Formation of aerobic granules in the presence of a synthetic chelating agent

This paper examines the development of aerobic granular sludge in the presence of a synthetic chelating agent, nitrilotriacetic acid (NTA), in sequencing batch reactors (SBR). The growth of seed sludge at 0.26 mM, 0.52 mM and 1.05 mM of NTA was found to be significantly lower as compared to that in the absence of NTA. Aerobic granulation was significantly enhanced in the three SBRs (R2, R3 and R4), which were fed with 0.26 mM, 0.52 mM and 1.05 mM of NTA as a co-substrate, in comparison to the acetate-alone fed SBR (R1). After 2 months of operation, the mean diameter of the biomass stabilized at 0.35 mm in R1 (acetate alone), as compared to 2.18 mm in R4 (1.05 mM NTA+acetate). NTA degradation was established in SBRs, with almost complete removal during the SBR cycle. Batch experiments also showed efficient degradation of NTA by the aerobic granules.     

Bioaugmentation of aerobic microbial granules with Pseudomonas putida carrying TOL plasmid

This paper describes results of a successful bioaugmentation experiment on aerobic granular sludge using Pseudomonas putida KT2442 cells bearing the TOL (pWWO) plasmid. The methodology was designed to monitor incorporation of the added donor cells into pre-existent microbial granules and the subsequent plasmid transfer to the autochthonous microbial community using shake flask microcosms. Expression of reporter proteins (GFP and DsRed) allowed in situ monitoring of donor cell attachment and plasmid transfer to the recipient cells using confocal laser scanning microscopy. Concomitant with donor integration and transconjugant proliferation in the granules, a significant increase in degradation of benzyl alcohol (used as sole substrate) was observed in the augmented microcosms. In contrast, control microcosms (with non-augmented granules) did not show any noticeable increase in the degradation of the substrate. This study shows that bioaugmentation of aerobic granular sludge via donor colonization and plasmid transfer is feasible for enhanced biodegradation.     

Landscape approach for quantifying land use land cover change (1972–2006) and habitat diversity in a mining area in Central India (Bokaro, Jharkhand)

The rate and intensity of land use land cover (LULC) change has increased considerably during the past couple of decades. Mining brings significant alterations in LULC specifically due to its impact on forests. Parts of Central India are well endowed with both forests and minerals. Here, the conflict between human interests and nature has intensified over time. Monitoring and assessment of such conflicts are important for land management and policy making. Remote sensing and Geographical Information System have the potential to serve as accurate tools for environmental monitoring. Understanding the importance of landscape metrics in land use planning is challenging but important. These metrics calculated at landscape, class, and patch level provide an insight into changing spatiotemporal distribution of LULC and ecological connectedness. In the present study, geospatial tools in conjunction with landscape metrics have been used to assess the impact of coal mining on habitat diversity. LULC maps, change detection analysis, and landscape metrics have been computed for the four time periods (1972, 1992, 2001, and 2006). There has been a significant decline in forest cover especially of the Sal-mixed forests, both in area as well as quality, due to flouted mining regulations. Reclamation of mined lands has also been observed in some of the areas since 2001.     

Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999

Deforestation is recognized as one of the most significant component in LULC and global changes scenario. It is imperative to assess its trend and the rates at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. In North-East India, one of the recognized global biodiversity hotspots, approximately 30% of total forest cover is under pressure of rapid land use changes. This region harbors variety of rare and endemic species of flora and fauna. It also has a strong bearing on regional climatic conditions. Extensive shifting cultivation, compounded by increasing population pressure and demands for agriculture land are the prime drivers in addition to other proximate drivers of deforestation. It is therefore of prime concern to analyse forest cover changes in the region, assess rate of change and extent and to identify the areas, which show repetitive changes. We analyzed forest cover maps from six temporal datasets based on satellite data interpretation, converted to geospatial database since 1972 till 1999. The states of Meghalaya, Nagaland and Tripura show highest changes in forest cover. Arunachal Pradesh shows least dynamic areas and maintains a good forest cover owing to its topographical inaccessibility in some areas. The present study reports the forest cover changes in the region using geospatial analysis and analyse them to devise proper management strategies.     

Development of tiger habitat suitability model using geospatial tools—a case study in Achankmar Wildlife Sanctuary (AMWLS), Chhattisgarh India

Geospatial tools supported by ancillary geo-database and extensive fieldwork regarding the distribution of tiger and its prey in Anchankmar Wildlife Sanctuary (AMWLS) were used to build a tiger habitat suitability model. This consists of a quantitative geographical information system (GIS) based approach using field parameters and spatial thematic information. The estimates of tiger sightings, its prey sighting and predicted distribution with the assistance of contextual environmental data including terrain, road network, settlement and drainage surfaces were used to develop the model. Eight variables in the dataset viz., forest cover type, forest cover density, slope, aspect, altitude, and distance from road, settlement and drainage were seen as suitable proxies and were used as independent variables in the analysis. Principal component analysis and binomial multiple logistic regression were used for statistical treatments of collected habitat parameters from field and independent variables respectively. The assessment showed a strong expert agreement between the predicted and observed suitable areas. A combination of the generated information and published literature was also used while building a habitat suitability map for the tiger. The modeling approach has taken the habitat preference parameters of the tiger and potential distribution of prey species into account. For assessing the potential distribution of prey species, independent suitability models were developed and validated with the ground truth. It is envisaged that inclusion of the prey distribution probability strengthens the model when a key species is under question. The results of the analysis indicate that tiger occur throughout the sanctuary. The results have been found to be an important input as baseline information for population modeling and natural resource management in the wildlife sanctuary. The development and application of similar models can help in better management of the protected areas of national interest.     

Assessing impact of industrialization in terms of LULC in a dry tropical region (Chhattisgarh), India using remote sensing data and GIS over a period of 30 years

The main focus of the paper is to assess the land use/ land cover (LULC) change in northern Chhattisgarh due to industrialization using remote sensing and Geographical Information System (GIS). The impact was assessed using an information extraction method applied to temporal satellite data (LANDSAT and IRS scenes) in GIS domain. For assessing the impact on natural resources, the classification scheme was restricted to (1) Forest patches ((a) completely cleared, (b) partially cleared, (c) least affected), (2) Non-Forest ((d) completely changed, (e) least changed), (3) Industrial/Mining area, and (4) River. Over the three decades 22.22% of forests have been completely cleared and converted to industrial setup. Another 25% is completely cleared and 10% is degraded. Around 4% of agricultural area is totally affected due to industrial activity. Random assessment of plant distribution (Trees, Shrubs and Herbs) indicates significant changes in the herb distribution directly related to distance gradient form the industrial/mining setup. Visual recording, socio-economic survey and satellite data also helped in delineation of extent of environmental pollution in forest and non-forest areas. The paper presents methodology for the environmental impact assessment.     

Vulnerability of forests in the Himalayan region to climate change impacts and anthropogenic disturbances: a systematic review

Regional Environmental Change - The Himalayan region is not only threatened by rapid changes in anthropogenic activities but also by global climate change. Given the uncertainties of magnitude and...     

Seasonal distribution and contamination levels of total PHCs, PAHs and heavy metals in coastal waters of the Alang-Sosiya ship scrapping yard, Gulf of Cambay, India

Alang-Sosiya situated on the Gulf of Cambay is one of the largest ship breaking yard in the world. The seasonal distribution and contamination levels of dissolved and/or dispersed total petroleum hydrocarbons (PHCs), total polycyclic aromatic hydrocarbons (PAHs) and heavy metals in seawater during high tide are investigated. The concentrations of petroleum hydrocarbons and heavy metals are higher in the winter than in the monsoon and summer. The concentrations of total PHCs and PAHs are about three times higher in the winter and two times in the monsoon or summer at Along-Sosiya and about twice in all seasons at two stations one on either side 5 km away from it as compared to the reference station at Mahuva, 60 km away towards the south. Further, the levels of PHCs are correlated with salinity and compared with those of other regions. The concentration of all metals is the highest in the winter season followed by the monsoon and summer. We carried out the quantitative analysis of the possible relationships among 13 variables such as Al, Fe, Pb, Mn, Cu, Zn, Cd, Cr, Co, pH, NO3-, NO2 and PO4(3-).