Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

Conservation and management applications of the REEF volunteer fish monitoring program

The REEF Fish Survey Project is a volunteer fish monitoring program developed by the Reef Environmental Education Foundation (REEF). REEF volunteers collect fish distribution and abundance data using a standardized visual method during regular diving and snorkeling activities. Survey data are recorded on preprinted data sheets that are returned to REEF and optically digitized. Data are housed in a publicly accessible database on REEF's Web site (http: //www.reef.org). Since the project's inception in 1993, over 40,000 surveys have been conducted in the coastal waters of North America, tropical western Atlantic, Gulf of California and Hawaii. The Fish Survey Project has been incorporated into existing monitoring programs through partnerships with government agencies, scientists, conservation organizations, and private institutions. REEF's partners benefit from the educational value and increased stewardship resulting from volunteer data collection. Applications of the data include an evaluation of fish/habitat interactions in the Florida Keys National Marine Sanctuary, the development of a multi-species trend analysis method to identify sites of management concern, assessment of the current distribution of species, status reports on fish assemblages of marine parks, and the evaluation of no-take zones in the Florida Keys. REEF's collaboration with a variety of partners, combined with the Fish Survey Project's standardized census method and database management system, has resulted in a successful citizen science monitoring program.     

Characterization of microbial communities from coastal waters using microarrays

Molecular methods, including DNA probes, were used to identify and enumerate pathogenic Vibrio species in the Chesapeake Bay; our data indicated that Vibrio vulnificus exhibits seasonal fluctuations in number. Our work included a characterization of total microbial communities from the Bay; development of microarrays that identify and quantify the diversity of those communities; and observation of temporal changes in those communities. To identify members of the microbial community, we amplified the 16S rDNA gene from community DNA isolated from a biofilm sample collected from the Chesapeake Bay in February, 2000. The resultant 75 sequences were 95% or more similar to 7 species including two recently described Shewanella species, baltica and frigidimarina, that have not been previously isolated from the Chesapeake. When the genera of bacteria from biofilm after culturing are compared to those detected by subcloning amplified 16S fragments from community DNA, the cultured sample exhibited a strong bias. In oysters collected in February, the most common bacteria were previously unknown. Based on our 16S findings, we are developing microarrays to detect these and other microbial species in these estuarine communities. The microarrays will detect each species using four distinct loci, with the multiple loci serving as an internal control. The accuracy of the microarray will be measured using sentinel species such as Aeromonas species, Escherichia coli, and Vibrio vulnificus. Using microarrays, it should be possible to determine the annual fluctuations of bacterial species (culturable and non-culturable, pathogenic and non-pathogenic). The data may be applied to understanding patterns of environmental change; assessing the health of the Bay; and evaluating the risk of human illness associated with exposure to and ingestion of water and shellfish.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Delineating shallow saline groundwater zones from Southern India using geophysical indicators

A geophysical survey was conducted over an industrial belt encompassing 80 functional leather factories in Southern India. These factories discharge untreated effluents which pollute shallow groundwater where electrical conductivity (EC) value had a wide range between 545 and 26,600 μS/cm (mean, 3, 901 μS/cm). The ranges of Na⁺ and Cl^? ions were from 46 to 4,850 mg/L (mean, 348 mg/L) and 25 to 10,390 mg/L (mean, 1,079 mg/L), respectively. Geoelectrical layer parameters of 37 vertical electrical soundings were analyzed to demarcate fresh and saline water zones. However, the analysis not did lead to a unique resolution of saline and fresh waters. It was difficult to assign a definitive value to the aquifer resistivity of any area. Thus, geophysical indicators, namely longitudinal unit conductance (S), transverse unit resistance (T), and average longitudinal resistivity (R _s), were calculated for identifying fresh and saline waters. Spatial distributions of S, T, and R _s reflected widely varying ranges for the saline and fresh water zones. Further, the empirical relation of formation factor (F) was established from pore-water resistivity and aquifer resistivity for fresh and saline aquifers, which may be used to estimate local EC values from the aquifer resistivity, where well water is not available.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Determination of gaseous polycyclic aromatic hydrocarbons by a simple direct method using thermal desorption–gas chromatography–mass spectrometry

In the last decade, the development of novel analytical methodologies enabled the identification of several environmental pollutants responsible for health problems associated with indoor exposure. Polycyclic aromatic hydrocarbons (PAHs) are among the potential hazardous chemicals present in ambient air. Due to their bioaccumulation potential and carcinogenic/mutagenic effects, 16 PAHs are currently listed as priority air pollutants. The main goal of this work was to implement a new and simple method for sampling and determination of PAHs in air by using a thermal desorption (TD) technique followed by gas chromatography coupled with mass spectrometry analysis. A detailed study was carried out to optimise the experimental method in each of its phases, including (active) sampling, TD and chromatographic analysis. The results demonstrate that this approach allowed the detection and quantification of the six more volatile PAHs, namely, naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, and anthracene. Acceptable precision and good linearity over the explored range were obtained. No carry-over was observed during experimental tests and the method provided a reproducible answer. The applicability of the novel methodology was tested in real environment, namely, on the roof of a building in an urban area, in a domestic kitchen and in a collective car garage. The method enabled the identification of two PAHs in the field samples, specifically, naphthalene (two rings) and phenanthrene (three rings). With regard to PAHs sample composition, the most abundant PAH found, in the three different locations, was naphthalene, accounting for about 84–100 % of the total PAH mass detected.     

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity’s influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed’s influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.