Adjusting the effect of seasonal variability in the bioassessment of streams

Bioassessment tools should distinguish between the effects of anthropogenic degradation in communities and natural temporal changes. The present study tests the influence of natural seasonal variability on macroinvertebrate stream communities assessed by a predictive model (PORTRIV) and a multimetric index (IPtI) calibrated for spring. The scores of PORTRIV decreased significantly between spring and autumn, and between spring and winter (ca. 37 to 53 %, respectively), while those of IPtI did not change significantly between seasons. For non-reference samples, the results of the predictive model also indicate no significant differences. A correction factor (CF) was calculated to adjust the existing differences in the model assessments between seasons, based on the percentage of variation of reference site scores from spring to autumn and winter. After the application of the CF to the OE50 scores of spring reference samples, the differences were no longer significant. Independent reference validation sites confirmed this tendency. This method has the advantage of avoiding large efforts required for the construction of databases from other seasons and the development of new models to allow the assessment of streams in seasons other than spring. Further tests with models developed in regions with more marked seasonal changes should be done to confirm its wider applicability.     

Impact of water quality on bacterioplankton assemblage along Cértima River Basin (central western Portugal) assessed by PCR–DGGE and multivariate analysis

The information on bacterial community composition (BCC) in Portuguese water bodies is very scarce. Cértima River (central western Portugal) is known to have high levels of pollution, namely organic. In the present work, the BCC from a set of 16 water samples collected from Cértima River Basin and its main tributaries was characterized using 16S rDNA–denaturing gradient gel electrophoresis, a culture-independent molecular approach. Molecular data were related to environmental parameters through multivariate analysis to investigate potential impact of water pollution along the river. Principal component analysis using environmental data showed a water quality gradient from more pristine waters (at the mountain tributaries) to waters with increasingly eutrophic potential (such as Fermentelos Lake). This gradient was mainly defined by factors such as organic and inorganic nutrient sources, electrical conductivity, hydrogen carbonate concentration, and pH. Molecular results showed variations in BCC along Cértima River Basin but in the main river section, a Bacteroidetes phylotype (Flavobacterium sp.) proved to be dominant throughout the river course. Multivariate analysis suggests that spatial variation of BCC along the Cértima River Basin depended mainly on parameters such as Chl a, total suspended solid (TSS), total organic carbon, electrical conductivity, and HCO _boxclose^-_{3}^{-} levels. Bacteroidetes phylotypes were all related to higher electrical conductivity and HCO₃^-_{3}^{-} levels although some of these were also correlated with high SO₄^2-_{4}^{2-} and others with high soluble reactive phosphorus, nitrate, TN, and Kjeld-N levels. The Gammaproteobacteria occurrence was correlated with high SO₄^2-_{4}^{2-} levels. One of the Betaproteobacteria phylotypes showed to correlate with low redox potential (E_h) and high temperature, pH, TSS, and Chl a levels while another one showed a negative correlation with Chl a values.     

Assessment of microcystins in lake water and fish (Mugilidae, <Emphasis Type="Italic">Liza</Emphasis> sp.) in the largest Spanish coastal lake

Cyanobacteria dominance and cyanotoxin production can become major threats to humans and aquatic life, especially in warm shallow lakes, which are often dominated by cyanobacteria. This study investigates the occurrence and distribution of microcystins (MCYST) in water, cell-bound and in the tissues of the commercial mugilid Liza sp. in the largest, coastal, Spanish Mediterranean lake (Albufera of Valencia). This is the first report concerning microcystin accumulation in tissues of mugilid fish species. Considerable amounts of microcystins were found in the water and seston, which correlated with development of Microcystis aeruginosa populations in the lake. The MCYST concentrations found in Lake Albufera (mean 1.7 and 17 μg/L and maximum 16 and 120 μg/L in water and seston, respectively) exceeded by one to two orders of magnitude the guideline levels proposed by the World Health Organization and were higher than that reported in other lakes of the Mediterranean zone. The presence of MCYST was found in all the fishes studied and accumulated differently among tissues of the commercial species Liza sp. Toxin accumulation in fish tissues showed that although the target organ for MCYST was the liver, high concentrations of microcystins were also found in other analysed tissues (liver>intestine>gills>muscle). Human tolerable daily intake for microcystins is assessed relative to the WHO guidelines, and potential toxicological risks for humans, wildlife and related ecosystems of the lake are discussed.     

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.