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.     

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.     

<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.     

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.     

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.     

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.     

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).     

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.     

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.     

Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of <Emphasis Type="Italic">Spartina alterniflora</Emphasis> under interspecies competition

The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited space, directly influencing the co-exist distribution in the future. However, these two species have different growth ratios in this area, which increase the difficulty to detect the distribution situation directly by remote sensing. As chlorophyll content is a key indicator of plant growth and physiological status, the objective of this study was to reduce the effect of interspecies competition when estimating Cab content; we evaluated 79 published representative indices to determine the optimal indices for estimating the chlorophyll a and b (Cab) content. After performing a sensitivity analysis for all 79 spectral indices, five spectral indices were selected and integrated using an artificial neural network (ANN) to estimate the Cab content of different competition ratios: the Gitelson ratio green index, the transformed chlorophyll absorption ratio index/optimized soil-adjusted vegetation index, the modified normalized difference vegetation index, the chlorophyll fluorescence index, and the Vogelmann chlorophyll index. The ANN method yielded better results (R ² = 0.7110 and RMSE = 8.3829 μg cm^?2) on average than the best single spectral index (R ² = 0.6319 and RMSE = 9.3535 μg cm^?2), representing an increase of 10.78% in R ² and a decrease of 10.38% in RMSE. Our results indicated that integrating multiple vegetation indices with an ANN can alleviate the impact of interspecies competition and achieve higher estimation accuracy than the traditional approach using a single index.     

Characterisation of the airborne pollen spectrum in Guadalajara (central Spain) and estimation of the potential allergy risk

Aerobiological research into airborne pollen diversity and seasonal variations in pollen counts has become increasingly important over recent decades due to the growing incidence of asthma, rhinitis and other pollen-related allergic conditions. Airborne pollen in Guadalajara (Castilla-La Mancha, Spain) was studied over a 6-year period (2008–2013) using a Hirst-type volumetric spore trap. The highest pollen concentrations were recorded from February to June, coinciding with the pollen season of the pollen types that most contribute to the local airborne pollen spectrum: Cupressaceae (32.2 %), Quercus (15.1 %), Platanus (13.2 %), Olea (8.3 %), Populus (7.8 %) and Poaceae (7.2 %). These are therefore critical months for allergy sufferers. The pollen calendar was typically Mediterranean and comprised 25 pollen types. Between January and March, Cupressaceae pollen concentrations exceeded allergy risk thresholds on 38 days. Other woody species such as Olea and Platanus have a shorter pollen season, and airborne concentrations exceeded allergy risk thresholds on around 13 days in each case. Poaceae pollen concentrations attained allergy risk levels on 26 days between May and July. Other highly allergenic pollen types included Urticaceae and Chenopodiaceae-Amaranthaceae, though these are less abundant than other pollen types in Guadalajara and did not exceed risk thresholds on more than 3 and 5 days, respectively.     

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.     

<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.     

Comparing two periphyton collection methods commonly used for stream bioassessment and the development of numeric nutrient standards

Periphyton is an important component of stream bioassessment, yet methods for quantifying periphyton biomass can differ substantially. A case study within the Arkansas Ozarks is presented to demonstrate the potential for linking chlorophyll-a (chl-a) and ash-free dry mass (AFDM) data sets amassed using two frequently used periphyton sampling protocols. Method A involved collecting periphyton from a known area on the top surface of variably sized rocks gathered from relatively swift-velocity riffles without discerning canopy cover. Method B involved collecting periphyton from the entire top surface of cobbles systematically gathered from riffle-run habitat where canopy cover was intentionally avoided. Chl-a and AFDM measurements were not different between methods (p = 0.123 and p = 0.550, respectively), and there was no interaction between method and time in the repeated measures structure of the study. However, significantly different seasonal distinctions were observed for chl-a and AFDM from all streams when data from the methods were combined (p < 0.001 and p = 0.012, respectively), with greater mean biomass in the cooler sampling months. Seasonal trends were likely the indirect results of varying temperatures. Although the size and range of this study were small, results suggest data sets collected using different methods may effectively be used together with some minor considerations due to potential confounding factors. This study provides motivation for the continued investigation of combining data sets derived from multiple methods of data collection, which could be useful in stream bioassessment and particularly important for the development of regional stream nutrient criteria for the southern Ozarks.     

Experimental arid land afforestation in Central Anatolia,Turkey

The afforestation of arid lands faces many challenges, and perhaps the most important key for success is choosing one or more species that are adapted well for local environmental conditions. We explored species that would be suitable for the steppe region of Central Anatolia. Intensive site preparation included ripping the subsoil (to 80 cm) and plowing the upper soil before planting seedlings of Elaeagnus angustifolia, Robinia pseudoacacia, Fraxinus angustifolia, and Pinus nigra were used as tree species. We also tested the success of several shrub species: Amygdalus orientalis, Calligonum polygonoides, and Spartium junceum. After five growing seasons, E. angustifolia showed the highest survival, with 80% of planted seedlings remaining. For the shrubs, A. orientalis was the most successful species with a 95% survival rate. Broad-leaved trees grew a cumulative average of 34 cm in height in 5 years, whereas P. nigra seedings grew only 9 cm. The greatest height growth occurred in the shrubs, with A. orientalis gaining 40 cm in height in 5 years. Overall, E. angustifolia and A. orientalis appeared best suited for afforestation in these areas. R. pseodoacacia and F. angustifolia may also be used as alternative species.     

Assessment of heavy metal pollution in vegetables and relationships with soil heavy metal distribution in Zhejiang province,China

There are increasing concerns on heavy metal contaminant in soils and vegetables. In this study, we investigated heavy metal pollution in vegetables and the corresponding soils in the main vegetable production regions of Zhejiang province, China. A total of 97 vegetable samples and 202 agricultural soil samples were analyzed for the concentrations of Cd, Pb, As, Hg, and Cr. The average levels of Cd, Pb, and Cr in vegetable samples [Chinese cabbage (Brassica campestris spp. Pekinensis), pakchoi (Brassica chinensis L.), celery (Apium graveolens), tomato (Lycopersicon esculentum), cucumber (Colletotrichum lagenarium), cowpea (Vigna unguiculata), pumpkin (Cucurbita pepo L.), and eggplant (Solanum melongena)] were 0.020, 0.048, and 0.043 mg kg^?1, respectively. The Pb and Cr concentrations in all vegetable samples were below the threshold levels of the Food Quality Standard (0.3 and 0.5 mg kg^?1, respectively), except that two eggplant samples exceeded the threshold levels for Cd concentrations (0.05 mg kg^?1). As and Hg contents in vegetables were below the detection level (0.005 and 0.002 mg kg^?1, respectively). Soil pollution conditions were assessed in accordance with the Chinese Soil Quality Criterion (GB15618-1995, Grade II); 50 and 68 soil samples from the investigated area exceeded the maximum allowable contents for Cd and Hg, respectively. Simple correlation analysis revealed that there were significantly positive correlations between the metal concentrations in vegetables and the corresponding soils, especially for the leafy and stem vegetables such as pakchoi, cabbage, and celery. Bio-concentration factor values for Cd are higher than those for Pb and Cr, which indicates that Cd is more readily absorbed by vegetables than Pb and Cr. Therefore, more attention should be paid to the possible pollution of heavy metals in vegetables, especially Cd.     

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.     

Organismic-level acute toxicology profiling of reactive azo dyes

In the present study, organismic-level acute toxicology profile of three reactive azo dyes, viz. Reactive Blue 221, Reactive Red 195, and Reactive Yellow 145, was investigated, by using bacterial (Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Listeria monocytogenes, and Bacillus subtilis), fungal (Trichoderma asperellum, Aspergillus flavus, Fusarium fujikuroi, and Rhizoctonia solani), plant (Raphanus sativus, Triticum aestivum, Sorghum bicolor, and Phaseolus mungo), and aquatic (Artemia salina and Daphnia magna) specimens. Microbial test organisms (all the six bacteria and two fungi, i.e., T. asperellum and A. flavus) and D. magna were found to be relatively more sensitive towards the reactive azo dyes and their mixture, as the EC50 values were in the range of 80–330, 135–360, and 108–242 ppm for bacteria, fungi, and D. magna, respectively (but the effect was not acutely toxic). Moreover, the effect of dye mixture was comparable tothe individual dyes in almost all the tested microbial specimens. For plant seeds, the dye mixture was found to be relatively more inhibitory towards T. aestivum and R. sativus than the individual dyes. For S. bicolor and P. mungo seeds, the effect of the dye mixture was almost identical to the individual dyes. However, in all cases, EC50 values were in the range of 950–3500 ppm, which indicates a non-toxic effect on plant seed germination potential. Likewise, the dyes and their mixture were not acutely toxic for Artemia salina larvae (more sensitive to the dye mixture) and Daphnia magna neonates (EC50, 516–950 and 108–242 ppm, respectively).     

Carbon and nitrogen mineralization in Vertisol as mediated by type and placement method of residue

Selection of appropriate residue application method is essential for better use of biomass for soil and environmental health improvement. A laboratory incubation experiment was conducted for 75 days to investigate C and N mineralization of residues of soybean (Glycine max L.), chickpea (Cicer arietinum L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) placed on the soil surface and incorporated into the soil. The residue of soybean and chickpea had a greater decomposition rate than that of maize and wheat, despite of their placements. Higher rate of decomposition of the residue of soybean and chickpea was recorded when it was kept on the soil surface while soil incorporation of residue of wheat and maize resulted in faster decomposition. Therefore, these findings could be used as guidelines for management of crop residue application in farmland to improve soil and environmental quality.