Publications by authors named "Asim Biswas"

35 Publications

Identifying hotspots and representative monitoring locations of field scale NO emissions from agricultural soils: A time stability analysis.

Sci Total Environ 2021 Sep 23;788:147955. Epub 2021 May 23.

School of Environmental Sciences, University of Guelph, Guelph, ON N1G2W1, Canada. Electronic address:

Greenhouse gas sampling from agricultural fields is laborious and time-consuming. Soil and topographical heterogeneity cause spatiotemporal variations, making nitrous oxide (NO) estimation and management a challenge. Identification of representative monitoring locations, hotspots, and coldspots could facilitate the mitigation of agricultural NO emissions. The objective of this study was to identify and characterize representative monitoring locations, hotspots, and coldspots of NO emissions in agricultural fields (Baggs farm; BF and Research North farm; RN) in Cambridge, Ontario, Canada, under humid continental climate. Soil in both fields was classified as Orthic Melanic Brunisol, with some areas categorized as Gleyed Brunisolic Gray Brown Luvisol and Orthic Humic Gleysol. In total, 28 sampling points were selected following conditional Latin hypercube design using topographical parameters (digital elevation, slope, topographical wetness index, and Pennock landform classification). Gas samples were collected over a two-year crop rotation with corn (2019) and soybean (2020). Additional sampling was conducted at BF at spring thaw (2020). Time stability analysis using mean relative difference (MRD) and standard deviation of mean relative difference (SDRD) was performed to test the hypothesis that "simultaneous analysis of spatiotemporal variations in NO emissions could help to identify and characterize representative monitoring locations, hotspots, coldspots and areas with few hot and cold moments. Most of the hotspots were located at shoulder positions, coldspots, and cold moments at backslope, and representative monitoring points were located at leveled positions or localized depressions. Time stability analysis coupled with multivariate groping analysis supported our hypothesis and helped successfully identify hotspots, coldspots, and representative locations based on landform classification with few exceptions. However, inclusion of additional topographical (curvature, contributing area, aspect) and morphological parameters (texture, thickness of soil horizon, depth to bedrock, and water table) are suggested for consideration in future research to manage variable-rate fertilizer application and mitigate NO hotspots at landscape level.
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http://dx.doi.org/10.1016/j.scitotenv.2021.147955DOI Listing
September 2021

Are heavy metals in urban garden soils linked to vulnerable populations? A case study from Guelph, Canada.

Sci Rep 2021 May 28;11(1):11286. Epub 2021 May 28.

School of Environmental Sciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.

With increasing population, there is growing concern for food security in urban areas. Though, urban gardening has gained popularity, several studies have found higher concentrations of contaminants in urban soils, especially heavy metals, often at toxic levels, which pose a potential risk for human health. Moreover, heavy metal polluted sites have been strongly associated with areas populated by low-income families, newcomers and racial minorities. In this study, heavy metals in the soils of community gardens in the city of Guelph, ON were examined as a case study and their relationship with vulnerable populations. We analyzed soil samples at two depths for a range of heavy metals and characterized their spatial patterns to see if they were related to disadvantaged communities. We estimated the pollution levels using two index-based approaches and assessed their potential risk for human health, although concentrations of most heavy metals were below the limits established by Canadian regulations, metals like Cd, Pb, Se and Zn exhibited a mild degree of pollution, whereas As exhibited a severe degree. Their association with vulnerable populations were weak, but hotspots were mainly located in low-income areas. This case study provides scientific evidence that could help to expand our understanding around the interconnection between pollution and poverty/racial inequality. Also the importance of generating strategies for the protection of human health and sustainable soil management practices in urban areas where food for human consumption is grown.
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http://dx.doi.org/10.1038/s41598-021-90368-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163869PMC
May 2021

Tapping the immunological imprints to design chimeric SARS-CoV-2 vaccine for elderly population.

Int Rev Immunol 2021 May 12:1-16. Epub 2021 May 12.

Division of Clinical Medicine, National Institute of Cholera and Enteric Diseases, Kolkata, India.

The impact of SARS-CoV-2 and COVID-19 disease susceptibility varies depending on the age and health status of an individual. Currently, there are more than 140 COVID-19 vaccines under development. However, the challenge will be to induce an effective immune response in the elderly population. Analysis of B cell epitopes indicates the minor role of the stalk domain of spike protein in viral neutralization due to low surface accessibility. Nevertheless, the accumulation of mutations in the receptor-binding domain (RBD) might reduce the vaccine efficacy in all age groups. We also propose the concept of chimeric vaccines based on the co-expression of SARS-CoV-2 spike and influenza hemagglutinin (HA) and matrix protein 1 (M1) proteins to generate chimeric virus-like particles (VLP). This review discusses the possible approaches by which influenza-specific memory repertoire developed during the lifetime of the elderly populations can converge to mount an effective immune response against the SARS-CoV-2 spike protein with the possibilities of designing single vaccines for COVID-19 and influenza. HighlightsImmunosenescence aggravates COVID-19 symptoms in elderly individuals.Low immunogenicity of SARS-CoV-2 vaccines in elderly population.Tapping the memory T and B cell repertoire in elderly can enhance vaccine efficiency.Chimeric vaccines can mount effective immune response against COVID-19 in elderly.Chimeric vaccines co-express SARS-CoV-2 spike and influenza HA and M1 proteins.
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http://dx.doi.org/10.1080/08830185.2021.1925267DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8127164PMC
May 2021

Long-term continuous cropping affects ecoenzymatic stoichiometry of microbial nutrient acquisition: a case study from a Chinese Mollisol.

J Sci Food Agric 2021 May 10. Epub 2021 May 10.

Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.

Background: Soil- and plant-produced extracellular enzymes drive nutrient cycling in soils and are assumed to regulate supply and demand for carbon (C) and nutrients within the soil. Thus, agriculture management decisions that alter the balance of plant and supplemental nutrients should directly alter extracellular enzyme activities (EEAs), and EEA stoichiometry in predictable ways. We used a 12-year experiment that varyied three major continuous grain crops (wheat, soybean, and maize), each crossed with mineral fertilizer (WCF, SCF and MCF, respectively) or not fertilized (WC, SC and MC, respectively, as controls). In response, we measured the phospholipid fatty acids (PLFAs), EEAs and their stoichiometry to examine the changes to soil microbial nutrient demand under the continuous cropping of crops, which differed with respect to the input of plant litter and fertilizer.

Results: Fertilizer generally decreased soil microbial biomass and enzyme activity compared to non-fertilized soil. According to enzyme stoichiometry, microbial nutrient demand was generally C- and phosphorus (P)-limited, but not nitrogen (N)-limited. However, the degree of microbial resource limitation differed among the three crops. The enzymatic C:N ratio was significantly lower by 13.3% and 26.8%, whereas the enzymatic N:P ratio was significantly higher by 9.9% and 42.4%, in MCF than in WCF and SCF, respectively. The abundances of arbuscular mycorrhizal fungi and aerobic PLFAs were significantly higher in MCF than in WCF and SCF.

Conclusion: These findings are crucial for characterizing enzymatic activities and their stoichiometries that drive microbial metabolism with respect to understanding soil nutrient cycles and environmental conditions and optimizing practices of agricultural management. © 2021 Society of Chemical Industry.
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http://dx.doi.org/10.1002/jsfa.11304DOI Listing
May 2021

Optimizing biochar application to improve soil physical and hydraulic properties in saline-alkali soils.

Sci Total Environ 2021 Jun 27;771:144802. Epub 2021 Jan 27.

School of Environmental Sciences, University of Guelph, Guelph, Ontario N1G 2W1, Canada.

Biochar application has been a promising approach to improve soil quality but their optimal amount in improving physical and hydraulic properties remains contradictory and inconclusive. The objective of this study was to examine and propose an optimal biochar application amount in saline alkali soil considering their impact on soil physical and hydraulic properties. A three-year field experiment was conducted in the saline-alkali soils under plastic film-mulched drip irrigation in Xinjiang, China. The studied physical and hydraulic properties included bulk density, soil porosity, saturated soil water content (θ), permanent wilting point (PWP), field capacity (FC), plant available water (PAW), spatial distribution of soil water content, planar soil water storage (PSWS), and soil evaporation. The treatments included biochar application amounts of 0 (CK), 10 (B10), 50 (B50), and 100 t ha (B100) in 2018. Additional two treatments with 25 t ha (B25) and 30 t ha (B30) were added in 2019 and 2020, respectively. A four-parameter Gaussian function was fitted to the single-peak curves of the studied hydraulic properties vs. biochar application amounts to determine the most optimal biochar application amount. The results indicated that: (1) All of the biochar treatments significantly decreased bulk density and increased soil porosity over CK; (2) B10 and B25 treatments significantly increased θ, FC, PAW, PWP, and PSWS of root zones in the film-mulched zones over CK, but reverse results were observed in the B50 and B100 treatments; (3) Daily and cumulative soil evaporation were increased in no mulch zones of all biochar treatments over CK; (4) A dose of 21.9 t ha was recommended as the most optimal biochar application amount for improving physical and hydraulic properties of saline-alkali soil. This research provided useful information on biochar application amounts for improving physical and hydraulic properties in saline-alkali soil.
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http://dx.doi.org/10.1016/j.scitotenv.2020.144802DOI Listing
June 2021

Impacts of land-use changes on the variability of microbiomes in soil profiles.

J Sci Food Agric 2021 Feb 11. Epub 2021 Feb 11.

Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin,, China.

Background: The conversion of arable land to grassland and/or forested land is a common strategy of restoration because the development of plant communities can inhibit the erosion of soil, increase biodiversity and improve associated ecosystem services. The vertical profiles of microbial communities, however, have not been well characterized and their variability after land conversion is not well understood. We assessed the effects of the conversion of arable land (AL) to grassland (GL) and forested land (FL) on bacterial communities as old as 29 years in 0-200-cm profiles of a Chinese Mollisol.

Results: The soil in AL has been a stable ecosystem and changes in the assembly of soil microbiomes tended to be larger in the topsoil. The soil properties and microbial biodiversity of arable land were larger following revegetation and reforestation. The conversion caused a more complex coupling among microbes, and negative interactions and average connectivity were stronger in the 0-20-cm layers in GL and in the 20-60-cm layers in FL. The land use dramatically influenced the assembly of the microbial communities more in GL than AL and FL. The bacterial diversity was an important component of soil multinutrient cycling in the profiles and microbial functions were not as affected by changes in land use.

Conclusion: The spatial variation of the microbiomes provided critical information on below-ground soil ecology and the ability of the soil to provide crucial ecosystem services. © 2021 Society of Chemical Industry.
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http://dx.doi.org/10.1002/jsfa.11150DOI Listing
February 2021

Comparison of Heating Strategies on Soil Water Measurement Using Actively Heated Fiber Optics on Contrasting Textured Soils.

Sensors (Basel) 2021 Feb 1;21(3). Epub 2021 Feb 1.

School of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada.

The actively heated fiber optics (AHFO) technique has the potential to measure soil water at high spatial and temporal resolutions, and thus it can bridge the measurement gap from point to large scales. However, the availability of power might restrict its use, since high power is required to heat long fiber optic cables under field conditions; this can be a challenge for long-term soil water monitoring under field conditions. This study investigated the performance of different heating strategies (power intensity and heating duration) on soil water measurement by the AHFO technique on three different textured soils. Different heating strategies: high power-short pulses (20 Wm-3 min), low power-short pulses (10 Wm-3 min, 5 Wm-3 min, 2.5 Wm-3 min) and low power-long pulses (10 Wm-5 min, 5 Wm-10 min, 2.5 Wm-15 min) were tested using laboratory soil columns. The study compared the sensitivity of the thermal response, NT to volumetric water content (VWC) and the predictive error of different heating strategies and soils. Results of this study showed that the sensitivity of NT increased and the predictive error decreased with increasing power intensity, irrespective of the soil type. Low power-short heat pulses such as 5 Wm-3 min and 2.5 Wm-3 min produced high predictive errors, RMSE of 5-6% and 6-7%, respectively. However, extending the heating duration was effective in reducing the error for both 10 and 5 Wm power intensities, but not for the 2.5 Wm. The improvement was particularly noticeable in 5 Wm -10 min; it reduced the RMSE by 1.5% (sand and clay loam) and 2.73% (sandy loam). Overall, the results of this study suggested that extending the heating duration of 10 and 5 Wm power intensities can improve the sensitivity of the thermal response and predictive accuracy of the estimated soil water content (SWC). The results are particularly important for field applications of the AHFO technique, which can be limited by the availability of high power, which restricts the use of 20 Wm. For example, 5 Wm-10 min improved the predictive accuracy to 3-4%, which has the potential to be used for validating soil water estimations at satellite footprint scales. However, the effects of diurnal temperature variations should also be considered, particularly when using low power intensity such as 5 Wm in surface soils under field conditions.
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http://dx.doi.org/10.3390/s21030962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867044PMC
February 2021

In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths.

Sensors (Basel) 2021 Jan 10;21(2). Epub 2021 Jan 10.

School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada.

The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 mm between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.
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http://dx.doi.org/10.3390/s21020447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826571PMC
January 2021

Seasonal Dynamics of Leaf Stoichiometry of : A Case Study From Yangguan Wetland, Dunhuang, China.

Plants (Basel) 2020 Oct 6;9(10). Epub 2020 Oct 6.

College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China.

Leaf stoichiometry can enhance our understanding of leaf elements' (C, N and P) concentrations and their corresponding ratios in an ecosystem with seasonal environment changes. This study quantified the seasonal dynamics of leaf stoichiometry of from Yangguan wetland, Dunhuang, China as a case study example. The leaf C concentration (LC) of changed between seasons and was 392.26 (g×kg), 417.35 (g×kg) and 392.58 (g×kg) in spring, summer and autumn, respectively. Leaf N and P concentrations (LN and LP) were 23.49 (g×kg), and 17.54 (g×kg) and 5.86 (g×kg), and 1.00 (g×kg), 0.75 (g×kg) and 0.16 (g×kg), respectively, in the three seasons. The maximum (77.68) and the minimum values (17.00) of LC:LN were observed in the autumn and spring, respectively. Seasonal variations in LC:LP also showed a similar trend, with the greatest value of 3015.91 in autumn and the lowest value of 429.39 in spring. However, the highest (45.67) and the lowest values (24.18) of LN:LP were observed in autumn and summer, respectively, indicating that the growth of was mainly affected by P. Based on these results, it can be concluded that adopted a competition strategy during the early growth stage but took on a defense life strategy at the late growth stage to cope with various environments.
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http://dx.doi.org/10.3390/plants9101323DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7600640PMC
October 2020

Long-term application of fertilizer and manures affect P fractions in Mollisol.

Sci Rep 2020 09 9;10(1):14793. Epub 2020 Sep 9.

Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 138 Haping Rd, Harbin, 150081, People's Republic of China.

Application of phosphorus (P), a major plant nutrient, as fertilizer is critical to maintain P level for crop production and yield in most cultivated soils. While, it may impact the dynamics, limited studies have examined the long-term effects of fertilization on P fractions in a soil profile in Mollisol. A long-term field experiment was conducted at the State Key Experimental Station of Agroecology of the Chinese Academy of Sciences in Hailun county, Heilongjiang Province, China. A sequential fractionation procedure was used to determine the effect of fertilizer (types) treatments including no fertilizer (CK), chemical fertilizer (NPK), chemical fertilizer plus straw (NPK + S) and pig manure (OM) on fractions of P and their distribution within 0-100 cm soil profiles. Unlike CK treatment, the long-term application of fertilizers increased the concentration and accumulation of total and available P in 0-20 and 0-40 cm soil depths than deeper soils, respectively. The phosphorus activity coefficient (PAC) ranged from 1.5 to 13.8% within 0-100 cm soil depth. The largest PAC value was observed under OM treatment at 0-40 cm soil depth and under NPK + S treatment at 40-100 cm soil depth. The Ca-P and Ca-P concentrations increased significantly by 0.5-7.5 times and 0.5-10.4 times, respectively in OM treatment with the largest value in 0-40 cm soil depth over CK treatment. The Al-P concentration under NPK + S and OM treatments increased throughout the soil profile. The OM treatment increased all Po concentrations in the 0-40 cm soil depth, while NPK and NPK + S treatments increased labile organic P, moderately labile organic P, and highly stable organic P in the 0-20 cm soil depth. Thus, the application of fertilizer and straw, or organic manure may enhance inorganic and organic P pool in a Mollisol in Northeast China. Thus, organic manure application in the subsoil as a potential P source and their impact should be considered in developing management practices and policies regarding nutrient management.
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http://dx.doi.org/10.1038/s41598-020-71448-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481193PMC
September 2020

Phage Types of 01 Biotype ElTor Strains Isolated from India during 2012-2017.

J Glob Infect Dis 2020 Apr-Jun;12(2):94-100. Epub 2020 May 22.

Division of Bacteriology, ICMR - National Institute of Cholera and Enteric Diseases, Kolkata, West Bengal, India.

Background: Cholera is a primordial disease caused by which existed from centuries in different parts of the world and still shows its periodic, endemic and epidemic presence. Thousands of cholera cases are reported from different parts of India and the disease remains endemic throughout the year. At present, we do not have enough knowledge about the phenotypic nature of the circulating strains in this part of the world.

Objectives: This study was carried out over a period of 6 years with the aim defer with the changes in the prevalence and distribution of biotypes, serotypes and phage types of clinical isolates from various endemic regions of the country to determine phenotypic characteristics of the circulating strains and also to predict the attributes of cholera strains responsible for causing significant outbreaks in future.

Materials And Methods: A total of 1882 O1 isolates from different cholera endemic areas of India were included in this study. strains which were identified as O1 biotype ElTor further analyzed for serotype and phage types using the standard methodologies. Polyvalent O1 and monospecific Inaba and Ogawa antisera were used for serotyping. A panel of five phages of Basu and Mukherjee phage typing scheme and five phages from the new phage typing scheme were used for phage typing analysis following standard methodology.

Results: Maximum numbers of strains were isolated from cholera-endemic states like Gujarat and Maharashtra. All the isolates were confirmed as O1 biotype ElTor and majority of them were serotype Ogawa (93.2%). New phage typing scheme resulted in almost 100% typeable V. cholerae O1 strains included in this study and phage type 27 was the predominant type. Although 80% of the strains used in this study were sensitive to all the vibrio phages, S5 phage was found most efficient in lysing cholera strains indicating its broader host range.

Conclusion: The current study identified phage type 27 as the most dominant type and serotype Ogawa was found continuous in circulation throughout the year which has caused recent cholera outbreaks in India during the past years. Phage sensitivity data propose an alternative cost-effective approach to prevent cholera outbreak by therapeutic uses of typing phages irrespective of origin or clonality of the strains.
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http://dx.doi.org/10.4103/jgid.jgid_42_19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7384690PMC
May 2020

Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China.

Sensors (Basel) 2020 May 12;20(10). Epub 2020 May 12.

College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China.

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.
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http://dx.doi.org/10.3390/s20102757DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7285483PMC
May 2020

Comparison of spectral and spatial-based approaches for mapping the local variation of soil moisture in a semi-arid mountainous area.

Sci Total Environ 2020 Jul 31;724:138319. Epub 2020 Mar 31.

School of Environmental Sciences, University of Guelph, Canada. Electronic address:

Accurate information on soil moisture (SM) is critical in various applications including agriculture, climate, hydrology, soil and drought. In this paper, various predictive relationships including regression (Multiple Linear Regression, MLR), machine learning (Random Forest, RF; Triangular regression, Tr) and spatial modeling (Inverse Distance Weighing, IDW and Ordinary kriging, OK) approaches were compared to estimate SM in a semi-arid mountainous watershed. In developing predictive relationship, Remote Sensing datasets including Landsat 8 satellite imagery derived surface biophysical characteristic, ASTER digital elevation model (DEM) derived surface topographical characteristic, climatic data recorded at the synoptic station and in situ SM data measured at Landsat 8 overpass time were utilized, while in spatial modeling, point-based SM measurements were interpolated. While 70%(calibration set) of the measured SM data were used for modeling, 30%(validation set) were used to evaluate modeling accuracy. Finally, the SM uncertainty maps were created for different models based on a bootstrapping approach. Among the environmental parameter sets, land surface temperature (LST) showed the highest impact on the spatial distribution of SM in the region at all dates. Mean R(RMSE) between measured and modeled SM on three dates obtained from the MLR, RF, IDW, OK, and Tr models were 0.70(1.97%), 0.72(1.92%), 0.59(2.38%), 0.59(2.27%) and 0.71(1.99%), respectively. The results showed that RF and IDW produced the highest and lowest performance in SM modeling, respectively. Generally, the performance of RS-based models was higher than interpolation models for estimating SM due to the influence from combination of topographic parameters and surface biophysical characteristics. Modeled SM uncertainty with different models varies in the study area. The highest uncertainty in SM modeling was observed at the north part of the study area where the surface heterogeneity is high. Using RS data increased the accuracy of SM modeling because they can capture the surface biophysical characteristics and topographical properties heterogeneity.
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http://dx.doi.org/10.1016/j.scitotenv.2020.138319DOI Listing
July 2020

Socio-ecological determinants on spatio-temporal changes of groundwater in the Yellow River Basin, China.

Sci Total Environ 2020 Aug 4;731:138725. Epub 2020 May 4.

Department of Natural Resources Sciences, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada.

The spatio-temporal complexity of groundwater storage change is a result of interconnected impact of socio-ecological factors. Previous research indicates several socio-ecological factors (e.g. human extraction, land cover change, and climate change) that may result in groundwater depletion. However, we seldom have empirical studies that provide spatio-temporally explicit information on the main drivers among these factors that determine regional groundwater change. This research explored a spatio-temporally explicit understanding on the socio-ecological determinants on the changes of groundwater storage in the Yellow River Basin (YRB) of north China. We selected this basin because the spatial heterogeneity of this basin complicates the relationship between socio-ecological factors and groundwater resources, whose changes would in turn fundamentally affect the socio-ecological system in the YRB. We collected annual (time resolution) data between 2003 and 2016 (time scope) with 1° × 1° grid (space resolution) about 18 social-ecological factors that might affect groundwater storage change in the YRB (space scope). Using this data and groundwater storage information from Gravity Recovery and Climate Experiment database, we determined best predictors, highly-performed predictive models, and dominant drivers for temporal and spatial changes of groundwater storage. Temporal changes of groundwater in the YRB between 2003 and 2016 were mainly contributed by anthropogenic factors, including population density, plantation, and irrigation water consumption over time. The spatial groundwater change across the YRB was determined by both the geographical location (e.g. indicated by longitude) and urbanization level (e.g. indicated by the domestic and industrial water consumption). The knowledge about socio-ecological determinants on groundwater dynamics in space and time in the YRB can help determine main levers to control regional change of groundwater storage and assist in a sustainable use of groundwater resource.
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http://dx.doi.org/10.1016/j.scitotenv.2020.138725DOI Listing
August 2020

Emergence of Novel Coronavirus and COVID-19: whether to stay or die out?

Crit Rev Microbiol 2020 Mar 13;46(2):182-193. Epub 2020 Apr 13.

Division of Bacteriology, ICMR-National institute of Cholera and Enteric Diseases, Kolkata, India.

The last century has witnessed several assaults from RNA viruses, resulting in millions of death throughout the world. The 21st century appears no longer an exception, with the trend continued with escalated fear of SARS coronavirus in 2002 and further concern of influenza H5N1 in 2003. A novel influenza virus created the first pandemic of the 21st century, the pandemic flu in 2009 preceded with the emergence of another deadly virus, MERS-CoV in 2012. A novel coronavirus "SARS-CoV-2" (and the disease COVID-19) emerged suddenly, causing a rapid outbreak with a moderate case fatality rate. This virus is continuing to cause health care providers grave concern due to the lack of any existing immunity in the human population, indicating their novelty and lack of previous exposure. The big question is whether this novel virus will be establishing itself in an endemic form or will it eventually die out? Endemic viruses during circulation may acquire mutations to infect naïve, as well as individual with pre-existing immunity. Continuous monitoring is strongly advisable, not only to the newly infected individuals, but also to those recovered individuals who were infected by SARS-CoV-2 as re-infection may lead to the selection of escape mutants and subsequent dissemination to the population.
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http://dx.doi.org/10.1080/1040841X.2020.1739001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7157960PMC
March 2020

Spatio-temporal evolution of agricultural land use change drivers: A case study from Chalous region, Iran.

J Environ Manage 2020 May 3;262:110326. Epub 2020 Mar 3.

School of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada. Electronic address:

Increasing global population put tremendous pressure on limited land resources and has led to changes in land use. Changing land use patterns are of great importance in environmental studies and critical for land use management decision-making. Thus, it is important to understand the relationship between the pattern of land use/cover change and its drivers in a region to initiate specific planning and management decisions. The objective of this study was to quantify changes in land use from a case study area in Chalous, Iran and identify geophysical characteristics (e.g., slope, elevation and soil) and socio-economic (e.g., population density, tourist industry, accessibility and land price) elements of the changes. This will help assess the impact on the trends in changing land use in the study area and elsewhere with similar conditions. In this study, multi-temporal satellite images, Geographic Information Systems (GIS), and semi-structured interviews were used to evaluate the spatio-temporal dynamics of land use/cover changes over a 20-year period (1996-2016). Supervised classification based on the maximum likelihood algorithm was used to obtain the land use classes with an overall accuracy of 87%, 92% and 93.50%, and kappa coefficients of 82.87%, 88.66% and 89.98% for 1996, 2006 and 2016, respectively. Change detection analysis also showed that agricultural land was reduced by 11.09% and built up areas were increased by 15.89% over the period of 20 years. The comprehensive evaluation of geophysical and socio-economic driving forces and the local characteristics of farmers indicated that economic factor and the tourist industry mainly contributed to the change from agricultural lands to built-up areas. In addition, a lack support from the government and the agricultural ministry also contributed to these conversions. Thus, investigation of the complexity of socio-ecological relationships and interaction with land use change drivers are necessary for sustainable planning and development and policy decisions.
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http://dx.doi.org/10.1016/j.jenvman.2020.110326DOI Listing
May 2020

Improved digital soil mapping with multitemporal remotely sensed satellite data fusion: A case study in Iran.

Sci Total Environ 2020 Jun 7;721:137703. Epub 2020 Mar 7.

School of Environmental Sciences, University of Guelph, Canada. Electronic address:

Modeling and mapping of soil properties are critical in many environmental, climatic, ecological and hydrological applications. Digital soil mapping (DSM) techniques are now commonly applied to predict soil properties with limited data by developing predictive relationships with environmental covariates. Most studies derive covariates from a digital elevation model (named static covariates). Many works also include single-day remotely sensed satellite imagery. However, multitemporal satellite images can capture information about soil properties over time and bring additional information in predicting soil properties in DSM. We refer to covariates derived from multitemporal satellite images as dynamic covariates. The objective of this study was to assess the performance of DSM when using terrain derivatives (static covariates), single-date remotely sensed satellite indices (limited dynamic covariates), multitemporal satellite indices (dynamic covariates), and combinations of terrain derivatives and satellite indices (covariate fusion) as covariates in predicting soil properties and estimating uncertainty. Three soil properties are considered in this study: organic carbon (OC), sand content, and calcium carbonate equivalent (CCE). Inclusion of single and/or multitemporal remotely sensed satellite indices improved the prediction of soil properties over traditionally used terrain indices. Significant improvements were observed in the prediction of soil properties using two models, Cubist and random forest (RF). The increase in the R values for Cubist and RF were 126% and 78% for OC, 110% and 54% for sand, and 87% and 32% for CCE. The RMSE decreased by 34% and 27% for OC, 25% and 12% for sand, and 39% and 19% for CCE, when compared to the terrain indices only model. This also reduced the uncertainty of estimation and mapping. These clearly showed the advantage of using multitemporal satellite data fusion rather than simply using static terrain indices for DSM of soil properties to deliver a great potential in improving soil modeling and mapping for many applications.
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http://dx.doi.org/10.1016/j.scitotenv.2020.137703DOI Listing
June 2020

Potential groundwater recharge from deep drainage of irrigation water.

Sci Total Environ 2020 May 3;716:137105. Epub 2020 Feb 3.

School of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1, Canada. Electronic address:

Knowledge of soil water dynamics in the deep vadose zone provides valuable information on the temporal and spatial variability of groundwater recharge. However, semi-arid climate can complicate how the input of water, such as irrigation, can contribute to potential groundwater recharge. This study assessed the recharge rates and their timing under irrigated cropland from a semi-arid region of northern Iran. A deep drainage (10 m) experiment was performed and in situ soil water content was measured to analyze the soil water dynamics and model hydraulic parameters using HYSDRUS-1D. The best parameters selected from inverse parameter optimization were used to calibrate model and estimate the long-term (20-year) average groundwater recharge and the influence of the root zone, unsaturated zone and the time scale on the recharge processes. The simulated annual flux ranged from 24 mm to 268 mm (mean of 110 mm) at 2-m depth and ranged between 26 mm to 207 mm (mean of 95 mm) at the 10-m depth. High fluxes, observed between December and April, may be the result of greater precipitation combined with the irrigation return flow. The May-October period showed a gradual decrease in flux at the depth of 2 m. At the depth of 10 m, the flux showed some continuity (base flux) during the long-term recharge simulation. In total, 12.7% of the input water contributed to the recharge of the groundwater. The annual soil water fluxes were almost similar irrespective of depth below the root zone and the flux rates did not show any clear relation between the different components of the water budget at any depth. This approach improved our understanding of the recharge process in the deep vadose zone in a semiarid region and can help for the development of effective management of groundwater resources.
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http://dx.doi.org/10.1016/j.scitotenv.2020.137105DOI Listing
May 2020

Phosphorus loss assessment tools: a review of underlying concepts and applicability in cold climates.

Environ Sci Pollut Res Int 2020 Feb 9;27(4):3794-3802. Epub 2019 Dec 9.

School of Environmental Sciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.

Identifying critical source areas (CSAs) of a watershed by phosphorus (P) loss assessment tools is essential for optimal placement of beneficial management practices (BMPs) to address diffuse P pollution. However, lack of significant progress in tackling diffuse P pollution could be, in part, associated with inefficacy of P loss assessment tools for accurately identifying CSAs. Phosphorus loss assessment tools have been developed to simulate P loss from the landscape where runoff is mainly driven by rainfall events. Therefore, they may underperform in cold climates where the land is often frozen during winter and runoff is dominated by snowmelt. This paper (i) reviews the strengths and weaknesses of current P loss assessment tools and their underlying assumptions in simulating soil P dynamics and P transfer to runoff, and (ii) highlights a number of challenges associated with modeling P transfer from agricultural land to surface waters in cold climates. Current P loss assessment tools do not appear to fully represent hydrological and biogeochemical processes responsible for P loss from CSAs, particularly in cold climates. Effort should be made to develop P loss assessment tools that are capable of considering P dynamics through the landscape as a result of abiotic perturbations that are common in cold climates, predicting runoff and P movement over frozen/partially frozen soils, and considering material-P connectivity between landscape and surface waters. Evaluating P loss assessment tools with water quality data is necessary to ensure such modifications result in improved identification of CSAs.
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http://dx.doi.org/10.1007/s11356-019-06800-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7024057PMC
February 2020

Rotavirus activates a noncanonical ATM-Chk2 branch of DNA damage response during infection to positively regulate viroplasm dynamics.

Cell Microbiol 2020 03 17;22(3):e13149. Epub 2019 Dec 17.

Division of Virology, National Institute of Cholera and Enteric Diseases, Kolkata, West Bengal, India.

Surveillance for maintaining genomic pristineness, a protective safeguard of great onco-preventive significance, has been dedicated in eukaryotic cells to a highly conserved and synchronised signalling cascade called DNA damage response (DDR). Not surprisingly, foreign genetic elements like those of viruses are often potential targets of DDR. Viruses have evolved novel ways to subvert this genome vigilance by twisting canonical DDR to a skewed, noncanonical response through selective hijacking of some DDR components while antagonising the others. Though reported for many DNA and a few RNA viruses, potential implications of DDR have not been addressed yet in case of infection with rotavirus (RV), a double-stranded RNA virus. In the present study, we aimed at the modulation of ataxia telangiectasia mutated (ATM)-checkpoint kinase 2 (Chk2) branch of DDR in response to RV infection in vitro. We found activation of the transducer kinase ATM and its downstream effector Chk2 in RV-SA11-infected cells, the activation response being maximal at 6-hr post infection. Moreover, ATM activation was found to be dependent on induction of the upstream sensor Mre11-Rad50-Nbs1 (MRN) complex. Interestingly, RV-SA11-mediated maximal induction of ATM-Chk2 pathway was revealed to be neither preceded by occurrence of nuclear DNA damage nor transduced to formation of damage-induced canonical nuclear foci. Subsequent investigations affirmed sequestration of MRN components as well as ATM-Chk2 proteins away from nucleus into cytosolic RV replication factories (viroplasms). Chemical intervention targeting ATM and Chk2 significantly inhibited fusion and maturation of viroplasms leading to attenuated viral propagation. Cumulatively, the current study describes RV-mediated activation of a noncanonical ATM-Chk2 branch of DDR skewed in favour of facilitated viroplasm fusion and productive viral perpetuation.
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http://dx.doi.org/10.1111/cmi.13149DOI Listing
March 2020

Updated information on soil salinity in a typical oasis agroecosystem and desert-oasis ecotone: Case study conducted along the Tarim River, China.

Sci Total Environ 2020 May 21;716:135387. Epub 2019 Nov 21.

Xinjiang Common University Key Lab of Smart City and Environmental Stimulation, College of Resource and Environmental Sciences, Xinjiang University, Urumqi 830046, China. Electronic address:

Precise and spatially explicit regional estimates of soil salinity are necessary to efficiently management and utilise limited land and water resources. Despite advances achieved in remote sensing over the past century, knowledge about the distribution and severity of soil salinization in economically important areas, such as oasis agroecosystems and desert-oasis ecotones (OADoE), is currently limited. An example of an area is southern Xinjiang, where the OADoE has a high anthropogenic influence. This study was conducted with the aim of mapping soil salinity in typical OADoE using remote sensing and machine learning techniques (Cubist and Random Forest, RF). A range of covariates was obtained from the multi-temporal Landsat-8 operational land imager (OLI) satellite for the period from 2013 to 2018. The values of coefficients of determination (R), Lin's concordance correlation coefficient, root mean square error, and relative root mean squared error values, were 0.78, 0.87, 9.59, and 0.76, respectively, for the Cubist and 0.78, 0.86, 9.79, and 0.78, respectively, for RF models. The slope of the linear fitting equation was higher for the Cubist model (0.75) than for RF (0.69). The explanatory power of Cubist and RF for soil salinity variation were 33.22% and 31.41% in the agroecosystem, and 72.25% and 71.66% in desert-oasis ecotone, respectively. For the agroecosystem, the range of the predicted values for 89.13% (Cubist) and 84.78% (RF) of sample was controlled within the same observational range at an interval of 0-5 dS m. Compared to single-year data (from 2013 to 2018), the ability to account for model spatial variability in soil salinity based on multi-year Landsat images was increased by 16%-35%. According to the variable importance evaluation, soil-related indices are the most important predictor variables, followed by vegetation, topography, landform, and land use, with relative importance values of 60%, 21%, 16%, and 3%, respectively. The predicted map was also broadly consistent with those obtained for Xinjiang in the Harmonized World Soil Database (HWSD) from the second national soil survey of China conducted from 1984 to 1997. The results also showed that the average value of the study area is 8.10 dS m based on the Cubist-based map whereas that of the HWSD is 10.60 dS m, this implied that the overall salinity level has reduced by 23.58%. The methodological framework presented covers all prediction process steps and has considerable potential to be used in future soil salinity mapping at large scales for other similar region as OADoEs. The map derived from the Cubist/RF model revealed more detailed variation information about spatial distribution of the soil salinity compared to HWSD, and can further assist with decision-making when planning and utilising on existing soil and water resources in OADoEs.
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http://dx.doi.org/10.1016/j.scitotenv.2019.135387DOI Listing
May 2020

Current challenges: from the path of "original antigenic sin" towards the development of universal flu vaccines.

Int Rev Immunol 2020 9;39(1):21-36. Epub 2019 Nov 9.

Bacteriology, ICMR-National Institute of Cholera and Enteric Diseases, Kolkata, India.

Annual flu led by influenza viruses is contemplated to be one of the foremost global health challenges due to its rapid spread leading to the life-threatening epidemic or pandemic. An enormous number of people die due to flu and its associated intricacies every year. Annual vaccination is considered to be the gold standard strategy to protect the individual from acquiring infection and further decimation, although recent estimates suggest that overall flu vaccine effectiveness was within 19% to 53% in last five years. A significant weakness of current vaccination is its inability to protect an individual from different or mutant flu strain. Host immune system performs a vital role during natural infection or after vaccination leading to influenza-specific immunities. Previous imprints of common flu or vaccination may alter the outcomes of the current vaccination. Current flu vaccine regime does not consider the host immune status before vaccination. Irrespective of the previous influenza exposure history or prior flu vaccination, individual get flu vaccination based on WHO recommendation with selected strains which may be the reason why induction of broad immunities does not transpire with their testimonial. Over the last few decades, scientific research had identified the role of preexisting immunities on vaccination or natural infection outcome. In this review, we are proposing the concept of personalized flu vaccines depending on individual immune status. We will also discuss why individual was unable to induce broader immunities to protect itself from diverse influenza viruses and how we can accomplish that goal with the current findings.
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http://dx.doi.org/10.1080/08830185.2019.1685990DOI Listing
June 2020

Characterising dryland salinity in three dimensions.

Sci Total Environ 2019 Sep 6;682:190-199. Epub 2019 May 6.

Institute of Agricultural Remote Sensing and Information Technology Application, College of Environment and Resource Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address:

Due to frequent salt migration and large spatial variability within soil profiles, salinity characterisation by traditional drilling sampling methods is time-consuming and labour-intensive. Thus, it is necessary to develop monitoring technology and three-dimensional (3D) characterisation methods for rapid, non-invasive, and accurate soil salinity measurement. This study presents a new framework combining sensor technology and an inversion algorithm to characterise 3D soil salinity. Four typical land-use types (natural desert, natural vegetation, apple orchard, and winter wheat farmland) in the Aksu region of southern Xinjiang were surveyed and apparent conductivity (ECa) data were recorded at depths of 0.75 m and 1.50 m. ECa data were converted to electrical conductivity and salinity characterisation was conducted following U.S. Salinity Laboratory recommendations. Ordinary Kriging interpolation was used to map the spatial distribution and an iterative inversion model was used to map the vertical distribution of soil salinity. Model parameters were adjusted several times and the accuracy of different inversion algorithms was compared to obtain the best inversion effect. As a result, the Multilevel Orthogonal Inversion model was developed to characterise 3D soil salinity for different land-use types. Due to crop activities including irrigation, managed land use types (apple orchard and winter wheat plots) typically exhibited weaker salinity than natural systems (desert and vegetation plots) but greater spatial variability overall. The proposed framework combining EM (electromagnetic) sensing and the 3D inversion algorithm can effectively characterise and visualise soil salinity for the entire soil profile, which is important for land evaluation and improvement.
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http://dx.doi.org/10.1016/j.scitotenv.2019.05.037DOI Listing
September 2019

Small alarmones (p)ppGpp regulate virulence associated traits and pathogenesis of Salmonella enterica serovar Typhi.

Cell Microbiol 2019 08 9;21(8):e13034. Epub 2019 May 9.

Division of Clinical Medicine, ICMR-National Institute of Cholera and Enteric Diseases, Kolkata, India.

How Salmonella enterica serovar Typhi (S. Typhi), an important human pathogen, survives the stressful microenvironments inside the gastrointestinal tract and within macrophages remains poorly understood. We report here that S. Typhi has a bonafide stringent response (SR) system, which is mediated by (p)ppGpp and regulates multiple virulence-associated traits and the pathogenicity of the S. Typhi Ty2 strain. In an iron overload mouse model of S. Typhi infection, the (p)ppGpp (Ty2ΔRelAΔSpoT) strain showed minimal systemic spread and no mortality, as opposed to 100% death of the mice challenged with the isogenic wild-type strain. Ty2ΔRelAΔSpoT had markedly elongated morphology with incomplete septa formation and demonstrated severely attenuated motility and chemotaxis due to the loss of flagella. Absence of the Vi-polysaccharide capsule rendered the mutant strain highly susceptible to complement-mediated lysis. The phenotypes of Ty2ΔRelAΔSpoT was contributed by transcriptional repression of several genes, including fliC, tviA, and ftsZ, as found by reverse transcriptase quantitative polymerase chain reaction and gene complementation studies. Finally, Ty2ΔRelAΔSpoT had markedly reduced invasion into intestinal epithelial cells and significantly attenuated survival within macrophages. To the best of our knowledge, this was the first study that addressed SR in S. Typhi and showed that (p)ppGpp was essential for optimal pathogenic fitness of the organism.
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http://dx.doi.org/10.1111/cmi.13034DOI Listing
August 2019

Identifying hotspots and representative monitoring area of groundwater changes with time stability analysis.

Sci Total Environ 2019 Jun 25;667:419-426. Epub 2019 Feb 25.

Department of Natural Resources Sciences, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, QC, Canada H9X 3V9.

Groundwater is a most accessible freshwater resource for human beings, and it is increasingly important as an alternative to surface water under the threat of climate change. However, its complex spatio-temporal dynamic remains unattended from management perspective. Past studies on groundwater management were stalled by a relative dearth of high-quality data and a lack of synthetic analysis on both spatial and temporal information. Thanks to NASA's launch of Gravity Recovery and Climate Experiment (GRACE) satellite mission, our study has solved these two problems by innovatively applying time stability analysis to GRACE-based groundwater data. Taking the Yellow River Basin (YRB) as an example, we employed GRACE satellite data to obtain monthly changes of groundwater tables from Jan. 2003 to Dec. 2016 in 1.0-degree grid of spatial resolution. Then we identified hotspots (which indicated severe groundwater declines and fluctuations over time) and representative monitoring areas (which stably represented the spatial average over time) using time stability analysis. Time stability employs multiple coefficients to identify the spatial relations between local variables and global variables overtime, thus showing the overall effect of spatial-wise and temporal-wise factors but never used in groundwater studies before. Based on this innovative method, we further identified management categories across the YRB using multivariate cluster analysis. As a result, the YRB has been divided into five zones for different management strategies. We identified the hotspots in west-most and east-most areas of the YRB, where we suggest a strengthened groundwater protections and risk response system. The northern part of the middle reach in the YRB was also identified as the representative monitoring areas. With these knowledge, decision-makers can have a clearer regional plan for groundwater protection, monitoring, and risk response system. This new method enables a quick decision on the prioritized areas for different groundwater management strategies while not losing the scope of spatio-temporal heterogeneity.
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http://dx.doi.org/10.1016/j.scitotenv.2019.02.294DOI Listing
June 2019

Spatio-temporal dynamics of groundwater storage changes in the Yellow River Basin.

J Environ Manage 2019 Apr 21;235:84-95. Epub 2019 Jan 21.

Department of Natural Resources Sciences, McGill University, 21111, Lakeshore Road, Ste-Anne-de-Bellevue, QC, H9X 3V9, Canada.

Groundwater is an important source of water supply and ecosystem resilience. However, limited information on spatio-temporal dynamics makes a complete assessment of available groundwater resources difficult, impairing sustainable water management. The Gravity Recovery and Climate Experiment mission (GRACE) has recently made this possible. In this study, we used the Yellow River Basin (YRB) as a model system to explore the use of spatio-temporal dynamics information about groundwater change derived from the GRACE datasets for regional groundwater management. While there was an overall decreasing trend (R = 0.57) during the last 14 year, the groundwater storage over the whole basin decreased significantly (p < 0.0001, slope changed from -0.0137 cm/month to -0.0684 cm/month) since 2010 (2010-2016) and showed stronger fluctuations than the time before (2003-2009). The range and the standard deviation of groundwater storage change also increased in recent years especially after 2010. At the basin scale, locations which exhibited higher variabilities (large standard deviation) over time generally showed radical decrease of groundwater storage. The results indicated that groundwater depletion may reduce the aquifers' function for ecosystem resilience, thus posing risks to the ecosystem of the YRB and threatening its people to climate change and extreme events. Despite the overall trend, the changes were heterogeneous if looking at finer scales: spatially, there was a gradual decline of storage from west to east (e.g. the change in December 2016 was -3.6, -9.1 and -25.8 cm for the upper, middle and lower reach, respectively); and temporally, the timeseries among the reaches were significantly different (p = 0.023). Our hotspot analysis also indicated the heterogeneity in groundwater decline across the basin and through the time. Additionally, it showed that human factors (e.g. groundwater consumption) become dominant in determining the groundwater change pattern over climatic variations. We therefore call for more attention to groundwater in developing sustainable water management strategies and suggest a closer cooperation of neighboring provinces in the YRB to have a reciprocal strategic plan for water regulation, protection, and management.
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http://dx.doi.org/10.1016/j.jenvman.2019.01.016DOI Listing
April 2019

Greenhouse gas flux with reflooding of a drained salt marsh soil.

PeerJ 2018 15;6:e5659. Epub 2018 Nov 15.

Department of Geography, McGill University, Montreal, Quebec, Canada.

Salt marshes are highly effective carbon (C) sinks and bury more C per square meter annually than any other ecosystem. Reclamation and anthropogenic impacts, however, have resulted in extensive losses of salt marshes. Carbon credits can be generated and sold by restoring marshes, but only if C sequestration and net reductions in greenhouse gases (GHG) are reliably quantified. Restored marshes, however, may exhibit different patterns of GHG emissions than natural marshes and it is possible that they could temporarily become sources of NO even in the usually N-limited estuarine environment. Research on short-term GHG flux following salt marsh restoration is limited to studies of two restored marshes which examined GHG flux more than six months after the return of tidal flooding. Here we report on a laboratory experiment in which soil cores collected from a drained agricultural marsh on the St. Lawrence Estuary were flooded with estuary water. Gas flux measurements immediately after flooding revealed small increases in NO and CH, but a large decline in CO yielding, from a climatic perspective, a net cooling effect over the observation period. In addition to restoring the land's capacity to sequester C once a marsh develops, returning tidal flooding thus appears to have the added benefit of stemming large ongoing C losses. With more than 400 km of undeveloped dykeland, Eastern Canada is well positioned to restore large sections of marsh and contribute to reducing atmospheric CO concentrations.
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http://dx.doi.org/10.7717/peerj.5659DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240435PMC
November 2018

Identification of significant coronary artery disease in patients with non-ST segment elevation acute coronary syndrome by myocardial strain analyses using three dimensional speckle tracking echocardiography.

Echocardiography 2018 12 30;35(12):1988-1996. Epub 2018 Oct 30.

Department of Cardiology, National Heart Foundation Hospital & Research Institute, Dhaka, Bangladesh.

Background: Speckle-tracking imaging is a novel method for assessing left ventricular function and ischemic changes. This study aimed to predict the presence of significant coronary artery stenosis in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) by 3D strain analysis using speckle tracking echocardiography (3DSTE) at rest.

Methods: This cross-sectional study included a total 60 patients with NSTE-ACS who underwent 3DSTE immediately prior to coronary angiography. Subsequently, patients undergone coronary angiogram (CAG) and divided into two groups; group- I: significant stenosis (n = 36), group-II: non-significant stenosis (n = 24).

Results: Global peak systolic longitudinal strain (GPSLS), circumferential strain (CS), area strain (AS), and radial strain (RS) were obtained successfully in 60 patients. All strain parameters were significantly reduced in patient group of significant stenosis. Receiver operating characteristic (ROC) curve analysis demonstrated that GPSLS could effectively detect patients with significant stenosis (area under ROC curve = 0.840, 95% CI = 0.735-0.945). GPSLS with a cutoff value of -13.50% showed good sensitivity and specificity for predicting significant stenosis (sensitivity 88.9% and specificity 70.8%).

Conclusion: Global peak systolic longitudinal strain using 3D speckle tracking echocardiography at rest was significantly lower in patients with significant stenosis and might be useful for identifying patients with a significant stenosis with good degree of sensitivity and specificity.
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http://dx.doi.org/10.1111/echo.14181DOI Listing
December 2018

Corrigendum to "Identifying localized and scale-specific multivariate controls of soil organic matter variations using multiple wavelet coherence" [Sci. Total Environ. 643 (2018) 548-558].

Sci Total Environ 2019 02 19;649:1661-1662. Epub 2018 Sep 19.

Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China.

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http://dx.doi.org/10.1016/j.scitotenv.2018.09.065DOI Listing
February 2019

Identifying localized and scale-specific multivariate controls of soil organic matter variations using multiple wavelet coherence.

Sci Total Environ 2018 Dec 23;643:548-558. Epub 2018 Jun 23.

Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China. Electronic address:

Environmental factors have shown localized and scale-dependent controls over soil organic matter (SOM) distribution in the landscape. Previous studies have explored the relationships between SOM and individual controlling factors; however, few studies have indicated the combined control from multiple environmental factors. In this study, we compared the localized and scale-dependent univariate and multivariate controls of SOM along two long transects (northeast, NE transect and north, N transect) from China. Bivariate wavelet coherence (BWC) between SOM and individual factors and multiple wavelet coherence (MWC) between SOM and factor combinations were calculated. Average wavelet coherence (AWC) and percent area of significant coherence (PASC) were used to assess the relative dominance of individual and a combination of factors to explain SOM variations at different scales and locations. The results showed that (in BWC analysis) mean annual temperature (MAT) with the largest AWC (0.39) and PASC (16.23%) was the dominant factor in explaining SOM variations along the NE transect. The topographic wetness index (TWI) was the dominant factor (AWC = 0.39 and PASC = 20.80%) along the N transect. MWC identified the combination of Slope, net primary production (NPP) and mean annual precipitation (MAP) as the most important combination in explaining SOM variations along the NE transect with a significant increase in AWC and PASC at different scales and locations (e.g. AWC = 0.91 and PASC = 58.03% at all scales). The combination of TWI, NPP and normalized difference vegetation index (NDVI) was the most influential along the N transect (AWC = 0.83 and PASC = 32.68% at all scales). The results indicated that the combined controls of environmental factors on SOM variations at different scales and locations in a large area can be identified by MWC. This is promising for a better understanding of the multivariate controls in SOM variations at larger spatial scales and may improve the capability of digital soil mapping.
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http://dx.doi.org/10.1016/j.scitotenv.2018.06.210DOI Listing
December 2018