The cumulative ecological risks from multiple herbicides in Japanese rivers were evaluated using species sensitivity distribution and were compared with natural periphytic diatom communities. Region-specific predicted environmental concentrations were estimated at 9 rivers considering the region-specific parameters of environmental conditions. Then the multi-substance potentially affected fraction (msPAF) was calculated as a risk index of multiple herbicides using the computation tool NIAES-CERAP. On the other hand, river ecological survey focusing on diatom community were conducted in these 9 rivers and several biological metrics for species composition were calculated such as genus number, Shannon’s diversity, DAIpo, and SPEARherbicides which is an indicator of the herbicide effect on the diatom community. DAIpo and SPEARherbicides (but the population number of each genus was not log-transformed) significantly correlated with msPAF, indicating the applicability of these metrics for assessing the effect of herbicide mixture. Moreover, the percentage of abundance for genus Planothidium and Nitzschia were significantly correlated with msPAF negatively and positively, respectively.
We compared the sensitivity based on the 50 percent effective concentrations (EC50s) of five species of plant to six herbicides, using an efficient high-throughput microplate-based toxicity assay. For five herbicides, the most sensitive species differed: Welsh onion Allium fistulosum was most sensitive to cyclosulfamuron (the inhibitor of acetolactate synthase), pretilachlor (the inhibitor of very long-chain fatty acid (VLCFA) synthesis) and pyrazoxyfen (the inhibitor of 4-hydroxyphenylpyruvate dioxygenase): watercress Nasturtium officinale was most sensitive to pyraclonil (the inhibitor of protoporphyrinogen oxidase); and basil Ocimum basilicum was most sensitive to esprocarb (the inhibitor of VLCFA synthesis). Simetryn, the inhibitor of photosynthesis, was evenly less toxic, with no differences in species sensitivity. These results suggested that a single species cannot represent the sensitivity of the primary producer assemblage to a given herbicide. To assess the ecological effects of herbicides, multispecies plant toxicity data sets are essential.
Styrene is a volatile chemical used as a raw material for production of synthetic resins and synthetic rubbers. A study of inhibition of algal growth was carried out according to OECD test guideline 201 in a completely closed system to clarify the inhibition of growth of the green alga Raphidocelis subcapitata by styrene. The median effective concentration for growth rate (ErC50) and no-observed-effect concentration for growth rate (NOECr) based on the measured concentrations of styrene were 5.99 mg/L and 0.985 mg/L, respectively. Based on these results, the Globally Harmonized System of Classification and Labelling of Chemicals (GHS) classification of hazards to the aquatic environment of styrene was Category 2 for short-term (acute) exposure and Category 3 for long-term (chronic) exposure.
The generalized linear model (GLM) is a useful tool to evaluate the relationship between the response variable and explanatory variables. However, the GLM analysis cannot consider the variation between experimental groups when the data shows over-dispersion of ecotoxicity testing data due to experimental replication. Alternatively, the generalized linear mixed model (GLMM) contains random effects which show a probability density distribution (in many cases, the Gaussian distribution is applied) attributed to the data variation. The GLMM can make a large variation by mixing the assumed probability density distribution with the fixed effects. To show the difference between GLM and GLMM analysis, we introduced two toxicity tests (Chironomus acute toxicity test in and mesocosm test) using dummy count data. The GLMM shows larger errors in the slope and intercept values than those in the GLM.
For the Chironomus acute toxicity test, the GLMM estimated large 95% confidence intervals for the EC50 (median effective concentration) values, which could show the toxicity variations between the replications. Our findings suggested that the GLM analysis is likely to increase frequency of Type I error in estimating the relationship between variables if there is a large variation between the data.
We performed algal growth inhibition test on Desmodesmus subspicatus using a cationic surfactant benzalkonium bromide (BZK-Br), and acute toxicity tests on two cladoceran species, Daphnia galeata and Bosmina longirostris, using BZK-Br and an anionic surfactant sodium octyl sulfate (SOS). The 72-h 50% effective concentration (EC50) with 95% confidence interval (CI) of initial BZK-Br to D. subspicatus was 60.3 µg L−1 with 46.4–74.2 µg L−1. The 48-h EC50s (with those CIs) of BZK-Br to D. galeata and B. longirostris, estimated from the geometric mean concentrations, were 40.9 (33.0–48.8) µg L−1 and 80.1 (68.1–92.0) µg L−1, respectively. Unlike BZK-Br, the 48-h EC50s (with those CIs) of SOS to D. galeata (335.9 mg L−1, 248.5–423.3 mg L−1) and B. longirostris (280.0 mg L−1, 211.1–348.9 mg L−1) were comparable. The present results were discussed about the difference in EC50s to similar compounds on standard test organisms. We also mentioned that BZK-Br and SOS concentrations can present below the EC50s in surface water, whereas they can affect biological interactions by interfering with colony formation response in D. subspicatus even at environmentally relevant concentrations.
Comparison of ecological risk assessment of herbicide by species sensitivity distribution with effect assessment of natural periphytic diatom communities by river ecological survey
Comparison of sensitivity of vascular plants to six paddy rice herbicides using the seed germination and seedling growth test method for five vascular plant species simultaneously
Effects of styrene on growth inhibition of Raphidocelis subcapitata
Statistical analysis for large variations between data using generalized linear mixed models
Sensitivities to surfactants in Desmodesmus subspicatus, Daphnia galeata, and Bosmina longirostris