Comprehensive environmental assessment: a meta-assessment approach.
Ontology highlight
ABSTRACT:
SUBMITTER: Powers CM
PROVIDER: S-EPMC3439956 | biostudies-other | 2012 Sep
REPOSITORIES: biostudies-other
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Project description:The Chinese government projected 30% of total consumed potatoes as a staple food (PSF) by 2020. We comprehensively assessed the potential impacts of PSF on rice and flour consumption, rice and wheat planting, energy and nutrient supply, irrigation-water, chemical nitrogen (N), phosphorus pentoxide (P2O5) and potassium oxide (K2O) fertilizer inputs and total greenhouse gases (GHG) emission for potatoes, rice and wheat, by assuming different proportions of potato substitutes for rice and flour. The results showed that per capita, 2.9 ± 0.3 and 4.7 ± 0.5 kg more potatoes per year would enter the Chinese staple-food diet, under the government's target. PSF consumed are expected to reach 5.2 ± 0.7 Tg yr-1, equivalent to substituting potatoes for 4.2 ± 0.8-8.5 ± 0.8 Tg yr-1 wheat and 5.1 ± 0.9-10.1 ± 1.8 Tg yr-1 rice under different scenarios. While this substitution can increase the nutrient supply index by 63% towards nutrient reference values, it may induce no significant effect on staple-food energy supply with lower chemical fertilizer (except for K2O) and irrigation-water inputs and GHG emissions in different substitution scenarios than the business as usual scenario. The reduction in rice and wheat demands lead to wheat in the North China Plain and early rice decrease by 6.1-11.4% and 12.1-24.1%, respectively. The total GHG reduction is equal to 1.1-9.0% of CO2 equivalent associated with CH4 and N2O emitted from the Chinese agroecosystem in 2005. The saved irrigation water for three crops compared to 2012 reaches the total water use of 17.9 ± 4.9-21.8 ± 5.9 million people in 2015. More N fertilizer, irrigation-water, and GHG can be reduced, if the PSF ratio is increased to 50% together with potato yield improves to the optimal level. Our results implied that the PSF policy is worth doing not only because of the healthier diets, but also to mitigate resource inputs and GHG emissions and it also supports agricultural structure adjustments in the areas of irrigated wheat on the North China Plain and early rice across China, designed to increase the adaptability to climate change.
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Project description:BACKGROUND:There is an increasing demand for rapid biodiversity assessment tools that have a broad taxonomic coverage. Here we evaluate a suite of environmental DNA (eDNA) markers coupled with next generation sequencing (NGS) that span the tree of life, comparing them with traditional biodiversity monitoring tools within ten 20×20 meter plots along a 700 meter elevational gradient. RESULTS:From six eDNA datasets (one from each of 16S, 18S, ITS, trnL and two from COI) we identified sequences from 109 NCBI taxonomy-defined phyla or equivalent, ranging from 31 to 60 for a given eDNA marker. Estimates of alpha and gamma diversity were sensitive to the number of sequence reads, whereas beta diversity estimates were less sensitive. The average within-plot beta diversity was lower than between plots for all markers. The soil beta diversity of COI and 18S markers showed the strongest response to the elevational variation of the eDNA markers (COI: r=0.49, p<0.001; 18S: r=0.48, p<0.001). Furthermore pairwise beta diversities for these two markers were strongly correlated with those calculated from traditional vegetation and invertebrate biodiversity measures. CONCLUSIONS:Using a soil-based eDNA approach, we demonstrate that standard phylogenetic markers are capable of recovering sequences from a broad diversity of eukaryotes, in addition to prokaryotes by 16S. The COI and 18S eDNA markers are the best proxies for aboveground biodiversity based on the high correlation between the pairwise beta diversities of these markers and those obtained using traditional methods.
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Project description:Parametric analysis of Cerebellar Ataxia (CA) could be of immense value compared to its subjective clinical assessments. This study focuses on a comprehensive scheme for objective assessment of CA through the instrumented versions of 9 commonly used neurological tests in 5 domains- speech, upper limb, lower limb, gait and balance. Twenty-three individuals diagnosed with CA to varying degrees and eleven age-matched healthy controls were recruited. Wearable inertial sensors and Kinect camera were utilised for data acquisition. Binary and multilabel discrimination power and intra-domain relationships of the features extracted from the sensor measures and the clinical scores were compared using Graph Theory, Centrality Measures, Random Forest binary and multilabel classification approaches. An optimal subset of 13 most important Principal Component (PC) features were selected for CA-control classification. This classification model resulted in an impressive performance accuracy of 97% (F1 score?=?95.2%) with Holmesian dimensions distributed as 47.7% Stability, 6.3% Timing, 38.75% Accuracy and 7.24% Rhythmicity. Another optimal subset of 11 PC features demonstrated an F1 score of 84.2% in mapping the total 27 PC across 5 domains during CA multilabel discrimination. In both cases, the balance (Romberg) test contributed the most (31.1% and 42% respectively), followed by the peripheral tests whereas gait (Walking) test contributed the least. These findings paved the way for a better understanding of the feasibility of an instrumented system to assist informed clinical decision-making.
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Project description:We evaluated the suitability of high-throughput transcriptomics approach to monitor terrestrial ecosystems. Free-living Mus spretus from several polluted sites of Huelva (Andalusia, SW Spain) were compared with mice from Doñana Biological Reserve (“Santa Olalla” lagoon (SOL) used as negative control). As most popular bioindicators, M. spretus is poorly represented in gene databases, therefore limiting the use of genomics in ecotoxicological studies. To solve this problem, we used microarrays produced from mRNAs of M. musculus. Specifically we used the One-Color Gene Expression Platform commercialized by Agilent.
2013-12-31 | GSE33663 | GEO
Project description:We evaluated the suitability of high-throughput transcriptomics approach to monitor terrestrial ecosystems. Free-living Mus spretus from several polluted sites of Huelva (Andalusia, SW Spain) were compared with mice from DoM-CM-1ana Biological Reserve (M-bM-^@M-^\Santa OlallaM-bM-^@M-^] lagoon (SOL) used as negative control). As most popular bioindicators, M. spretus is poorly represented in gene databases, therefore limiting the use of genomics in ecotoxicological studies. To solve this problem, we used microarrays produced from mRNAs of M. musculus. Specifically we used the One-Color Gene Expression Platform commercialized by Agilent. Gene expression in Mus spretus liver was assessed in mice from 5 sites of the Spanish Southwest. Five independent experiments were performed. The arrays were hybridized with labelled cRNA samples made from pooled livers of 9 mice per sampling site. We made 4 technichal repetitions per sample.
2013-12-31 | E-GEOD-33663 | biostudies-arrayexpress
Project description:Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.
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Project description:In many developing countries, including South Africa, water scarcity has resulted in poor sanitation practices. The majority of the sanitation infrastructures in those regions fail to meet basic hygienic standards. This along with the lack of proper sewage/wastewater infrastructure creates significant environmental and public health concerns. A self-sustained, waterless "Nano Membrane Toilet" (NMT) design was proposed as a result of the "Reinvent the Toilet Challenge" funded by the Bill and Melinda Gates Foundation. A "cradle-to-grave" life cycle assessment (LCA) approach was adopted to study the use of NMT in comparison with conventional pour flush toilet (PFT) and urine-diverting dry toilet (UDDT). All three scenarios were applied in the context of South Africa. In addition, a Quantitative Microbial Risk Assessment (QMRA) was used to reflect the impact of the pathogen risk on human health. LCA study showed that UDDT had the best environmental performance, followed by NMT and PFT systems for all impact categories investigated including human health, resource and ecosystem. This was mainly due to the environmental credits associated with the use of urine and compost as fertilizers. However, with the incorporation of the pathogen impact into the human health impact category, the NMT had a significant better performance than the PFT and UDDT systems, which exhibited an impact category value 4E?+?04 and 4E?+?03 times higher, respectively. Sensitivity analysis identified that the use of ash as fertilizer, electricity generation and the reduction of NOx emissions were the key areas that influenced significantly the environmental performance of the NMT system.
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Project description:CTNNB1, encoding ?-catenin, is a well-known tumor-related gene in the wnt signaling pathway. It has been reported that CTNNB1 polymorphisms are associated with cancer risk. However, the data were inconsistent. In this article, we conducted a systematic review for the researches related to the association of single nucleotide polymorphisms (SNPs) in CTNNB1 with overall cancer risk. Meanwhile, a series of inclusion and exclusion criteria were set to select articles for quantitative analysis. Consequently, eight case-control studies containing 4388 cases and 4477 controls were included in a meta-analysis of four highly studied CTNNB1 SNPs (rs1798802 A/G, rs4135385 A/G, rs11564475 A/G, and rs2293303 C/T). The association between each SNP and cancer risk was estimated by calculating odds ratios (ORs) and their 95% confidence intervals (95%CIs). The results showed rs1798802 (AA compared with GG: P=0.044, OR=0.72) and rs2293303 (TT compared with CC: P=0.002, OR=2.86; recessive model: P=0.006, OR=2.91; T compared with C: P=0.004, OR=1.19) polymorphisms were associated with overall cancer risk. In stratified analysis, rs4135385 polymorphism was found to elevate the risk in Caucasian or in gastrointestinal cancer subgroup. Additionally, rs2293303 conferred to an increased cancer risk when the source of control groups was hospital-based (HB). In conclusion, the three CTNNB1 SNPs were suggested to have the potential to be novel biomarkers for risk prediction of cancer in overall population or some specific subgroups. Our study could provide research clues for further related investigations.
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