indirect effects by influencing metal availability. In general, structural diversity seemed more positively related to functional endpoints than structural biomass. TMEs proved valuable tools to assess the structure and function in metal polluted field situations. The outcome feeds modeling effort and direct future research.

A stress ecology framework for comprehensive risk assessment of diffuse pollution.

Environmental pollution is traditionally classified as either localized or diffuse. Local pollution comes from a point source that emits a well-defined cocktail of chemicals, distributed in the environment in the form of a gradient around the source. Diffuse pollution comes from many sources, small and large, that cause an erratic distribution of chemicals, interacting with those from other sources into a complex mixture of low to moderate concentrations over a large area. There is no good method for ecological risk assessment of such types of pollution. We argue that effects of diffuse contamination in the field must be analysed in the wider framework of stress ecology. A multivariate approach can be applied to filter effects of contaminants from the many interacting factors at the ecosystem level. Four case studies are discussed (1) functional and structural properties of terrestrial model ecosystems, (2) physiological profiles of microbial communities, (3) detritivores in reedfield litter, and (4) benthic invertebrates in canal sediment. In each of these cases the data were analysed by multivariate statistics and associations between ecological variables and the levels of contamination were established. We argue that the stress ecology framework is an appropriate assessment instrument for discriminating effects of pollution from other anthropogenic disturbances and naturally varying factors.

Collembase: a repository for springtail genomics and soil quality assessment.

BACKGROUND: Environmental quality assessment is traditionally based on responses of reproduction and survival of indicator organisms. For soil assessment the springtail Folsomia candida (Collembola) is an accepted standard test organism. We argue that environmental quality assessment using gene expression profiles of indicator organisms exposed to test substrates is more sensitive, more toxicant specific and significantly faster than current risk assessment methods. To apply this species as a genomic model for soil quality testing we conducted an EST sequencing project and developed an online database. DESCRIPTION: Collembase is a web-accessible database comprising springtail (F. candida) genomic data. Presently, the database contains information on 8686 ESTs that are assembled into 5952 unique gene objects. Of those gene objects approximately 40% showed homology to other protein sequences available in GenBank (blastx analysis; non-redundant (nr) database; expect-value < 10-5). Software was applied to infer protein sequences. The putative peptides, which had an average length of 115 amino-acids (ranging between 23 and 440) were annotated with Gene Ontology (GO) terms. In total 1025 peptides (approximately 17% of the gene objects) were assigned at least one GO term (expect-value < 10-25). Within Collembase searches can be conducted based on BLAST and GO annotation, cluster name or using a BLAST server. The system furthermore enables easy sequence retrieval for functional genomic and Quantitative-PCR experiments. Sequences are submitted to GenBank (Accession numbers: EV473060 - EV481745). CONCLUSION: Collembase http://www.collembase.org is a resource of sequence data on the springtail F. candida. The information within the database will be linked to a custom made microarray, based on the Agilent platform, which can be applied for soil quality testing. In addition, Collembase supplies information that is valuable for related scientific disciplines such as molecular ecology, ecogenomics, molecular evolution and phylogenetics.

Assessment of soil contamination--a functional perspective.

In many industrialized countries the use of land is impeded by soil pollution from a variety of sources. Decisions on clean-up, management or set-aside of contaminated land are based on various considerations, including human health risks, but ecological arguments do not have a strong position in such assessments. This paper analyses why this should be so, and what ecotoxicology and theoretical ecology can improve on the situation. It seems that soil assessment suffers from a fundamental weakness, which relates to the absence of a commonly accepted framework that may act as a reference. Soil contamination can be assessed both from a functional perspective and a structural perspective. The relationship between structure and function in ecosystems is a fundamental question of ecology which receives a lot of attention in recent literature, however, a general concept that may guide ecotoxicological assessments has not yet arisen. On the experimental side, a good deal of progress has been made in the development and standardized use of terrestrial model ecosystems (TME). In such systems, usually consisting of intact soil columns incubated in the laboratory under conditions allowing plant growth and drainage of water, a compromise is sought between field relevance and experimental manageability. A great variety of measurements can be made on such systems, including microbiological processes and activities, but also activities of the decomposer soil fauna. I propose that these TMEs can be useful instruments in ecological soil quality assessments. In addition a "bioinformatics approach" to the analysis of data obtained in TME experiments is proposed. Soil function should be considered as a multidimensional concept and the various measurements can be considered as indicators, whose combined values define the "normal operating range" of the system. Deviations from the normal operating range indicate that the system is in a condition of stress. It is hoped that more work along this line will improve the prospects for ecological arguments in soil quality assessment.

Threshold models for species sensitivity distributions applied to aquatic risk assessment for zinc.

Species sensitivity distributions (SSDs) are used in ecological risk assessment to derive maximum acceptable concentrations of toxicants in the environment from a limited set of ecotoxicity data obtained in the laboratory. Such distributions usually employ continuous bell-shaped functions such as the normal and the logistic distribution, which have the disadvantage that an arbitrary cut-off value must be chosen (usually the 5-percentile) to designate the concentration below which the fraction of species exposed above their no-effect level is considered acceptably small. In this paper the possibility is explored of introducing a true no-effect principle in the SSD framework by considering models with a finite lower threshold. Four of these distributions are elaborated, the uniform, triangular, exponential and Weibull distributions. The mathematical representations of these functions were re-parameterized allowing direct estimation of the threshold parameter by nonlinear regression. By way of example, a data set comprising chronic ecotoxicity of zinc to 21 different aquatic organisms was used. The exponential distribution did not describe the data well. The other distributions provided estimates for HC(0) (hazardous concentration for none of the species) between 1.66 and 7.83 µg/l. The triangular distribution fitted best to the data and was consistent with previous models. Since threshold-SSDs incorporate a true no-effect level they may be better communicable as a principle for environmental protection in comparison to the approach based on '95% protection'.