Classification of local- and landscape-scale ecological types in the southern Appalachian Mountains

Five local ecological types based on vegetative communities and two landscape types based on groups of communities, were identified by integrating landform, soil, and vegetation components using multivariate techniques. Elevation and several topographic and soil variables were highly correlated with types of both scales. Landscape ecological types based only on landform and soil variables without vegetation did not correspond with types developed using vegetation. Models developed from these relationships could allow classification and mapping of extensive areas using geographic information systems.     

Geospatial Analysis of Climatic and Geomorphic Interactions Influencing Stream Discharge, Appalachian Mountains, USA

Streamflow values are commonly synthesized for locations where flow measurement stations are lacking or where only intermittent measurements are available. In an Appalachian Mountains dataset comprised of 29 watersheds, the most appropriate among geomorphic, geologic, and hydrogeologic datasets were selected for use in prediction of streamflow at watershed scale. A statistical model was developed using principal components analysis (PCA) and cluster analysis (CA) for. Using CA on variables derived from the PCA, an optimum set of variables was derived for predicting streamflow. Results indicate there are two categories of watersheds in the study area. The first is strongly correlated with climatic variables (precipitation, temperature, elevation, and groundwater recharge). The second is strongly correlated with two geomorphic variables (watershed slope and percentage of forested area). The spatial distribution of cluster classifications shows that watersheds dominated by the climatic component are located along the Allegheny Front while watersheds dominated by the geomorphic component are located in the Allegheny Plateau and Valley and Ridge physiographic provinces. These variations between the Allegheny Plateau and Valley and Ridge physiographic provinces suggest that, to accurately model streamflow, modeling needs be done based on natural physiographic boundaries rather than political boundaries. In this physiographic setting, elevation seems to be a major control.     

Toxicodynamic modeling of 137Cs to estimate white-tailed deer background levels for the Department of Energy's Savannah River Site

The U.S. Department of Energy's (USDOE) Savannah River Site (SRS) is a former nuclear weapon material production and current research facility adjacent to the Savannah River in South Carolina, USA. The purpose of this study was to determine the background radiocesium (¹³⁷Cs) body burden (e.g., from global fallout) for white-tailed deer (Odocoileus virginianus) inhabiting the SRS. To differentiate what the background burden is for the SRS versus ¹³⁷Cs obtained from SRS nuclear activities, data were analyzed spatially, temporally and compared to other off-site hunting areas near the SRS. The specific objectives of this study were: to compare SRS and offsite deer herds based on time and space; to interpret comparisons based on how data were collected as well as the effect of environmental and anthropogenic influences; to determine what the ecological half-life/decay rate is for ¹³⁷Cs in the SRS deer herd; and to give a recommendation to what should be considered the background ¹³⁷Cs level in the SRS deer herd. Based on the available information and analyses, it is recommended that the determination of what is considered background for the SRS deer herd be derived from data collected from the SRS deer herd itself and not offsite collections for a variety of reasons. Offsite data show extreme variability most likely due to environmental factors such as soil type and land-use patterns (e.g., forest, agriculture, residential activities). This can be seen from results where samples from offsite military bases (Fort Jackson and Fort Stewart) without anthropogenic ¹³⁷Cs sources were much higher than both the SRS and a nearby (Sandhills) study site. Moreover, deer from private hunting grounds have the potential to be baited with corn, thus artificially lowering their ¹³⁷Cs body burdens compared to other free-ranging deer. Additionally, sample size for offsite collections were not robust enough to calculate a temporal decay curve with an upper confidence level to determine if the herds are following predicted radioactive decay rates like the SRS or if the variability is due to those points described above. Using mean yearly values, the ecological half-life for ¹³⁷Cs body burdens for SRS white-tailed deer was determined to be 28.79 years—very close to the 30.2 years physical half-life.     

Ozone Exposures and Implications for Vegetation in Rural Areas of the Central Appalachian Mountains, U.S.A.

The United States is making the transition from the 1979 1 hr maximum ozone standard to the newly adopted 8 hr ozone standard (3 yr average of the 4th highest maximum 8 hr ozone concentration). Consequently, we analyzed and compared ozone concentrations under both standards from a variety of monitoring sites throughout the central Appalachian region of Kentucky (KY), West Virginia (WV), and Virginia (VA). Data from 1988-1999 were used to determine how ozone exposure between the two metrics compared for remote sites. Most sites exceeded the 1 hr standard in 1988-1990 due to the 3 yr averaging and multiple high ozone concentrations that occurred over the region in 1988. All sites were in compliance with the 1 hr standard every year after 1991. It was much more common for the ozone exposure to exceed the 8 hr standard, particularly from 1997-1999. Many sites showed exceedences beginning in 1995; Big Meadows (VA) exceeded the 8 hr standard all years except 1994 and 1996. Response of vegetation to ozone in these areas was determined using the combination of W126 values (sigmoidally weighted exposure index), the number of hours that average concentrations > or = 0.10 ppm (N100), and the presence of moderate or more extreme droughts. In general, W126 and N100 values suggested that negative vegetation growth responses over most of the 12 yr would have been minimal for most sites, even for those exceeding ozone standards. Drought-induced stomatal closures would have overridden more extreme negative growth responses at all but the Big Meadows site in 1988.     

Spatial assessment of soil salinity in the Harran Plain using multiple kriging techniques

The Harran Plain is located in the southeastern part of Turkey and has recently been developed for irrigation agriculture. It already faces soil salinity problems causing major yield losses. Management of the problem is hindered by the lack of information on the extent and geography of the salinization problem. A survey was carried out to delineate the spatial distribution of salt-affected areas by randomly selecting 140 locations that were sampled at two depths (0 to 30 and 30 to 60 cm) and analyzed for soil salinity variables: soil electrical conductivity (EC), soluble cations (Ca^2+, Mg²⁺, Na⁺, and K⁺), soluble anions (SO ₄ ^2? , Cl^?), exchangeable Na⁺ (me 100 g^?1) and exchangeable sodium percentage. Terrain attributes (slope, topographical wetness index) were extracted from the digital elevation model of the study area. Variogram analyses after log transformation and ordinary kriging (OK) were applied to map spatial patterns of soil salinity variables. Multivariate geostatistical methods—regression kriging (RK) and kriging with external drift (KED)—were used using elevation and soil electrical conductivity data as covariates. Performances of the three estimation methods (OK, RK, and KED) were compared using independent validation samples randomly selected from the main dataset. Soils were categorized into salinity classes using disjunctive kriging (DK) and ArcGIS, and classification accuracy was tested using the kappa statistic. Results showed that soil salinity variables all have skewed distribution and are poorly correlated with terrain indices but have strong correlations among each other. Up to 65 % improvement was obtained in the estimations of soil salinity variables using hybrid methods over OK with the best estimations obtained with RK using EC_0–30 as covariate. DK–ArcGIS successfully classified soil samples into different salinity groups with overall accuracy of 75 % and kappa of 0.55 (p?<?0.001).     

Spatial assessment of water quality parameters in Jhelum city (Pakistan)

In this study, we assess the drinking water quality of Jhelum city. Two hundred and ninety-two drinking water samples were randomly collected in the study area. These samples were chemically analyzed for three key toxic (in excess) elements such as pH, total dissolved solids (TDS), and calcium. Geostatistical techniques such as variogram and kriging were used to investigate the spatial variations of these minerals across the city. The spatial structure for each element was found to be anisotropic, and thus, anisotropic variograms were used. The kriging predictions revealed significant concentrations of the above-stated elements at some locations in the study area. While comparing with the World Health Organization, United States Environmental Protection Agency, and Pakistan Environmental Protection Agency standards, the water samples were found to be unsatisfactory for drinking. We conclude that the drinking water in this region is of poor quality and needs proper treatment to make it palatable.     

Spatial assessment of groundwater quality in Mamundiyar basin, Tamil Nadu, India

Understanding the groundwater quality is important as it is the main factor determining its suitability for drinking, domestic, agricultural, and industrial purposes. In order to assess the groundwater quality, 30 groundwater samples have been collected in year 2008. The water samples collected in the field were analyzed for electrical conductivity, pH, total dissolved solids (TDS), major cations like calcium, magnesium, sodium, potassium, and anions like bicarbonate, carbonate, chloride, nitrate, and sulfate, in the laboratory using the standard methods given by the American Public Health Association. The groundwater locations were selected to cover the entire study area and attention was been given to the area where contamination is expected. The expected groundwater contaminants were chloride, nitrate, TDS, etc. The results were evaluated in accordance with the drinking water quality standards given by the World Health Organization (WHO 1993). To know the distribution pattern of the concentration of different elements and to demarcate the higher concentration zones, the contour maps for various elements were also generated, discussed, and presented.     

Spatial distribution and potential ecologic risk assessment of heavy metals in the sediments of the Nansi Lake in China

The contamination levels and ecological risks of heavy metals in the sediments of the Nansi Lake were investigated. The contents of Cd, Cr, Cu, Pb, Zn, Ni, and Co in the surface sediments collected at 20 sites ranged from 0.08 to 1.12, 58.92 to 135.62, 38.09 to 78.65, 24.51 to 53.95, 110.51 to 235.36, 11.30 to 65.40, and 4.12 to 20.14 mg/kg, respectively. The results of partitioning analysis revealed that the proportions of soluble and exchangeable fraction were less than 1 %, the proportions of carbonate, amorphous oxides, organic matter, and crystalline oxides fraction were less than 10 %, and 10.52 % of Cd was associated with carbonate. The average proportions in the residual fraction ranged from 48.62 % for Cu to 73.76 % for Ni, indicating low mobility and bioavailability. The geoaccumulation index (I _geo), relative enrichment factor (REF), sediment pollution index (SPI), and potential effect concentration quotient (PECQ) values of the heavy metals in the sediments were not in agreement with each another. The average REF values of Cd and Zn were higher than those of other metals. However, the average PECQ values were higher for Cr and Ni than those of other metals, indicating that these two metals would cause higher adverse biological effects. Therefore, it is suggested that future management and pollution control might focus on Cd, Zn, Cr, and Ni in the sediments of the Nansi Lake.     

Spatial variability of air pollutants in the city of Taranto, Italy and its potential impact on exposure assessment

Epidemiological studies typically use monitored air pollution data from a single station or as averaged data from several stations to estimate population exposure. In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the city of Taranto, which is one of the most highly industrialized cities in southern Italy. Epidemiological studies have revealed several critical situations in this area, in terms of mortality excess and short-term health effects of air pollution. The aims of this paper are to study the variability of air pollutants in the city of Taranto and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data (SO2, NO2, PM10), measured simultaneously and continuously during the period 2006–2010 in five air quality stations, were analyzed. Relative and absolute spatial concentration variations were investigated by means of statistical indexes. Results show significant differences among stations. The highest correlation between stations was observed for PM10 concentrations, while critical values were found for NO2. The worst values were observed for the SO2 series. The high values of 90th percentile of differences between pairs of monitoring sites for the three pollutants index suggest that mean concentrations differ by large amounts from site to site. The overall analysis supports the hypothesis that various parts of the city are differently affected by the different emission sources, depending on meteorological conditions. In particular, analysis revealed that the influence of the industrial site may be primarily identified with the series of SO2 data which exhibit higher mean concentration values and positive correlations with wind intensity when the monitoring station is downwind from the industrial site. Results suggest evaluating the population exposure to air pollutants in industrialized cities by taking into account the possible zones of influence of different emission sources. More research is needed to identify an indicator, which ought to be a synthesis of several pollutants, and take into account the meteorological variables.     

Coastal dune systems and disturbance factors: monitoring and analysis in central Italy

This study describes the conservation status of dune systems in relation to disturbance factors in the coastal stretch of the Viterbo province, Latium Region, Italy. Particular emphasis was given to the bioindication value of plant communities and their sequence. Each plant community was considered as a "habitat" in accordance with Annex I of the Directive 92/43/EU. Stress factors, such as sand dynamic and erosion, and anthropogenic pressures, such as trampling and bathing settlements, influence the sequence of habitats and weaken the system of relations that makes these coenoses to occur in extreme conditions. The choice to carry out surveys along wide transects, recording different data, allowed to explore the use of habitats as bioindicators. Comparing sites characterized by the same extension in a homogeneous area, it was possible to expand the use of canonical correspondence analysis (CCA) as a tool to correlate habitat composition and disturbance factors. The application of CCA showed a high correlation of degradation and habitat loss with coastal erosion, trampling and presence of waste. Furthermore, floristic surveys allowed the application of different biodiversity indices to quantify species richness of sampled areas. The conservation status of the sites investigated was found to be diverse, from the total disappearance of the mobile dune habitats to their complete sequence. The proposed methodology has been useful to fulfill the objective of the work and is applicable to other case studies in the Mediterranean.     

Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.     

Health,safety, and environmental risk assessment of steel production complex in central Iran using TOPSIS

This research was carried out with the aim of presenting an environmental management plan for steel production complex (SPC) in central Iran. Following precise identification of the plant activities as well as the study area, possible sources of environmental pollution and adverse impacts on the air quality, water, soil, biological environment, socioeconomic and cultural environment, and health and safety of the employees were determined considering the work processes of the steel complex. Afterwards, noise, wastewater, and air pollution sources were measured. Subsequently, factors polluting the steel complex were identified by TOPSIS and then prioritized using Excel Software. Based on the obtained results, the operation of the furnaces in hot rolling process with the score 1, effluent derived from hot rolling process with the score 0.565, nonprincipal disposal and dumping of waste at the plant enclosure with the score 0.335, walking beam process with the score 1.483 respectively allocated themselves the highest priority in terms of air, water, soil and noise pollution. In terms of habitats, land cover and socioeconomic and cultural environment, closeness to the forest area and the existence of four groups of wildlife with the score 1.106 and proximity of villages and residential areas to the plant with the score 3.771 respectively enjoyed the highest priorities while impressibility and occupational accidents with the score 2.725 and cutting and welding operations with score 2.134 had the highest priority among health and safety criteria. Finally, strategies for the control of pollution sources were identified and Training, Monitoring and environmental management plan of the SPC was prepared.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

Ecosystem classification for EU habitat distribution assessment in sandy coastal environments: An application in central Italy

Many recent developments in coastal science have gone against the demands of European Union legislation. Coastal dune systems which cover small areas of the earth can host a high level of biodiversity. However, human pressure on coastal zones around the world has increased dramatically in the last 50 years. In addition to direct habitat loss, the rapid extinction of many species that are unique to these systems can be attributed to landscape deterioration through the lack of appropriate management. In this paper, we propose to use of an ecosystem classification technique that integrates potential natural vegetation distribution as a reference framework for coastal dune EU Habitats (92/43) distribution analysis and assessment. As an example, the present study analyses the EU Habitats distribution within a hierarchical ecosystem classification of the coastal dune systems of central Italy. In total, 24 land elements belonging to 8 land units, 5 land facets, 2 land systems and 2 land regions were identified for the coastal dunes of central Italy, based on diagnostic land attributes. In central Italy, coastal dune environments including all the beach area, mobile dunes and all the fixed-dune land elements contain or could potentially hold at least one EU habitat of interest. Almost all dune slack transitions present the potentiality for the spontaneous development of EU woodlands of interest. The precise information concerning these ecosystems distribution and ecological relationships that this method produces, makes it very effective in Natura 2000 European network assessment. This hierarchical ecosystem classification method facilitates the identification of areas to be surveyed and eventually bound, under the implementation of EU Habitat directive (92/43) including areas with highly disturbed coastal dune ecosystems.     

Application of SMR to Modeling Watersheds in the Catskill Mountains

Very few hydrological models commonly used in watershed management are appropriate for simulating the saturation excess runoff. The Soil Moisture Routing model (SMR) was developed specifically to predict saturation excess runoff from variable source areas, especially for areas where shallow interflow controls saturation. A recent version of SMR was applied to two rural catchments in the Catskill Mountains to evaluate its ability to simulate the hydrology of these systems. Only readily available meteorological, topographical, and landuse information from published literature and governmental agencies was used. Measured and predicted streamflows showed relatively good agreement; the average Nash–Sutcliffe efficiency for the two watersheds were R ²=72% and R ²=63%. Distributed soil moisture contents and the locations of hydrologically sensitive areas were also predicted well.