Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

Methane oxidation and abundance of methane oxidizers in tropical agricultural soil (vertisol) in response to CuO and ZnO nanoparticles contamination

There is worldwide concern over the increase use of nanoparticles (NPs) and their ecotoxicological effect. It is not known if the annual production of tons of industrial nanoparticles (NPs) has the potential to impact terrestrial microbial communities, which are so necessary for ecosystem functioning. Here, we have examined the consequences of adding the NPs particularly the metal oxide (CuO, ZnO) on CH₄ oxidation activity in vertisol and the abundance of heterotrophs, methane oxidizers, and ammonium oxidizers. Soil samples collected from the agricultural field located at Madhya Pradesh, India, were incubated with either CuO and ZnO NPs or ionic heavy metals (CuCl₂, ZnCl₂) separately at 0, 10, and 20 μg g^?1 soil. CH₄ oxidation activity in the soil samples was estimated at 60 and 100 % moisture holding capacity (MHC) in order to link soil moisture regime with impact of NPs. NPs amended to soil were highly toxic for the microbial-mediated CH₄ oxidation, compared with the ionic form. The trend of inhibition was Zn 20?>?Zn 10?>?Cu 20?>?Cu 10. NPs delayed the lag phase of CH₄ oxidation to a maximum of 4-fold and also decreased the apparent rate constant k up to 50 % over control. ANOVA and Pearson correlation analysis (α?=?0.01) revealed significant impact of NPs on the CH₄ oxidation activity and microbial abundance (p?<?0.0001, and high F statistics). Principal component analysis (PCA) revealed that PC1 (metal concentration) rendered 76.06 % of the total variance, while 18.17 % of variance accounted by second component (MHC). Biplot indicated negative impact of NPs on CH₄ oxidation and microbial abundance. Our result also confirmed that higher soil moisture regime alleviates toxicity of NPs and opens new avenues of research to manage ecotoxicity and environmental hazard of NPs.     

Assessment of large-scale deforestation of Nawarangpur district, Orissa, India: a remote sensing based study

The Nawarangpur district, Orissa, a tropical region with Sal mixed moist deciduous and Sal mixed dry deciduous forests, has been affected by extensive deforestation. The district was surveyed using Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) satellite imagery. From 1973 to 1990, more than 888.6 km(2) of dense forest (rate of deforestation = 3.62) and from 1990 to 2004, 429.7 km(2) (rate of deforestation = 3.97) were found to have been deforested. The analysis of results identified the reduction in area of dense forest and increase of agricultural land, degraded areas of abandoned agricultural land and unproductive scrub. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. From this study it can be concluded that temporal changes and the factors affecting these changes should be determined for sustainable management of natural resources.     

The use of marine sponge, Haliclona tenuiramosa as bioindicator to monitor heavy metal pollution in the coasts of Gulf of Mannar, India

The results of the present research study indicate that the heavy metal accumulation in the marine sponges provide evidence as an excellent bioindicators for monitoring heavy metal pollution between near and offshore environments of Mandapam coast of "Gulf of Mannar (GoM), India". The heavy metal concentrations in sea water and accumulation in the tissues of Haliclona tenuiramosa were analyzed by ICP-MS (inductively coupled plasma-mass spectrometry). The concentrations of metals in the coastal waters of nearshore (< 0.5 km from shore) were always higher than those in the offshore waters (2-5 km away from shore). Likewise, sponges living in the nearshore accumulated greater concentrations of heavy metals (As, Cd, Co, Cu, Fe, Mn and Ni) ranging from 2 to 17 times higher concentration than the sponges located away from the shore. A positive correlation between concentration levels in water and bioaccumulation in tissues was observed. The bioaccumulation of heavy metals in sponge tissue were in order of Fe > Mn > Ni > Cu > As > Co > Cd in both the near and offshore stations. The present results justified that a more comprehensive monitoring of presence of heavy metals in H. tenuiramosa of surrounding GoM, is necessary to help a better mitigation of the problem.     

Long-term effect of rice-based farming systems on soil health

Integrated rice–fish culture, an age-old farming system, is a technology which could produce rice and fish sustainably at a time by optimizing scarce resource use through complementary use of land and water. An understanding of microbial processes is important for the management of farming systems as soil microbes are the living part of soil organic matter and play critical roles in soil C and N cycling and ecosystem functioning of farming system. Rice-based integrated farming system model for small and marginal farmers was established in 2001 at Central Rice Research Institute, Cuttack, Odisha. The different enterprises of farming system were rice–fish, fish–fingerlings, fruits, vegetables, rice–fish refuge, and agroforestry. This study was conducted with the objective to assess the soil physicochemical properties, microbial population, carbon and nitrogen fractions, soil enzymatic activity, and productivity of different enterprises. The effect of enterprises induced significant changes in the chemical composition and organic matter which in turn influenced the activities of enzymes (urease, acid, and alkaline phosphatase) involved in the C, N, and P cycles. The different enterprises of long-term rice-based farming system caused significant variations in nutrient content of soil, which was higher in rice–fish refuge followed by rice–fish enterprise. Highest microbial populations and enzymatic properties were recorded in rice–fish refuge system because of waterlogging and reduced condition prolonged in this system leading to less decomposition of organic matter. The maximum alkaline phosphatase, urease, and FDA were observed in rice–fish enterprise. However, highest acid phosphatase and dehydrogenase activity were obtained in vegetable enterprise and fish–fingerlings enterprise, respectively.     

Modelling of lindane transport in groundwater of metropolitan city Vadodara,Gujarat, India

Migration pattern of organochloro pesticide lindane has been studied in groundwater of metropolitan city Vadodara. Groundwater flow was simulated using the groundwater flow model constructed up to a depth of 60 m considering a three-layer structure with grid size of 40?×?40?×?40 m³. The general groundwater flow direction is from northeast to south and southwest. The river Vishwamitri and river Jambua form natural hydrologic boundary. The constant head in the north and south end of the study area is taken as another boundary condition in the model. The hydraulic head distribution in the multilayer aquifer has been computed from the visual MODFLOW groundwater flow model. TDS has been computed though MT3D mass transport model starting with a background concentration of 500 mg/l and using a porosity value of 0.3. Simulated TDS values from the model matches well with the observed data. Model MT3D was run for lindane pesticide with a background concentration of 0.5?μg/l. The predictions of the mass transport model for next 50 years indicate that advancement of containment of plume size in the aquifer system both spatially and depth wise as a result of increasing level of pesticide in river Vishwamitri. The restoration of the aquifer system may take a very long time as seen from slow improvement in the groundwater quality from the predicted scenarios, thereby, indicating alarming situation of groundwater quality deterioration in different layers. It is recommended that all the industries operating in the region should install efficient effluent treatment plants to abate the pollution problem.     

Spatial and temporal estimation of soil loss for the sustainable management of a wet semi-arid watershed cluster

The ungauged wet semi-arid watershed cluster, Seethagondi, lies in the Adilabad district of Telangana in India and is prone to severe erosion and water scarcity. The runoff and soil loss data at watershed, catchment, and field level are necessary for planning soil and water conservation interventions. In this study, an attempt was made to develop a spatial soil loss estimation model for Seethagondi cluster using RUSLE coupled with ARCGIS and was used to estimate the soil loss spatially and temporally. The daily rainfall data of Aphrodite for the period from 1951 to 2007 was used, and the annual rainfall varied from 508 to 1351 mm with a mean annual rainfall of 950 mm and a mean erosivity of 6789 MJ mm ha^?1 h^?1 year^?1. Considerable variation in land use land cover especially in crop land and fallow land was observed during normal and drought years, and corresponding variation in the erosivity, C factor, and soil loss was also noted. The mean value of C factor derived from NDVI for crop land was 0.42 and 0.22 in normal year and drought years, respectively. The topography is undulating and major portion of the cluster has slope less than 10°, and 85.3 % of the cluster has soil loss below 20 t ha^?1 year^?1. The soil loss from crop land varied from 2.9 to 3.6 t ha^?1 year^?1 in low rainfall years to 31.8 to 34.7 t ha^?1 year^?1 in high rainfall years with a mean annual soil loss of 12.2 t ha^?1 year^?1. The soil loss from crop land was higher in the month of August with an annual soil loss of 13.1 and 2.9 t ha^?1 year^?1 in normal and drought year, respectively. Based on the soil loss in a normal year, the interventions recommended for 85.3 % of area of the watershed includes agronomic measures such as contour cultivation, graded bunds, strip cropping, mixed cropping, crop rotations, mulching, summer plowing, vegetative bunds, agri-horticultural system, and management practices such as broad bed furrow, raised sunken beds, and harvesting available water using farm ponds and percolation tanks. This methodology can be adopted for estimating the soil loss from similar ungauged watersheds with deficient data and for planning suitable soil and water conservation interventions for the sustainable management of the watersheds.     

Statistical Analysis of Trends in Urban Ozone Air Quality

The purpose of this paper is to demonstrate the use of some statistical methods for examining trends in ambient ozone air quality downwind of major urban areas. To this end, daily maximum 1 -hr ozone concentrations measured over New Jersey, metropolitan New York City and Connecticut for the period 1980 to 1989 were assembled and analyzed. This paper discusses the application of the bootstrap method, extreme value statistics and a nonparametric test for evaluating trends in urban ozone air quality. The results indicate that although there is an improvement in ozone air quality downwind of New York City, there has been little change in ozone levels upwind of New York City during this ten-year period.     

Ozone Air Quality over North America: Part II—An Analysis of Trend Detection and Attribution Techniques

ABSTRACT

Assessment of regulatory programs aimed at improving ambient O₃ air quality is of considerable interest to the scientific community and to policymakers. Trend detection, the identification of statistically significant long-term changes, and attribution, linking change to specific clima-tological and anthropogenic forcings, are instrumental to this assessment. Detection and attribution are difficult because changes in pollutant concentrations of interest to policymakers may be much smaller than natural variations due to weather and climate. In addition, there are considerable differences in reported trends seemingly based on similar statistical methods and databases. Differences arise from the variety of techniques used to reduce nontrend variation in time series, including mitigating the effects of meteorology and the variety of metrics used to track changes. In this paper, we review the trend assessment techniques being used in the air pollution field and discuss their strengths and limitations in discerning and attributing changes in O₃ to emission control policies.