Advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the ...domain of ecologists are now being used more widely. This 2006 book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.
Groundwater contamination studies are important to understand the risks to public health. In this study, groundwater quality, major ion chemistry, sources of contaminants, and related health risks ...were evaluated for North-West Delhi, India, a region with a rapidly growing urban population. Groundwater samples collected from the study area were analysed for physicochemical parameters — pH, electrical conductivity, total dissolved solids, total hardness, total alkalinity, carbonate, bicarbonate, chloride, nitrate, sulphate, fluoride, phosphate, calcium, magnesium, sodium and potassium. Investigation of hydrochemical facies revealed that bicarbonate was the dominant anion while magnesium was the dominant cation. Multivariate analysis using principal component analysis and Pearson correlation matrix indicated that major ion chemistry in the aquifer under study is primarily due to mineral dissolution, rock-water interactions and anthropogenic factors. Water quality index values showed that only 20% of the samples were acceptable for drinking. Due to high salinity, 54% of the samples were unfit for irrigation purposes. Nitrate and fluoride concentrations ranged from 0.24 to 380.19 mg/l and 0.05 to 7.90 mg/l, respectively due to fertilizer use, wastewater infiltration and geogenic processes. The health risks from high levels of nitrate and fluoride were calculated for males, females, and children. It was found that health risk from nitrate is more than fluoride in the study region. However, the spatial extent of risk from fluoride is more indicating that more people suffer from fluoride pollution in the study area. The total hazard index for children was found to be more than adults. Continuous monitoring of groundwater and application of remedial measures are recommended to improve the water quality and public health in the region.
Compositional data are commonly used in chemical ecology to describe the biological role of chemical compounds in communication, defense or other behavioral modifications. Statistical analyses of ...compositional data, however, are challenging due to several constraints (e.g., constant sum constraint). We use an ontogenetic series of defensive gland secretions from larvae, three nymphal stages and adults of the oribatid model species
Archegozetes longisetosus
as a typical chemo-ecological data set to prepare a practical guide for compositional data analyses in chemical ecology. We compare various common and less common statistical and ordination methods to depict small quantitative and/or qualitative differences in compositional datasets: principal component analysis (PCA), non-metric multidimensional scaling (NMDS), multivariate statistical tests (Anderson’s permutational multivariate analyses of variance = PERMANOVA; permutational analyses of multivariate dispersions = PERMDIPS), linear discriminant analysis (LDA), the data mining algorithm Random Forests, bipartite network analysis and dynamic range boxes (dynRB). We summarize which methods are suitable for different research questions and how data needs to be structured and pre-processed. Network analyses and dynamic range boxes are promising tools for analyzing compositional data beyond the “classical” methods and provide additional information.
Abstract
This study proposed a framework to evaluate multivariate return periods of hurricanes using event‐based frequency analysis techniques. The applicability of the proposed framework was ...demonstrated using point‐based and spatial analyses on a recent catastrophic event, Hurricane Ian. Univariate, bivariate, and trivariate frequency analyses were performed by applying generalized extreme value distribution and copula on annual maximum series of flood volume, peak discharge, total rainfall depth, maximum wind speed, wave height and storm surge. As a result of point‐based analyses, return periods of Hurricane Ian was investigated by using our framework; univariate return periods were estimated from 39.2 to 60.2 years, bivariate from 824.1 to 1,592.6 years, and trivariate from 332.1 to 1,722.9 years for the Daytona‐St. Augustine Basin. In the Florida Bay‐Florida Keys Basin, univariate return periods were calculated from 7.5 to 32.9 years, bivariate from 36.5 to 114.9 years, and trivariate from 25.0 to 214.8 years. Using the spatial analyses, we were able to generate the return period map of Hurricane Ian across Florida. Based on bivariate frequency analyses, 18% of hydrologic unit code 8 (HUC8) basins had an average return period of more than 30 years. Sources of uncertainty, due to the scarcity of analysis data, stationarity assumption and impact of other weather systems such as strong frontal passages, were also discussed. Despite these limitations, our framework and results will be valuable in disaster response and recovery.
Key Points
We introduced a new framework for evaluating multivariate return periods of hurricane events through event‐based frequency analyses
Using this framework, we estimated the univariate, bivariate, and trivariate return periods of Hurricane Ian
A return period map was produced using the framework to identify the HUC8 basins affected by Hurricane Ian
Abstract
While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true ...miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.
Concentrations of heavy metals in sediments and seawaters from the intertidal zone are analyzed along with cage-bred fish in the Sandu Bay of Fujian Province in China. Elements measured are As, Cd, ...Cr, Cu, Hg, Ni, Pb, and Zn. The concentrations of Cu and Ni found in the sediments do not meet the first standard of the Chinese National Criteria for Marine Sediment Quality. The results of Igeo, EF, and CF index calculations for the sediment samples clearly prove anthropogenic causes of contamination. The water quality standard for fisheries was exceeded by As, Hg, and Cu. Cage-bred fish show increased levels of As, Cr, and Zn. Significant associations are found for AsCu and NiZn. These findings can be related to coal and crude oil combustion and processes associated with the production of batteries, steel, and alloys. The results point to industrial source locations along discharging rivers north and northwest of the Sandu Bay.
•Main contaminants in the sediments and seawater are As, Cr, Cu, Hg, Ni, Pb, and Zn.•The contamination with heavy metals is of anthropogenic origin.•Fish, cage bred in the bay, exceed Chinese food safety standards for As, Cr and Zn.•Processes of heavy industry and maritime ship traffic can be considered as sources.
Considerable lacunae exists in As and F− co-contamination investigation in the Brahmaputra and Gangetic floodplains. Therefore we selected Diphu a township in the Karbi Plateau rising from the ...Brahmaputra floodplains for evaluation of As and F co-occurrence, correlation with coexisting ions of the aquifer system and elucidation of potential processes for releasing As and F− in the groundwater. Our initial appraisal used generic plots for identification of hydro geochemical processes and major water types. Subsequently, As and F− co-occurrence with pH, depth, HCO3−, SO42−, Ca2+ and Fe were probed for possible correlation followed by hierarchical cluster analyses to identify key processes for co-occurrence. Finally, saturation indices of groundwater minerals were calculated using MINTEQA2 to elucidate prospective As and F− release into groundwater. Results indicate F− and As presence in Ca–HCO3 rich water along with positive correlation between Ca2+ and F− possibly due to limestone reserves in adjoining areas. Multivariate analyses suggest the presence of high concentrations of PO43−, and H4SiO4 either individually or in combination can enhance the mobility of both As and F− and possibly abet conditions conducive for co-contamination of aquifers. Initial release of As and F− from the parent rock seems driven by the anthropogenic activities while mobilization depends on chemical interactions and individual affinities of the elements. The results of speciation highlight further mobilization of As and F− into the groundwater which in turn require regular attention for sustainable management of scarce water resource present in the area.
•Application of speciation and cluster analyses to understand co-contamination.•Two contaminants were not found strongly correlated in their distribution.•PO43−, HCO3−, and H4SiO4 enhance the mobility of both As and F−.•Initial release of As and F− seems driven by anthropogenic activities.•Mobilization depends on individual chemical affinities of the elements (As or F−).
The study investigates the occurrence and bioaccumulation of heavy metals in water, sediment, fish, and prawn from the Ojo River with a view to identify the source of origin and the associated ...ecological and human health risks. The result shows that heavy metal concentrations in water As = 0.010, Cd = 0.001, Cr = 0.041, Cu = 0.019, Co = 0.050, Fe = 0.099, Pb = 0.006, Ni = 0.003, and Zn = 0.452(mg/L) were within the acceptable limits. The heavy metals in the sediment As = 0.050, Cd = 0.287, Cr = 0.509, Cu = 0.207, Co = 0.086, Fe = 33.093, Pb = 0.548, Ni = 0.153 and Zn = 4.249 (mg/kg) were within their respective background levels or earth’s crust and the TEL and PEL standard limits. The bioaccumulation of heavy metals in fish and prawn tissues are in this hierarchical form: Fe > Zn > Cu > Cr > Ni > Co > Pb > Ar > Cd and Fe > Zn > Cu > Cr > Pb > Ar > Ni > Co > Cd, respectively. The bioaccumulation factors of heavy metals in fish ranged from 0.893 - 16.611 and 1.056 - 49.204 in prawn, which were higher than the biota-sedimentation factors (BSAF) values, inferring that the fish and prawns of this study ingested heavy metals highly from water column. The aggregated BSAF scores (fish = 5.584 and prawn = 9.137) showed that these organisms are good concentrators of heavy metals in sediments. The water quality index and other pollution indices (Single pollution index, Heavy metal assessment index, and Heavy metal pollution index) demonstrates slightly clean water, with a moderate level of contamination. The HI values of heavy metals in water, fish, and prawn were lower than 1, implying non-carcinogenic risk in children or adults. The ADD and EDI values of the metals were within their respective oral reference doses (RfD). The TCR values showed that exposure to water, either by ingestion or dermal absorption and the consumption of
P. obscura
and
M. vollenhovenii
from the Ojo River would not induce cancer risks in people, though As, Cr, Cd, and Pb showed carcinogenic potentials. The sediment contamination indices such as CF, mCd, EF, and Igeo showed a moderate level of pollution. The ecological risk values (NMPI, mCd = 0.068, PLI = 0.016, and R.I = 86.651) of heavy metals implies “no-moderate risk” except for Cd, which showed high risk. The ecotoxicological parameters, m-PEL-Q (0.024) and m-ERM-Q (0.016) denotes low contamination and no probability of acute toxicity. The CV analysis showed high dispersions and variabilities in the distributions of the heavy metals in water. Other source analyses (Pearson’s correlation matrix, PCA, and HCA) showed that both natural processes and anthropogenic activities are responsible for the occurrence of heavy metals in water and sediment from the Ojo River.
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