太湖典型河网区地表水与沉积物氮、磷和重金属含量空间分异

将无锡城乡交错区河网分为城镇生活区水巷、工业区主河道、农业区主河道、农业区支流和鱼塘5种类型区.通过秋季(旱季)和夏季(雨季)2次采样,研究氮、磷和Cu、Zn、Pb、Cr、Cd在地表水和沉积物中的含量及其空间变化.结果表明:(1)城乡交错区地表水氮、磷来源于生活污染和工业污染的比例大于农田,同时具有来源分散、污染面广的特征.(2)由于城镇地表径流和工业活动影响,各类型区地表水重金属含量均有不同程度提高.但地表水重金属主要沿主河道迁移,旱季和雨季主河道重金属含量均大于农业区支流,而且随着与城镇距离增加,主河道沉积物重金属含量迅速降低,重金属污染影响范围较小.(3)与重金属相比,地表水氮、磷污染仍是太湖水网区主要的环境问题.但城镇及其周围河流沉积物中富集的重金属含量很高,其潜在环境风险不容忽视.     

Influence of contaminant burial depth on the bioaccumulation of PCBs and PBDEs by two benthic invertebrates (Monoporeia affinis and Marenzelleria spp.)

The bioaccumulation of buried polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) added to specific depths in sediment (2.0-2.5, 5.0-5.5 and 10.0-10.5 cm) was studied in two infaunal species with similar feeding habits (surface deposit-feeders) but different bioturbation modes. The deep-burrowing polychaetes Marenzelleria spp. (Mz) displayed up to 36 times higher tissue concentrations of buried (spiked) contaminants than the surface-dwelling biodiffusing amphipod Monoporeia affinis. The differences in bioaccumulation were most pronounced for less hydrophobic contaminants due to the bioirrigating activity of Mz. Contaminants buried at shallow depths displayed higher accumulation than more deeply buried contaminants. In contrast, the bioaccumulation of unspiked (native) contaminants with a uniform vertical distribution in the sediment was similar between the species. For Mz, the BSAFs increased with increased K_OW for the uniformly distributed contaminants, but decreased for the buried contaminants, which indicates that the dominant uptake routes of the buried contaminants can differ from the uniformly distributed contaminants. The surface sediment concentration of buried contaminants increased in Mz treatments, showing that Mz bioturbation can remobilize historically buried contaminants to the biologically active surface layer and increase the exposure for surface-dwelling species.     

Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

Environmental Services Provided from Riparian Forests in the Nordic Countries

Riparian forests (RF) growing along streams, rivers and lakes comprise more than 2% of the forest area in the Nordic countries (considering a 10 m wide zone from the water body). They have special ecological functions in the landscape. They receive water and nutrients from the upslope areas, are important habitats for biodiversity, have large soil carbon stores, but may emit more greenhouse gases (GHG) than the uplands. In this article, we present a review of the environmental services related to water protection, terrestrial biodiversity, carbon storage and greenhouse gas dynamics provided by RF in the Nordic countries. We discuss the benefits and trade-offs when leaving the RF as a buffer against the impacts from upland forest management, in particular the impacts of clear cutting. Forest buffers are effective in protecting water quality and aquatic life, and have positive effects on terrestrial biodiversity, particularly when broader than 40 m, whereas the effect on the greenhouse gas exchange is unclear.     

Strong Influence of Variable Treatment on the Performance of Numerically Defined Ecological Regions

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale “sub-domains” defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.     

Acute and chronic effects of nano- and non-nano-scale TiO2 and ZnO particles on mobility and reproduction of the freshwater invertebrate Daphnia magna

Among the emerging literature addressing the biological effects of nanoparticles, very little information exists, particularly on aquatic organisms, that evaluates nanoparticles in comparison to non-nanocounterparts. Therefore, the potential effects of nano-scale and non-nano-scale TiO₂ and ZnO on the water flea, Daphnia magna, were examined in 48-h acute toxicity tests using three different test media, several pigment formulations – including coated nanoparticles – and a variety of preparation steps. In addition, a 21-d chronic Daphnia reproduction study was performed using coated TiO₂ nanoparticles. Analytical ultracentrifugation analyses provided evidence that the nanoparticles were present in a wide range of differently sized aggregates in the tested dispersions. While no pronounced effects on D. magna were observed for nano-scale and non-nano-scale TiO₂ pigments in 19 of 25 acute (48-h) toxicity tests (EC50 > 100 mg L⁻¹), six acute tests with both nano- and non-nano-scale TiO₂ pigments showed slight effects (EC10, 0.5–91.2 mg L⁻¹). For the nano-scale and non-nano-scale ZnO pigments, the acute 48-h EC50 values were close to the 1 mg L⁻¹ level, which is within the reported range of zinc toxicity to Daphnia. In general, the toxicity in the acute tests was independent of particle size (non-nano-scale or nano-scale), coating of particles, aggregation of particles, the type of medium or the applied pre-treatment of the test dispersions. The chronic Daphnia test with coated TiO₂ nanoparticles demonstrated that reproduction was a more sensitive endpoint than adult mortality. After 21 d, the NOEC for adult mortality was 30 mg L⁻¹ and the NOEC for offspring production was 3 mg L⁻¹. The 21-d EC10 and EC50 values for reproductive effects were 5 and 26.6 mg L⁻¹, respectively. This study demonstrates the utility of evaluating nanoparticle effects relative to non-nano-scale counterparts and presents the first report of chronic exposure to TiO₂ nanoparticles in D. magna.     

Design,Engineering, and Construction of Photosynthetic Microbial Cell Factories for Renewable Solar Fuel Production

There is an urgent need to develop sustainable solutions to convert solar energy into energy carriers used in the society. In addition to solar cells generating electricity, there are several options to generate solar fuels. This paper outlines and discusses the design and engineering of photosynthetic microbial systems for the generation of renewable solar fuels, with a focus on cyanobacteria. Cyanobacteria are prokaryotic microorganisms with the same type of photosynthesis as higher plants. Native and engineered cyanobacteria have been used by us and others as model systems to examine, demonstrate, and develop photobiological H₂ production. More recently, the production of carbon-containing solar fuels like ethanol, butanol, and isoprene have been demonstrated. We are using a synthetic biology approach to develop efficient photosynthetic microbial cell factories for direct generation of biofuels from solar energy. Present progress and advances in the design, engineering, and construction of such cyanobacterial cells for the generation of a portfolio of solar fuels, e.g., hydrogen, alcohols, and isoprene, are presented and discussed. Possibilities and challenges when introducing and using synthetic biology are highlighted.     

Exposure assessment at a PCDD/F contaminated site in Sweden—field measurements of exposure media and blood serum analysis

Background, aim, and scope  

The main pathway for human exposure to the highly toxic polychlorinated-p-dioxins and polychlorinated furans [polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs)] is via dietary intake. Other exposure pathways may, however, be important in close proximity to point sources, such as wood preservation sites, where PCDD/F contaminated chlorophenols (CP) were previously used. In this study, a heavily PCDD/F contaminated CP saw mill site in Sweden was investigated. Human exposure through a broad spectrum of exposure pathways was assessed. Such studies are in demand since the question whether contaminated sites represent a current or future risk can only be answered by detailed site-specific risk assessments.     

Rapid whole exome sequencing in pregnancies to identify the underlying genetic cause in fetuses with congenital anomalies detected by ultrasound imaging

Objective

The purpose of this study was to explore the diagnostic yield and clinical utility of trio-based rapid whole exome sequencing (rWES) in pregnancies of fetuses with a wide range of congenital anomalies detected by ultrasound imaging.

Methods

In this observational study, we analyzed the first 54 cases referred to our laboratory for prenatal rWES to support clinical decision making, after the sonographic detection of fetal congenital anomalies. The most common identified congenital anomalies were skeletal dysplasia (n = 20), multiple major fetal congenital anomalies (n = 17) and intracerebral structural anomalies (n = 7).

Results

A conclusive diagnosis was identified in 18 of the 54 cases (33%). Pathogenic variants were detected most often in fetuses with skeletal dysplasia (n = 11) followed by fetuses with multiple major fetal congenital anomalies (n = 4) and intracerebral structural anomalies (n = 3). A survey, completed by the physicians for 37 of 54 cases, indicated that the rWES results impacted clinical decision making in 68% of cases.

Conclusions

These results suggest that rWES improves prenatal diagnosis of fetuses with congenital anomalies, and has an important impact on prenatal and peripartum parental and clinical decision making.