Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Changes in the sorption and rate of 17β-estradiol biodegradation by dissolved organic matter collected from different water sources

The potential biodegradation and subsequent transformation of 17β-estradiol (E2) to estrone (E1) were examined in the presence of various dissolved organic matter (DOM) isolated from effluent, river and lake waters. In addition, estrogenicity was estimated in association with the removal of E2 via its sorption onto DOM and biodegradation. The more biodegradable lake-derived DOM promoted more extensive transformation of E2 into E1 than the effluent organic matter through a biodegradation process. Overall, under all conditions, biodegradation dominated the removal of E2 in water. The increased dissolved organic carbon (DOC) concentrations in river and lake-derived DOM (e.g. 6.5 mg C L(-1)) reduced the removal of E2 by decreasing its biodegradation due to the moderate sorption of E2 onto DOM. The effluent organic matter showed greater removal of E2 via biodegradation, as well as significantly high sorption. This was associated with a large amount of hydrophobic fulvic acid (FA)- and humic acid (HA)-like organic components, as shown by the small increase in the specific UV absorbance at 254 nm (SUVA(254)). An increase in the DOC concentration reduced the removal of E2, resulting in high estrogenicity. The present study suggests that both organic composition and DOC concentration influenced the removal of E2 and, therefore, should be fully considered when assessing estrogenicity and its impacts on the aquatic environment.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Bioavailability of copper,cadmium, zinc,and lead in tropical savanna soils assessed by diffusive gradient in thin films (DGT) and ion exchange resin membranes

The technique of diffusion gradient in thin films (DGT) for assessing bioavailable metals has not been tested under field conditions. We assessed the relationships of DGT- and cation exchange resin-membrane-measured concentrations of Cd, Cu, Pb, and Zn with plant uptake of the metals under greenhouse and field conditions. In the greenhouse, the effective concentrations of Cu, Pb, and Zn by DGT correlated significantly with uptake by sorghum (Sorghum bicolor), but cation exchange resin-membrane-measured concentrations of Cd, Pb, and Zn did not correlate with sorghum uptake. In the field, the DGT-measured concentrations of Cd, Pb, and Zn were not linearly related to uptake Cd, Pb, and Zn by lettuce (Lactuca sativa) except for Cu uptake (r = 0.87, p < 0.05). Similarly, it was only the resin-membrane-extractable Pb that correlated with Pb uptake by lettuce (r = 0.77; p < 0.05). However, fitting non-linear regression models improved the plant metal uptake predictions by DGT-measured bioavailable Cd, Cu, Pb, and Zn under field conditions. In conclusion, the DGT technique was fairly predictive of bioavailability in the greenhouse, but not in the field.     

Trace element concentrations in surface estuarine and marine sediments along the Mississippi Gulf Coast following Hurricane Katrina

Hurricanes are relatively frequent ecological disturbances that may cause potentially long-term impacts to the coastal environment. Hurricane Katrina hit the Mississippi Gulf Coast in August 2005, and caused a storm surge with the potential to change the trace element content of coastal surface sediments. In this study, surface estuarine and marine sediments were collected monthly following the storm from ten sites along the Mississippi Gulf Coast (Mobile Bay, Grand Bay Bayous Heron and Cumbest, Pascagoula, Ocean Springs, Biloxi Gulf, Back Biloxi Bay, Gulfport Gulf, Gulfport Courthouse Rd, and Gulfport Marina). Concentrations of V, Cr, Mn, Fe, Co, Ni, Zn, As, Cd, and Pb were measured by inductively coupled plasma–mass spectrometry to evaluate their temporal and spatial variations in the year following Hurricane Katrina. Sediments were characterized by pH, particle size distribution and total carbon and nitrogen content. Trace element contents of the sediments were determined in both <2 mm and <63 μm grain size fractions. Results revealed no significant temporal and spatial variability in trace element concentrations, in either size fraction. Potential ecological risk of the sediments was assessed by using NOAA SQuiRTs’ guideline values; most concentrations remained below probable adverse effects guidelines to marine organisms suggesting that trace elements redistributed by Hurricane Katrina would not cause an adverse impact on resident organisms. Instead, the concentrations of trace elements were site-dependent, with specific contaminants relating to the use of the area prior to Hurricane Katrina.     

An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.     

Evaluation of concentration efficiency of the Pseudomonas aeruginosa phage PP7 in various water matrixes by different methods

Enteric viruses monitoring in surface waters requires the concentration of viruses before detection assays. The aim of this study was to evaluate different methods in terms of recovery efficiencies of bacteriophage PP7 of Pseudomonas aeruginosa, measured by real-time PCR, using it as a viral control process in water analysis. Different nucleic acid extraction methods (silica–guanidinium thiocyanate, a commercial kit (Qiagen Viral RNA Kit) and phenol–chloroform with alcohol precipitation) exhibited very low recovery efficiencies (0.08–4.18 %), being the most efficient the commercial kit used for subsequent experiments. To evaluate the efficiency of three concentration methods, PBS (as model for clean water) and water samples from rivers were seeded to reach high (HC, 10⁶ pfu ml^?1) and low concentrations (LC, 10⁴ pfu ml^?1) of PP7. Tangential ultrafiltration proved to be more efficient (50.36?±?12.91, 17.21?±?9.22 and 12.58?±?2.35 % for HC in PBS and two river samples, respectively) than adsorption–elution with negatively charged membranes (1.00?±?1.34, 2.79?±?2.62 and 0.05?±?0.08 % for HC in PBS and two river samples, respectively) and polyethylene glycol precipitation (15.95?±?7.43, 4.01?±?1.12 and 3.91?±?0.54 %, for HC in PBS and two river samples, respectively), being 3.2–50.4 times more efficient than the others for PBS and 2.7–252 times for river samples. Efficiencies also depended on the initial virus concentration and aqueous matrixes composition. In consequence, the incorporation of an internal standard like PP7 along the process is useful as a control of the water concentration procedure, the nucleic acid extraction, the presence of inhibitors and the variability of the recovery among replicas, and for the calculation of the sample limit of detection. Thus, the use of a process control, as presented here, is crucial for the accurate quantification of viral contamination.     

The effect of changes in land use on nitrate concentration in water supply wells in southern Chester County, Pennsylvania

An analysis of private potable water well data was conducted for seven single family residential developments in southern Chester County, Pennsylvania. Background data were available for 165 wells within the communities when the wells were first drilled in the 1980s and early 1990s. Sampling of 75 wells within these same communities was performed in 2006 to determine whether conversion of the land to residential housing along with the use of conventional on-lot septic systems had resulted in elevated concentration of nitrate-nitrogen in the drinking water aquifer. The data indicate that prior land use influenced the occurrence of nitrate-nitrogen in the drinking water aquifer. The median nitrate-nitrogen concentration for the 165 wells in the background dataset was 2.9 mg/L. One hundred-seven of those wells were drilled on land previously used for active agricultural purposes. The median nitrate concentration in these wells was 3.8 mg/L. Of 48 wells drilled on forested land, the median nitrate concentration was 1.1 mg/L, approximately 3.5 times lower than those drilled on active agricultural land. The median nitrate concentration in the 2006 sampling dataset was 3.6 mg/L, an increase of 0.7 mg/L. The data indicate that conversion of the land has not resulted in contamination of the drinking water aquifer with respect to nitrate-nitrogen. Likewise, the data suggest that the conversion has not resulted in significant improvements to overall water quality.