Estimation of underwater visibility in coastal and inland waters using remote sensing data

An optical method is developed to estimate water transparency (or underwater visibility) in terms of Secchi depth (Z _sd ), which follows the remote sensing and contrast transmittance theory. The major factors governing the variation in Z _sd , namely, turbidity and length attenuation coefficient (1/(c + K _d ), c = beam attenuation coefficient; K _d  = diffuse attenuation coefficient at 531 nm), are obtained based on band rationing techniques. It was found that the band ratio of remote sensing reflectance (expressed as (R _rs (443) + R _rs (490))/(R _rs (555) + R _rs (670)) contains essential information about the water column optical properties and thereby positively correlates to turbidity. The beam attenuation coefficient (c) at 531 nm is obtained by a linear relationship with turbidity. To derive the vertical diffuse attenuation coefficient (K _d ) at 531 nm, K _d (490) is estimated as a function of reflectance ratio (R _rs (670)/R _rs (490)), which provides the bio-optical link between chlorophyll concentration and K _d (531). The present algorithm was applied to MODIS-Aqua images, and the results were evaluated by matchup comparisons between the remotely estimated Z _sd and in situ Z _sd in coastal waters off Point Calimere and its adjoining regions on the southeast coast of India. The results showed the pattern of increasing Z _sd from shallow turbid waters to deep clear waters. The statistical evaluation of the results showed that the percent mean relative error between the MODIS-Aqua-derived Z _sd and in situ Z _sd values was within ±25%. A close agreement achieved in spatial contours of MODIS-Aqua-derived Z _sd and in situ Z _sd for the month of January 2014 and August 2013 promises the model capability to yield accurate estimates of Z _sd in coastal, estuarine, and inland waters. The spatial contours have been included to provide the best data visualization of the measured, modeled (in situ), and satellite-derived Z _sd products. The modeled and satellite-derived Z _sd values were compared with measurement data which yielded RMSE = 0.079, MRE = ?0.016, and R ²  = 0.95 for the modeled Z _sd and RMSE = 0.075, MRE = 0.020, and R ²  = 0.95 for the satellite-derived Z _sd products.     

Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis

Trend analysis of stream constituent concentrations requires adjustment for exogenous variables like discharge because concentrations often have variable relations with flow. To remove the influence of flow on stream water quality data, an accurate characterization of the relationship between the constituent and streamflow is needed. One popular method, locally weighted regression (LOESS), provides an effective means for flow-adjusting concentrations. The LOESS fit can be tailored to the data via the smoothing parameter (f), so that the user can avoid overfitting or oversmoothing the data. However, it is a common practice to use a single f value when flow-adjusting water quality data for trend analysis. This study provides a robust, automated method for determining the optimal f value (f_opt) for each dataset via an iterative K-fold cross-validation procedure that minimizes prediction error in LOESS. The method is developed by analyzing datasets of seven different constituents across 17 sites (119 datasets total) from a stream monitoring program in northwest Arkansas (USA). We recommend using 10 iterations of 10-fold cross-validation (10?×?10 CV) in order to select f_opt when flow-adjusting water quality data with LOESS. The use of a default f value did not produce different trend interpretations for the data used here; however, the proposed approach may be helpful in other water quality studies which employ similar statistical fitting methods. Additionally, we provide an implementation of the method in the R statistical computing environment.     

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m³ s^?1, representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size?>?0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5 %. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20 %) compared to group 2 (16.90 to 45.55 %). Two Fisher’s linear discriminant functions, F ₁ and F ₂, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F ₁?=??9.405?+?4232.119?×?A???1795.805?×?B?+?281.224?×?C, and F ₂?=??2.842?+?2725.137?×?A???1307.688?×?B?+?231.353?×?C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m³ s^?1, respectively. The model correctly predicts 88.9 and 100.0 % of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8 % are correctly classified. The model predicts that 31.4 % of the model domain areas consist of high-sand mass composition areas and the remaining 68.6 % comprise low-sand mass composition areas.     

Dynamic Modeling of Biological Treatment of Leachates from Solid Wastes

Leachates from municipal solid wastes are liquids formed by organic and inorganic components suitable for biological treatment. In biological treatment plants, prediction of the output parameter value due to dynamic variation is essential. A dynamic model based on ASM1 has been applied for prediction of effluent COD value at real scale, using three different composition leachates. Tuning between dynamic variables and predicted parameter is tested for a correct proposal of the model. Dynamic model predicts correctly fluctuations in the output COD value and tempers dynamism caused by variation of temperature and biomass concentration in the case of high organic loaded leachates. Kinetic parameters Y _H and K _s are fixed to solve the model, and dynamic variables μ _H and X_BH are changing in time. μ_H,max is obtained in simulation (0.37–1.82 day^?1) for minimum error between predicted values and experimental data. μ_H,max value is much lower compared with the value for domestic wastewater treatment due to lower biodegradability of leachate.     

Stochastic modeling approaches based on neural network and linear–nonlinear regression techniques for the determination of single droplet collection efficiency of countercurrent spray towers

This paper presents a new mathematical model and a two-layer neural network approach to predict the single droplet collection efficiency (SDCE), η _d, of countercurrent spray towers. SDCE values were calculated using MATLAB^® algorithm for 205 different artificial scenarios given in a large range of operating conditions. Theoretical results were compared with outputs obtained from a two-layer neural network and DataFit^® scientific software. The predicted model developed from linear–nonlinear regression analysis and network outputs agreed with the theoretical data, and all predictions proved to be satisfactory with a correlation coefficient of about 0.921 and 0.99, respectively. By using the proposed model, iterations between Reynolds number (Re), drag coefficient (C _D) and terminal velocity values (v _T) were neglected for a large range of operating conditions. SDCE values were also obtained speedily and practically for five main operating inputs used in the model.     

A regional algorithm to model mesozooplankton biomass along the southwestern Bay of Bengal

A three-dimensional regression analysis attempted to model mesozooplankton (MSP) biomass using sea surface temperature (SST) and chlorophyll-a (Chl-a). The study was carried out from January 2014 to July 2015 in the southwestern Bay of Bengal (BoB) and sampling was carried out on board Sagar Manjusha and Sagar Purvi. SST ranged from 26.2 to 33.1 °C while Chl-a varied from 0.04 to 6.09 μg L^?1. During the course of the study period, there was a weak correlation (r?= 0.32) between SST and Chl-a statistically. MSP biomass varied from 0.42 to 9.63 mg C m^?3 and inversely related with SST. Two kinds of approaches were adopted to develop the model by grouping seasonal datasets (four seasonal algorithms) and comprising all datasets (one annual algorithm). Among the four functions used (linear, paraboloid, the Lorentzian and the Gaussian functions), paraboloid model was best suited. The best seasonal and annual algorithms were applied in the synchronous MODIS-derived SST and Chl-a data to estimate the MSP biomass in the southwestern BoB. The modelled MSP biomass was validated with field MSP biomass and the result was statistically significant, showing maximum regression coefficient for the seasonal algorithms (R²?=?0.60; p?=?0.627; α?= 0.05), than the annual algorithm (R²?=?0.52; p?=?0.015, α?=?0.05).     

Seasonal variations and source profile of <Emphasis Type="Italic">n</Emphasis>-alkanes in particulate matter (PM<Subscript>10</Subscript>) at a heavy traffic site,Delhi

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m³) in PM₁₀ was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m³, along with the diagnostic tools has been calculated. The values of CPI₁, CPI₂, and CPI₃ for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C _max were at C₂₅ and C₂₇. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m³) than during the summer season (56.3 ± 1.1 ng/m³).     

Soil tillage erosion estimated by using magnetism of soils—a case study from Bulgaria

A detailed field and laboratory study on small 0.84-ha test site of agricultural land near Sofia (Bulgaria) has been carried out in order to test the applicability of magnetic methods in soil erosion estimation in the particular case of strongly magnetic parent material. Field measurements of magnetic susceptibility were carried out with grid size of 6 m, resulting in 258 data points. Bulk soil material was gathered from 78 grid points. Natural, non-disturbed soil section was sampled near the agricultural field for reference profile of complete undisturbed soil. Surface susceptibility measurements reveal well-defined maxima down slope which, however, cannot be assigned directly to a certain depth interval, corresponding with susceptibilities along the non-disturbed soil profile. This is caused by the high magnetic susceptibility of the lithogenic coarse-grained magnetic fraction. Non-uniqueness is resolved by using magnetic susceptibility of coarse (1 mm >?d?> 63 μm) and fine (d < 63 μm) mechanical fractions and the parameter Δχ = 100*(χ _coarse???χ _fine)/χ _bulk (%). It shows increased values in the C-horizon of undisturbed soil profile, which corresponds to a certain part of the studied area. After the application of an empirical model to predict the values of magnetic parameter after tillage homogenization and removal of soil material from the surface, the amount of soil loss is estimated.     

Antibiotic resistance and plasmid profiling of <Emphasis Type="Italic">Vibrio</Emphasis> spp. in tropical waters of Peninsular Malaysia

Vibrio species isolated from four different sampling stations in the west coast of Peninsular Malaysia were screened for their antimicrobial resistance and plasmid profiles. A total of 138 isolates belonging to 15 different species were identified. Vibrio campbellii, V. parahaemolyticus, V. harveyi, and V. tubiashii were found to predominance species at all stations. High incidence of erythromycin, ampicillin, and mecillinam resistance was observed among the Vibrio isolates. In contrast, resistance against aztreonam, cefepime, streptomycin, sulfamethoxazole, and sulfonamides was low. All the Vibrio isolates in this study were found to be susceptible to imipenem, norfloxacin, ofloxacin, chloramphenicol, trimethoprim/sulfamethoxazole, and oxytetracycline. Ninety-five percent of the Vibrio isolates were resistant to one or more different classes of antibiotic, and 20 different resistance antibiograms were identified. Thirty-two distinct plasmid profiles with molecular weight ranging from 2.2 to 24.8 kb were detected among the resistance isolates. This study showed that multidrug-resistant Vibrio spp. were common in the aquatic environments of west coast of Peninsular Malaysia.     

Pollution characteristics and ecological risk assessment of heavy metals in three land-use types on the southern Loess Plateau,China

The accumulation of heavy metals in agricultural soils has been the subject of great concern because these metals have the potential to be transferred to soil solutions and subsequently accumulate in the food chain. To study the persistence of trace metals in crop and orchard soils, representative surface soil samples were collected from terrace farmland that had been cultivated for various numbers of years (3, 8, 12, 15, and >20 years), terrace orchard land that had been cultivated for various numbers of years (4, 7, 10, 12, 15, 18, 25, and >30 years), and slope farmland with various gradients (3°, 5°, 8°, 12°, 15°, and 25°) and analyzed for heavy metals (As, Cr, Cu, Hg, Ni, and Zn). These samples were collected from Nihegou catchment of Chunhua county in the southern Loess Plateau of China. The six heavy metals demonstrated different trends with time or gradient in the three land-use types. The Cu and Zn contents of the soil were higher than the referee background values of the loessal soil, and the contents of Cr and Ni, and especially those of As and Hg, were lower. Cu was the only heavy metal that just met the Grade III Environmental Quality Standard for Soils of China, while the others reached grade I. Cu and Hg were considered contaminant factors and Hg was a moderate potential ecological risk factor in the catchment. Of the sites investigated, 89.5% fell into the category with a low degree of contamination (C _d ) and rest were moderate, while all three land-use types had low potential ecological risk (RI). Changes of C _d and RI were consistent with the cultivated time in the terrace farmland and terrace orchard land. Values of RI increased while C _d decreased with the increasing of slope gradient in the slope farmland. Evaluating the ecological risk posed by heavy metals using more soil samples in a larger study area is necessary on the Loess Plateau of China.     

Epilithic diatom assemblages and their relationships with environmental variables in the Nilüfer Stream Basin,Bursa, Turkey

Patterns of epilithic diatom species distribution in relation to environmental variables from 12 sampling sites on the main stream and some of its tributaries in the Nilüfer Stream Basin were determined using multivariate statistical techniques. The stream basin has been heavily influenced by anthropogenic effects. The upper part of the basin that is distant from pollution sources mostly has a spring water quality, while the lower part where the stream flows through the urban area and receives domestic and industrial wastewater has a quite low quality. Ordination techniques using both diatom taxa and 21 environmental variables revealed non- to slightly polluted upper basin sites and highly polluted lower basin sites along the stream. The results showed that the stream catchment is polluted gradually from upstream to downstream and that most of the downstream sites have very low water quality especially in summer months. A total of 134 epilithic diatom taxa belonging to 50 genera were recorded for 12 sample sites. Partial CCA results indicated that water temperature (T), discharge (Q), and total phosphorus (TP) were the most important variables affecting the distribution of diatom species. Unpolluted or slightly polluted upper basin sites were dominated by Achnanthidium minutissimum, Cocconeis placentula var. euglypta, Gomphonema olivaceum, and Navicula tripunctata. Highly polluted lower basin sites were characterized by high levels of organic and inorganic matters and low dissolved oxygen (DO) values. Species widespread in the highly polluted lower basin sites such as Nitzschia umbonata, Nitzschia amphibia, Nitzschia capitellata, Nitzschia palea, Nitzschia paleacea, Luticola mutica, and Stephanodiscus niagarae were mostly related to pollution indicator variables such as ammonium nitrogen (NH₄ ⁺–N), sodium (Na⁺), total phosphorus (TP), and total organic matter (TOM).     

Relative proportions of <Emphasis Type="Italic">E. coli</Emphasis> and <Emphasis Type="Italic">Enterococcus spp.</Emphasis> may be a good indicator of potential health risks associated with the use of roof harvested rainwater stored in tanks

A total of 285 water samples were collected from 71 roof harvested rainwater tanks from four villages in different provinces over a two-year (2013–2014) period during the early (October to December) and late (January to March) rainy season. Water quality was evaluated based on Escherichia coli, faecal coliforms and Enterococcus spp. prevalence using the IDEXX Quanti-Tray quantification system. Real-Time PCR was used to analyse a subset of 168 samples for the presence of Shigella spp., Salmonella spp. and E. coli virulence genes (stx1, stx2 and eaeA). Escherichia coli were detected in 44.1% of the samples, Enterococcus spp. in 57.9% and faecal coliforms in 95.7%. The most prevalent E. coli concentrations in harvested rainwater were observed in 29.1% of samples and 22.5% for Enterococcus spp. and, were within 1–10 cfu/100 ml and 10–100 cfu/100 ml, respectively, whereas those for faecal coliforms (36.6%) were within 100–1000 cfu/100 ml. On average 16.8% of the samples had neither E. coli nor Enterococcus spp. detected, while 33.9% had only Enterococcus spp. and 23.7% had only E. coli. E. coli and Enterococcus spp. were detected together in 25.5% of the samples. Evaluation of samples for potential pathogenic bacteria showed all tested samples to be negative for the Shigella spp. ipaH gene, while five tested positive for Salmonella ipaB gene. None of the samples tested positive for the stx1 and stx2 genes, and only two tested positive for the eaeA gene. These findings are potentially useful in the development of a simplified risk assessment strategy based on the concentrations of indicator bacteria.     

Variation in biochemical constituents and master elements in common seaweeds from Alexandria Coast,Egypt, with special reference to their antioxidant activity and potential food uses: prospective equations

Biochemical constituents and master elements (Pb, Cr, Cd, Fe, Cu, Zn, Hg, B, Al, SO₄ ^2?, Na, K, Li, Ca, Mg, and F) were investigated in six different seaweed species from Abu Qir Bay in the Egyptian Mediterranean Sea coast. The moisture level ranged from 30.26% in Corallina mediterranea to 77.57% in Padina boryana. On dry weight basis, the ash contents varied from 25.53% in Jania rubens to 88.84% in Sargassum wightii. The protein contents fluctuated from 8.26% in S. wightii to 28.01% in J. rubens. Enteromorpha linza showed the highest lipids (4.66%) and carbohydrate contents (78.95%), whereas C. mediterranea had the lowest lipid (0.5%), and carbohydrate contents (38.12%). Chlorophylls and carotenoid contents varied among the species. Total antioxidant capacity of the tested green seaweeds had the highest activities followed by brown and red seaweeds which had a similar trend of phenol and tannins contents. High reducing power was observed in all tested seaweeds extract except Ulva lactuca. Brown species had the highest amount of elements followed by red and green seaweeds. Notably, SO₄ ^2? recorded the highest level in the tested green species (108.05 mg/g dry weight (DW)). The Ca/Mg and K/Na ratios reflected highly significant difference between seaweed species. This study keeps an eye on 29 parameters and by applying stepwise multiple regression analysis, prospective equations have been set to describe the interactions between these parameters inside seaweeds. Accordingly, the tested seaweeds can be recommended as a source of healthy food with suitable ion quotient and estimated daily intake values.     

Diversity of crude oil-degrading bacteria and alkane hydroxylase (<Emphasis Type="Italic">alkB</Emphasis>) genes from the Qinghai-Tibet Plateau

The aim of this study was to survey the response of the microbial community to crude oil and the diversity of alkane hydroxylase (alkB) genes in soil samples from the Qinghai-Tibet Plateau (QTP). The enrichment cultures and clone libraries were used. Finally, 53 isolates and 94 alkB sequences were obtained from 10 pristine soil samples after enrichment at 10 °C with crude oil as sole carbon source. The isolates fell into the phyla Proteobacteria, Actinobacteria, and Bacteroidetes, with the dominance of Pseudomonas and Acinetobacter. The composition of degraders was different from polar habitats where Acinetobacter sp. is not a predominant responder of alkane degradative microbial communities. Phylogenetic analysis showed that the alkB genes from isolates and enrichment communities formed eight clusters and mainly related with alkB genes of Pseudomonas, Rhodococcus, and Acinetobacter. The alkB gene diversity in the QTP was lower than marine environments and polar soil samples. In particular, a total of 10 isolates exhibiting vigorous growth with crude oil could detect no crude oil degradation-related gene sequences, such as alkB, P450, almA, ndoB, and xylE genes. The Shannon-Wiener index of the alkB clone libraries from the QTP ranged from 1.00 to 2.24 which is similar with polar pristine soil samples but lower than that of contaminated soils. These results indicated that the Pseudomonas, Acinetobacter, and Rhodococcus genera are the candidate for in situ bioremediation, and the environment of QTP may be still relatively uncontaminated by crude oil.     

Microphytobenthic biomass,species composition and environmental gradients in the mangrove intertidal region of the Andaman Archipelago,India

Monthly sampling in mangrove intertidal sediments of Andaman Archipelago was carried out during a 1-year study (January to December, 2013) in order to analyse the spatial and temporal distribution of microphytobenthos (MPB) and MPB biomass (sediment chlorophyll-a (chl-a)) in the surficial layer 0–1 cm. The MPB community was mainly composed of diatoms. The MPB biomass concentration in surface sediment (0–1 cm) ranged from 0.7 to 16.98 μg cm^?3. Population density of benthic diatoms varied from 78 to 224 ind cm^?3. This study identified 41 diatom taxa (27 pennate diatoms, 14 centric diatoms) in the sediment, and among all the diatom taxa, we distinguished few true planktonic species—Coscinodiscus centralis, Coscinodiscus marginatus, Leptocylindricus danicus, Planktoniella sol, Thalassiosira decipiens, Thalassionema nitzschioides and Thalassiothrix longissima. Overall, a high percentage of diatoms were pennate (81%) as opposed to centric. Based on benthic diatom abundance, species composition and distribution, MPB assemblages of sampling stations were grouped into two distinct clusters: one with St. 1 and St. 3 and another one with St. 2 and St. 4. Canonical correspondence analysis (CCA) revealed seasonality as the most important factor determining variability in diatom species composition among sampling sites. There was a distinct seasonal pattern in MPB biomass distribution and benthic diatom cell density during monsoon and post-monsoon seasons. Our results suggest that among various physical and chemical variables studied, greater levels of overlying water nutrients and sediment textures significantly correlated and were conducive factors for MPB. This is the first detailed study on the MPB from these mangrove sediments, providing benchmark data for future studies about these remote groups of Andaman and Nicobar Islands.     

Physicochemical properties associated with the presence of <Emphasis Type="Italic">Burkholderia pseudomallei</Emphasis> in small ruminant farm water supplies in Peninsular Malaysia

Burkholderia pseudomallei causes melioidosis, a life-threatening infection in both humans and animals. Water is an important reservoir of the bacteria and may serve as a source of environmental contamination leading to infection. B. pseudomallei has an unusual ability to survive in water for a long period. This paper investigates physicochemical properties of water associated with the presence of B. pseudomallei in water supply in small ruminant farms in Peninsular Malaysia. Physicochemical properties of water samples taken from small ruminant farms that included temperature, pH, dissolved oxygen (DO₂), optical density (OD), and chemical oxygen demand (COD) were measured after which the samples were cultured for B. pseudomallei. Multivariable logistic regression model revealed that slightly acidic water pH and higher COD level were significantly associated with the likelihood of the B. pseudomallei presence in the water.     

Investigation of polar organic chemical integrative sampler (POCIS) flow rate dependence for munition constituents in underwater environments

Munition constituents (MC) are present in aquatic environments throughout the world. Potential for fluctuating release with low residence times may cause concentrations of MC to vary widely over time at contaminated sites. Recently, polar organic chemical integrative samplers (POCIS) have been demonstrated to be valuable tools for the environmental exposure assessment of MC in water. Flow rate is known to influence sampling by POCIS. Because POCIS sampling rates (R_s) for MC have only been determined under quasi-static conditions, the present study evaluated the uptake of 2,4,6-trinitrotoluene (TNT), RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine), and 2,4- and 2,6-dinitrotoluenes (DNT), by POCIS in a controlled water flume at 7, 15, and 30 cm/s in 10-day experiments using samplers both within and without a protective cage. Sampling rate increased with flow rate for all MC investigated, but flow rate had the strongest impact on TNT and the weakest impact on RDX. For uncaged POCIS, mean R_s for 30 cm/s was significantly higher than that for 7 cm by 2.7, 1.9, 1.9, and 1.3 folds for TNT, 2,4-DNT, 2,6-DNT, and RDX, respectively. For all MC except RDX, mean R_s for caged POCIS at 7 cm/s were significantly lower than for uncaged samplers and similar to those measured at quasi-static condition, but except for 2,6-DNT, no caging effect was measured at the highest flow rate, indicating that the impact of caging on R_s is flow rate-dependent. When flow rates are known, flow rate-specific R_s should be used for generating POCIS-derived time-averaged concentrations of MC at contaminated sites.     

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter ??_t,τ, beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.     

Mapping aboveground woody biomass using forest inventory,remote sensing and geostatistical techniques

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m?×?31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10–40, 40–70 and >70 % of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m³ ha^?1. The total growing stock of the forest was found to be 2,024,652.88 m³. The AGWB ranged from 143 to 421 Mgha^?1. Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE)?=?42.25 Mgha^?1) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha^?1 respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha^?1. The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.     

The distribution and enrichment characteristics of copper in soil and <Emphasis Type="Italic">Phragmites australis</Emphasis> of Liao River estuary wetland

The aims of the present investigation were to reveal the distribution and enrichment characteristics of copper in soil and Phragmites australis of Liao River estuary wetland. The concentrations of copper in root, stem, leaf, and ear of Phragmites australis as well as in soil were determined to study the absorption capacity of copper by wild Phragmites australis of Liao River estuary wetland. The study was carried out at test pool of the Shenyang Agricultural University, and the experimental materials (soil, irrigating water and Phragmites australis) were derived from Liao River estuary wetland. The concentrations of copper in soil and Phragmites australis were 16.4441 to 49.0209 mg/kg and 0.8621 to 89.5524 mg/kg, respectively. The results indicated that the enrichment coefficients of copper in different tissues of Phragmites australis changed with the growth of Phragmites australis. The results revealed that the enrichment coefficients of copper in the whole Phragmites australis were greater than 1 at each growing stage of the Phragmites australis. The results also showed that the transfer coefficients of Phragmites australis to copper changed with the growth of Phragmites australis. The results revealed that the Phragmites australis had a good removal effect on copper from soil and had some characteristics of copper hyperaccumulator.