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.     

<Emphasis Type="Italic">Synechococcus</Emphasis> production and grazing loss rates in nearshore tropical waters

Temporal variation of Synechococcus, its production (μ) and grazing loss (g) rates were studied for 2 years at nearshore stations, i.e. Port Dickson and Port Klang along the Straits of Malacca. Synechococcus abundance at Port Dickson (0.3–2.3 × 10⁵ cell ml^?1) was always higher than at Port Klang (0.3–7.1 × 10⁴ cell ml^?1) (p < 0.001). μ ranged up to 0.98 day^?1 (0.51 ± 0.29 day^?1), while g ranged from 0.02 to 0.31 day^?1 (0.15 ± 0.07 day^?1) at Port Klang. At Port Dickson, μ and g averaged 0.47 ± 0.13 day^?1 (0.29–0.82 day^?1) and 0.31 ± 0.14 day^?1 (0.13–0.63 day^?1), respectively. Synechococcus abundance did not correlate with temperature (p > 0.25), but nutrient and light availability were important factors for their distribution. The relationship was modelled as log Synechococcus = 0.37Secchi ? 0.01DIN + 4.52 where light availability (as Secchi disc depth) was a more important determinant. From a two-factorial experiment, nutrients were not significant for Synechococcus growth as in situ nutrient concentrations exceeded the threshold for saturated growth. However, light availability was important and elevated Synechococcus growth rates especially at Port Dickson (F = 5.94, p < 0.05). As for grazing loss rates, they were independent of either nutrients or light intensity (p > 0.30). In nearshore tropical waters, an estimated 69 % of Synechococcus production could be grazed.     

Large-scale carbon stock assessment of woody vegetation in tropical dry deciduous forest of Sathanur reserve forest,Eastern Ghats,India

Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research, especially in the Eastern Ghats. Therefore, the present study was aimed to quantify the carbon storage in woody vegetation (trees and lianas) on large scale (30, 1 ha plots) in the dry deciduous forest of Sathanur reserve forest of Eastern Ghats. Biomass of adult (≥10 cm DBH) trees was estimated by species-specific allometric equations using diameter and wood density of species whereas in juvenile tree population and lianas, their respective general allometric equations were used to estimate the biomass. The fractional value 0.4453 was used to convert dry biomass into carbon in woody vegetation of tropical dry forest. The mean aboveground biomass value of juvenile tree population was 1.86 Mg/ha. The aboveground biomass of adult trees ranged from 64.81 to 624.96 Mg/ha with a mean of 245.90 Mg/ha. The mean aboveground biomass value of lianas was 7.98 Mg/ha. The total biomass of woody vegetation (adult trees + juvenile population of trees + lianas) ranged from 85.02 to 723.46 Mg/ha, with a mean value of 295.04 Mg/ha. Total carbon accumulated in woody vegetation in tropical dry deciduous forest ranged from 37.86 to 322.16 Mg/ha with a mean value of 131.38 Mg/ha. Adult trees accumulated 94.81% of woody biomass carbon followed by lianas (3.99%) and juvenile population of trees (1.20%). Albizia amara has the greatest biomass and carbon stock (58.31%) among trees except for two plots (24 and 25) where Chloroxylon swietenia contributed more to biomass and carbon stock. Similarly, Albizia amara (52.4%) showed greater carbon storage in juvenile population of trees followed by Chloroxylon swietenia (21.9%). Pterolobium hexapetalum (38.86%) showed a greater accumulation of carbon in liana species followed by Combretum albidum (33.04%). Even though, all the study plots are located within 10 km radius, they show a significant spatial variation among them in terms of biomass and carbon stocks which could be attributed to variation in anthropogenic pressures among the plots as well as to changes in tree density across landscapes. Total basal area of woody vegetation showed a significant positive (R ² = 0.978; P = 0.000) relationship with carbon storage while juvenile tree basal area showed the negative relationship (R ² = 0.4804; P = 0.000) with woody carbon storage. The present study generates a large-scale baseline data of dry deciduous forest carbon stock, which would facilitate carbon stock assessment at a national level as well as to understand its contribution on a global scale.     

Effects of land conversion from native shrub to pistachio orchard on soil erodibility in an arid region

Land-use change through degrading natural vegetation for agricultural production adversely affects many of soil properties particularly organic carbon content of soils. The native shrub land and grassland of Gaziantep-Adiyaman plateau that is an important pistachio growing eco-region have been cleared to convert into pistachio orchard for the last 50 to 60 years. In this study, the effects of conversion of natural vegetation into agricultural uses on soil erodibility have been investigated. Soil samples were collected from surface of agricultural fields and adjacent natural vegetation areas, and samples were analyzed for some soil erodibility indices such as dispersion ratio (DR), erosion ratio (ER), structural stability index (SSI), Henin’s instability index (I _s ), and aggregate size distribution after wet sieving (AggSD). According to the statistical evaluation, these two areas were found as different from each other in terms of erosion indices except for I _s index (P < 0.001 for DR and ER or P < 0.01 for SSI). In addition, native shrub land and converted land to agriculture were found different in terms of AggSD in all aggregate size groups. As a contrary to expectations, correlation tests showed that there were no any interaction between soil organic carbon and measured erodibility indices in two areas. In addition, significant relationships were determined between measured variables and soil textural fractions as statistical. These obtaining findings were attributed to changing of textural component distribution and initial aggregate size distribution results from land-use change in the study area. Study results were explained about hierarchical aggregate formation mechanism.     

<Emphasis Type="Italic">Mazzaella laminarioides</Emphasis> and <Emphasis Type="Italic">Sarcothalia crispata</Emphasis> as possible bioindicators of heavy metal contamination in the marine coastal zone of Chile

The suitability of Mazzaella laminarioides and Sarcothalia crispata as heavy metal biomonitors of Cd, Cu, Hg, Pb, and Zn was assessed by comparing bioaccumulation of these elements in different life stages and frond sizes in samples from three locations, San Vicente Bay (industrial area), Coliumo, and Quidico (the latter as a reference station), where different degrees of heavy metal pollution are recorded. Bioaccumulation and bioconcentration factors of Cd, Cu, Hg, Pb, and Zn were evaluated. The two macroalgae species showed similar patterns, with higher values of Cu, Hg, Pb, and Zn in polluted areas. M. laminarioides bioaccumulated higher concentrations of all metals assessed than S. crispata, independent of life stage and frond size. The results also showed significantly higher Cu, Hg, Pb, and Zn concentrations (p < 0.05) in water samples from San Vicente Bay than those measured in Coliumo and Quidico. Concentrations of Cd, Hg, Pb, and Zn in San Vicente Bay and Cd, Hg, and Pb in Coliumo and Quidico exceed the mean values considered to represent natural concentrations (Cu = 3.00 μg L^?1; Zn = 5.00 μg L^?1; Pb = 0.03 μg L^?1; Cd = 0.05 μg L^?1; Hg = 0.05 μg L^?1); however, the concentrations recorded do not cause negative effects on the growth and survival of macroalgae. The assessment of heavy metals bioaccumulated in M. laminarioides and S. crispata, particularly Hg, Pb, and Zn, offers a reliable approach for pollution assessment in rocky intertidal environments. Cu and Cd concentrations in seawater samples from San Vicente and Coliumo Bays were significantly higher than in those from Quidico (p value < 0.05); no significant differences in Cd concentrations were observed between San Vicente and Coliumo Bays (p < 0.05). Exceptionally, Cd is bioaccumulated at high levels independent of its availability in the water, thus reaching high concentrations in control areas. High concentrations of metals like Cu and Zn may limit or inhibit Cd uptake in macroalgae, since the transport channels are saturated by some metals, reducing the accumulation of others. These macroalgae species offer good potential for the development of suitable heavy metal pollution survey tools in rocky intertidal environments.     

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).     

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).     

Assessment of physicochemical parameters and prevalence of virulent and multiple-antibiotic-resistant <Emphasis Type="Italic">Escherichia coli</Emphasis> in treated effluent of two wastewater treatment plants and receiving aquatic <Emphasis Type="Italic">milieu</Emphasis> in Durban,South Africa

The poor operational status of some wastewater treatment plants often result in the discharge of inadequately treated effluent into receiving surface waters. This is of significant public health concern as there are many informal settlement dwellers (ISDs) that rely on these surface waters for their domestic use. This study investigated the treatment efficiency of two independent wastewater treatment plants (WWTPs) in Durban, South Africa and determined the impact of treated effluent discharge on the physicochemical and microbial quality of the receiving water bodies over a 6-month period. Presumptive Escherichia coli isolates were identified using biochemical tests and detection of the mdh gene via PCR. Six major virulence genes namely eae, hly, fliC, stx1, stx2, and rfbE were also detected via PCR while antibiotic resistance profiles of the isolates were determined using Kirby-Bauer disc diffusion assay. The physicochemical parameters of the wastewater samples ranged variously between 9 and 313.33 mg/L, 1.52 and 76.43 NTUs, and 6.30 and 7.87 for COD, turbidity, and pH respectively, while the E. coli counts ranged between 0 and 31.2?×?10³ CFU/ml. Of the 200 selected E. coli isolates, the hly gene was found in 28 %, fliC in 20 %, stx2 in 17 %, eae in 14 %, with stx1 and rfbE in only 4 % of the isolates. Notable resistance was observed toward trimethoprim (97 %), tetracycline (56 %), and ampicillin (52.5 %). These results further highlight the poor operational status of these WWTPs and outline the need for improved water quality monitoring and enforcement of stringent guidelines.     

Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions

Th aim of this study is to investigate spatio-temporal trends of dengue vector breeding and epidemic (disease incidence) influenced by climatic factors. The spatio-temporal (low-, medium-, and high-intensity periods) evaluation of entomological and epidemiological investigations along with climatic factors like rainfall (RF), temperature (T_max), relative humidity (RH), and larval indexing was conducted to develop correlations in the area of Lahore, Pakistan. The vector abundance and disease transmission trend was geo-tagged for spatial insight. The sufficient rainfall events and optimum temperature and relative humidity supported dengue vector breeding with high larval indices for water-related containers (27–37%). Among temporal analysis, the high-intensity period exponentially projected disease incidence followed by post-rainfall impacts. The high larval incidence that was observed in early high-intensity periods effected the dengue incidence. The disease incidence had a strong association with RF (r = 0.940, α = 0.01). The vector larva occurrence (r = 0.017, α = 0.05) influenced the disease incidence. Similarly, RH (r = 0.674, α = 0.05) and average T_max (r = 0.307, α = 0.05) also induced impact on the disease incidence. In this study, the vulnerability to dengue fever highly correlates with meteorological factors during high-intensity period. It provides area-specific understanding of vector behavior, key containers, and seasonal patterns of dengue vector breeding and disease transmission which is essential for preparing an effective prevention plan against the vector.     

The influence of chemical protection on the content of heavy metals in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) growing on the soil enriched with granular sludge

The presence of heavy metals in Triticum aestivum L. growing on the soil enriched with granular sludge after chemical protection was observed. The five variants of treatments using herbicide (Chwastox Turbo 340SL) and four fungicides (Topsin M 500SC, Amistar 250SC, Artea 330EC, and Falcon 460EC) were performed. On control and experimental plots, the concentration of Ni, Pb, Cr, and Cu in wheat leaves were in the range 0.32–0.99, 0.92–1.57, 0.89–6.31, and 7.08–12.59 mg/kg and in grains 0.03 to 0.11, 0.14–0.25, 0.11–0.76, and 1.06–1.46 mg/kg, respectively. The concentration of Pb in grain protected by MCPA and 2,4-D with thiophanate-methyl and azoxystrobin was higher than the maximum levels of 0.20 mg/kg D.M. The bioconcentration factor (BCF) differed and depended on chemical protection. The highest value of BCF was achieved for Cd. The statistical analysis showed a significant correlation between concentration of metals and quality parameters of wheat. One observed significant negative correlations between Ni/Zeleny sedimentation value (r = ?0.51) and between Pb/starch content (r = ?0.57). Positive correlations were observed between Cd/yield, the number of grains/ergosterol concentration (respectively, r = 0.41, r = 0.55, r = 0.56), and Zn/thousand grain weight (r = 0.50) at a p ≤ 0.05.     

Assessment of chlorine tolerance profile of <Emphasis Type="BoldItalic">Citrobacter</Emphasis> species recovered from wastewater treatment plants in Eastern Cape,South Africa

This present study assessed the chlorine tolerance of some Citrobacter species recovered from secondary effluents from the clarifiers of two wastewater treatment plants in the Eastern Cape, South Africa. The bacterial survival, chlorine lethal dose and inactivation kinetics at lethal doses were examined. Inactivation of the test bacteria (n = 20) at the recommended dose of 0.5 mg/l for 30 min exposure showed a progressive reduction in bacterial population from 4 to 5 log reduction and residuals ranged between 0.12 and 0.46 mg/l. The bactericidal activity of chlorine increased at higher dosages with a substantial reduction in viability of the bacteria and complete inactivation of the bacterial population at a lethal dose of 0.75 and 1.0 mg/l in 30 min. For the inactivation kinetics, bactericidal activity of chlorine increased with time showing a 3.67–5.4 log reduction in 10 min, 4.0–5.6 log reduction in 20 min and above 6.3 log reductions to complete sterilization of bacterial population over 30 min for all the entire test Citrobacter isolates used in this study. Furthermore, there was a strong correlation (R ² > 0.84) between bacteria inactivation and increase in contact time. This study appears to have provided support for laboratory evidence of bacterial tolerance to chlorine disinfection at current recommended dose (0.5 mg/l for 30 min), and chlorine concentration between 0.75 and 1.0 mg/l was found to have a better disinfecting capacity to check tolerance of Citrobacter species.     

Variation of phytoplankton assemblages of Kongsfjorden in early autumn 2012: a microscopic and pigment ratio-based assessment

Phytoplankton species distribution and composition were determined by using microscopy and pigment ratios in the Kongsfjorden during early autumn 2012. Variation in sea surface temperature (SST) was minimal and matched well with satellite-derived SST. Nutrients were generally limited. Surface phytoplankton abundance ranged from 0.21?×?10³ to 10.28?×?10³ cells L^?1. Phytoplankton abundance decreased with depth and did not show any significant correlation with chlorophyll a (chl a). Column-integrated phytoplankton cell counts (PCC) ranged from 94.3?×?10⁶ cells m^?2 (Kf4) to 13.7?×?10⁶ cells m^?2 (Kf5), while chl a was lowest at inner part of the fjord (6.3 mg m^?2) and highest towards the mouth (24.83 mg m^?2). Biomass from prymnesiophytes and raphidophytes dominated at surface and 10 m, respectively. The contribution of Bacillariophyceae to biomass was low. Generally, heterotrophic dinoflagellates were great in abundance (12.82 %) and ubiquitous in nature and were major contributors to biomass. Various chl pigments (chl b, chl c, phaeopigments (phaeo)) were measured to obtain pigment/chl a ratios to ascertain phytoplankton composition. Phaeo were observed only in inner fjord. Chl b:a ratios and microscopic observations indicated dominance of Chlorophyceae at greater depths than surface. Furthermore, microscopic observations confirmed dominance of chl c containing algae throughout the fjord. The study indicates that pigment ratios can be used as a tool for preliminary identification of major phytoplankton groups. However, under the presence of a large number of heterotrophic dinoflagellates such as Gymnodinium sp. and Gyrodinium sp., pigment signatures need to be supplemented by microscopic observations.     

Oil contamination in surface sediment of Anzali Wetland in Iran is primarily even carbon number <Emphasis Type="Italic">n</Emphasis>-alkanes

To determine the extent of oil contamination and biodegradation in Anzali Wetland of Iran, we examined aliphatic hydrocarbons in surface sediment of this area (n=20). Petroleum hydrocarbon levels (mean 1585 ± 1117; range 316 to 4358 μg g?¹ dry weight) were similar in value to reports from other highly contaminated areas, such as New York Bight, Saudi and Kuwaiti coasts of the Persian Gulf, and Dubai shorelines. Even carbon homologs dominated distribution of n-alkanes in surface sediment of Anzali, which is rarely reported elsewhere. Multiple factors used in our study point to petrogenic source for n-alkanes in Anzali Wetland. Anzali receives multiple industrial and agricultural runoffs from the surrounding area. Shipping industry and oil industry are responsible for a major portion of pollutants entering Anzali. Municipal wastewater discharges are another source of Anzali pollution. To determine why even carbon number n-alkanes predominate in Anzali, we examined the following indices: existence of unresolved complex mixtures (UCM), ratio of UCM to resolved alkanes (RA), ratio of low-molecular weight to high-molecular weight molecules, presence of degraded oil residue, high-relative biodegradation, and the degree of hydrocarbon weathering in the surface sediment of the area. Our findings corroborate with such predominance.     

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.     

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.     

Monitoring and measurement of microalgae using the first derivative of absorbance and comparison with chlorophyll extraction method

Monitoring of microalgae in water supplies and industrial applications are becoming increasingly important, yet there are few options available that are simple and accurate, and can provide real-time information. The present work illustrates a new method to determine the concentration of microalgae in water and wastewater using spectrophotometry and the first derivative of absorbance. Chlorella vulgaris was used as an indicator microalga, spiked in water samples representing a range of water qualities (distilled water, surface water, and wastewater), and correlations among C. vulgaris concentrations, absorbance, and the first derivative of absorbance measurements were investigated. In addition, detection limits were established and sensitivity analyses were carried out to determine the lowest C. vulgaris concentrations that can be confidently measured in different water matrices. Finally, the study compared the performance and detection limits of the spectrophotometry-based methods with the well-accepted chlorophyll extraction method. A strong linear relationship (R²?>?0.97) was found between C. vulgaris concentration and absorbance at 695 nm. Using the first derivative of absorbance improved C. vulgaris detection limits by reducing the effects of the background noise and interferences from other substances. The detection limits established using the first derivative method were 0.47, 0.56, and 1.96 mg TVS/L in distilled water, surface water, and wastewater, respectively. In comparison, the detection limits of the chlorophyll extraction method were found to be 19.6, 38.6, and 48.3 mg TVS/L in the same water matrices. These results indicate that first derivative of absorbance can be successfully used for monitoring of microalgae in surface waters and environmental samples as well as in bioreactors used for microalgae cultivation in industrial applications.     

Bioindicator responses and performance of plant species along a vehicular pollution gradient in western Himalaya

Loss of green cover, and increasing pollution is a prime global concern. The problem calls for screening of pollution-tolerant tree species that can be integrated into plantation drives. Recognizing this, the study analyzed bio-indicator responses and performance of commonly occurring plant species along a pollution gradient in western Himalaya. Based on distance from the road, three sites viz., highly polluted (HP), moderately polluted (MP), and least polluted (LP), were identified. From these sites, leaves of commonly occurring 26 tree species were collected and analyzed for dust accumulation, total chlorophyll, relative water content (RWC), ascorbic acid, and pH using standard protocols. Later, assessment of Air Pollution Tolerance Index (APTI) and Anticipated Performance Indices (API) was carried out. The results revealed variations in biochemical characteristics. The pH, RWC, and total chlorophyll increased with decreasing pollution while ascorbic acid increased with increasing pollution. Dust capturing potential of Ficus carica (1.191 mg/m²) and Toona ciliata (0.820 mg/m²) was relatively higher. Based on the results of APTI, Grevillea robusta was classified as tolerant. It scored significantly higher values (21.06, 21.19, and 19.61 in LP, MP, and HP sites, respectively). Quercus floribunda, G. robusta (68.75% each), Juglans regia (68.7%), and T. ciliata (62.50%) were good performers in HP sites. Acer caesium, Betula utilis, and Morus alba that had low API scores (43.75%) were predicted as poor performers. Thus, G. robusta, Q. floribunda, J. regia, T. ciliata, and F. carica were evaluated as best performers. They could be integrated into plantations drives for environmental management.     

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.     

Live diatoms as indicators of urban stormwater runoff

Diatom bioassessment of streams/rivers does not distinguish between live (cells with intact chloroplasts) and dead (empty cells) individuals, even though most diatom samples collected from the field will be composed of a mixture of both. This study aimed to evaluate whether percentage of live diatoms (PLD), live diatom density and chlorophyll a, and diatom species compositions can be used as indicators of hydrologic disturbance in an urban stream. We deployed artificial substrates on a monthly basis and collected periphyton samples weekly over the course of one calendar year (n = 182) in three tributaries of urbanized Ruddiman Creek (Michigan, USA). We also collected samples before and after six major storm events (>0.5 cm rain). We found no temporal patterns in PLD (Mann-Kendall test p > 0.05) or species composition (non-metric multidimensional scaling (NMDS) ordination), which may be explained by a diatom composition already tolerant to frequent disturbance. There was no difference in PLD before and after storm events, which might partially be explained by their disturbance resistance due to different assemblage ages (1, 2, and 4 weeks old) before the storms. High flow had differential effects on diatom species; loosely attached Navicula and Nitzschia species were more easily removed compared to stalk-forming Gomphonema parvulum. The most important environmental variable that was found to affect live diatom density and chlorophyll was stream width, which has an indirect effect (as a measure of discharge) on periphyton assemblages. In conclusion, PLD was found to be unsuitable metric for assessing stormwater runoff in urban streams where periphyton may not have enough time to form mature communities.     

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.