European Farmland Bird Distribution Explained by Remotely Sensed Phenological Indices

Birds are important components of biodiversity conservation since they are capable of indicating changes in the general status of wildlife and of the countryside. The Pan-European Common Bird Monitoring Scheme (PECBM) has been launched by the BirdLife Partnership in Europe, where the European Bird Census Council has been collecting data from 20 independent breeding bird survey programs across Europe over the last 25 years. These data show dramatic declines in European farmland birds. We suggest that seasonal characteristics of vegetation cover derived from high temporal resolution remote sensing images could facilitate the monitoring the suitability of farmland bird habitats, and that these indicators may be a better choice for monitoring than climate data. We used redundancy analysis to link the PECBM data of the estimated number of farmland birds in Europe to a set of phenological and climatic indicators and to the biogeographic regions of Europe. Variance partitioning was used to account for the variation explained by the phenological and climate variables and by the area of the environmental strata individually, to define the pure effect of the variables, and to extract the total explained variance. The analysis revealed high statistical significance (p < 0.001) of the correlations between species and environment. Phenological indices explained 38% of the variance in community composition of the 23 farmland bird species, whereas climate explained 30% of the variance. After partitioning the other variables as covariables, the pure effect of phenology, climate, and environmental strata were 16%, 8%, and 16%, respectively. Based on the probability results, we suggest that phenological indicators derived from remote sensing may supply better indicators for continental scale biodiversity studies than climate only. In addition, these indicators are cost and time effective, are on continuous scale, and are readily repeatable on a large spatial coverage while supplying standardized results.     

Live diatoms as indicators of urban stormwater runoff

Diatom bioassessment of streams/rivers does not distinguish between live (cells with intact chloroplasts) and dead (empty cells) individuals, even though most diatom samples collected from the field will be composed of a mixture of both. This study aimed to evaluate whether percentage of live diatoms (PLD), live diatom density and chlorophyll a, and diatom species compositions can be used as indicators of hydrologic disturbance in an urban stream. We deployed artificial substrates on a monthly basis and collected periphyton samples weekly over the course of one calendar year (n = 182) in three tributaries of urbanized Ruddiman Creek (Michigan, USA). We also collected samples before and after six major storm events (>0.5 cm rain). We found no temporal patterns in PLD (Mann-Kendall test p > 0.05) or species composition (non-metric multidimensional scaling (NMDS) ordination), which may be explained by a diatom composition already tolerant to frequent disturbance. There was no difference in PLD before and after storm events, which might partially be explained by their disturbance resistance due to different assemblage ages (1, 2, and 4 weeks old) before the storms. High flow had differential effects on diatom species; loosely attached Navicula and Nitzschia species were more easily removed compared to stalk-forming Gomphonema parvulum. The most important environmental variable that was found to affect live diatom density and chlorophyll was stream width, which has an indirect effect (as a measure of discharge) on periphyton assemblages. In conclusion, PLD was found to be unsuitable metric for assessing stormwater runoff in urban streams where periphyton may not have enough time to form mature communities.     

Variations in seasonal phytoplankton assemblages as a response to environmental changes in the surface waters of a hypo saline coastal station along the Bhagirathi�CHooghly estuary

Due to the close proximity of the Bay of Bengal and the freshwater inflow of Bhagirathi-Hooghly, Diamond Harbour appeared as an important coastal station of the Bhagirathi-Hooghly estuary. The spatial and temporal composition and abundance of microphytoplankton species was examined in relation to physical and chemical surface water variables (i.e., salinity, nutrient, and temperature).The primary objective of the study was to observe the variations in phytoplankton species assemblages as a response to environmental variables. Hierarchical cluster analysis and non-metric multidimensional scaling were used to find out distinct seasonal groups based on the composition of phytoplankton. The results indicate that several key environmental factors like temperature, DIN content, and molar ratio of nutrients like DIN-DIP and DIN-DSi influenced seasonal phytoplankton assemblages within the estuary. The distribution of phytoplankton population showed two main groups where the blue-green and green algal populations favored the warmer conditions of summer and monsoon months, whereas the diatom population primarily flourished in the cooler months of autumn and winter.     

湖泊微生物群落构建机制及研究展望

湖泊微生物生态过程研究是深入了解湖泊生态系统结构与功能的关键。论述了湖泊微生物多样性时空分布规律及群落构建机制研究进展,总结了微生物群落构建机制的分析方法,介绍了微生物生态网络构建原理及应用。群落构建机制分析方法分为统计分析法、模型推断法和生态网络分析法。统计分析法包括群落结构差异分析、群落结构-环境因子关联分析和方差分解分析等,此类方法能够初步识别驱动群落组成与结构时空差异的影响因子,判别空间因素与已知环境变量对群落构建过程的相对贡献;模型推断法包括中性群落模型方法和零模型方法等,能够进一步实现对群落构建生态过程的区分,量化和比较随机性因素及确定性因素的相对重要性;生态网络分析法可用于揭示物种共现模式,探究作为确定性因素的生物相互作用,也可用于物种-环境响应关系的研究,探究环境选择过程对群落结构的影响。     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

CORINE land cover and floristic variation in a Mediterranean wetland

The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.     

Biomonitoring acidic drainage impact in a complex setting using periphyton

Acid mine drainage (AMD) often exerts various environmental pressures on nearby water courses: chemical stress from low pH and dissolved metals; physical stress from metal oxide deposits. Affected streams can thus display a spatially variable combination of stress agents that may complicate its biomonitoring using native communities such as periphyton. Here, we have measured water and periphyton variables in four streams that surround an abandoned copper mine to determine which periphyton attributes consistently detected AMD impact in a complex environmental setting. Seventeen years after the end of commercial exploitation, the abandoned mine still decreases water quality in nearby streams: moderate acidification, very high metal load (Al, Ni, Cu, Zn), and a conspicuous presence of metal oxide deposits with diverse composition. Even under the resultant complex pattern of polluted conditions, periphyton was a reliable bioindicator of AMD. Epilithic diatom taxa tolerant of acidic conditions increased in AMD sites and, at severely impacted locations, species richness decreased. Also, algal biomass may have been negatively affected in some stream reaches affected by metal oxide deposits. Other periphyton attributes (total biomass, diatom diversity) seemed mostly unrelated to AMD. Diatom assemblage composition was the most sensitive and consistent bioindicator of mine drainage; besides, it rendered a biological assessment of AMD impact that largely coincided with the physicochemical evaluation. Still, including other taxonomic (proportion of acid-tolerant diatom species, diatom richness) and non-taxonomic (algal biomass) attributes in the biomonitoring procedure rendered a more comprehensive assessment of the negative consequences generated by AMD.     

Visually determined stream mesohabitats influence benthic macroinvertebrate assessments in headwater streams

Mesohabitat components such as substrate and surface flow types are intimately related to benthic macroinvertebrate assemblages in streams. Visual assessments of the distribution of these components provide a means of evaluating physical habitat heterogeneity and aid biodiversity surveys and monitoring. We determined the degree to which stream site and visually assessed mesohabitat variables explain variability (i.e., beta-diversity) in the relative abundance and presence-absence of all macroinvertebrate families and of Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera. We systematically sampled a wide variety of mesohabitat arrangements as they occured in stream sites. We also estimated how much of the explanation given by mesohabitat was associated with substrate or surface flow types. We performed variation partitioning to determine fractions of explained variance through use of partial redundancy analysis (pRDA). Mesohabitats and stream sites explained together from 23 to 32 % of the variation in the four analyses. Stream site explained 8–11 % of that variation, and mesohabitat variables explained 13–20 %. Surface flow types accounted for >60 % of the variation provided by the mesohabitat component. These patterns are in accordance with those obtained in previous studies that showed the predominance of environmental variables over spatial location in explaining macroinvertebrate distribution. We conclude that visually assessed mesohabitat components are important predictors of assemblage composition, explaining significant amounts of beta-diversity. Therefore, they are critical to consider in ecological and biodiversity assessments involving macroinvertebrates.     

Ecosystem classifications based on summer and winter conditions

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.     

Microphytobenthic biomass,species composition and environmental gradients in the mangrove intertidal region of the Andaman Archipelago,India

Monthly sampling in mangrove intertidal sediments of Andaman Archipelago was carried out during a 1-year study (January to December, 2013) in order to analyse the spatial and temporal distribution of microphytobenthos (MPB) and MPB biomass (sediment chlorophyll-a (chl-a)) in the surficial layer 0–1 cm. The MPB community was mainly composed of diatoms. The MPB biomass concentration in surface sediment (0–1 cm) ranged from 0.7 to 16.98 μg cm^?3. Population density of benthic diatoms varied from 78 to 224 ind cm^?3. This study identified 41 diatom taxa (27 pennate diatoms, 14 centric diatoms) in the sediment, and among all the diatom taxa, we distinguished few true planktonic species—Coscinodiscus centralis, Coscinodiscus marginatus, Leptocylindricus danicus, Planktoniella sol, Thalassiosira decipiens, Thalassionema nitzschioides and Thalassiothrix longissima. Overall, a high percentage of diatoms were pennate (81%) as opposed to centric. Based on benthic diatom abundance, species composition and distribution, MPB assemblages of sampling stations were grouped into two distinct clusters: one with St. 1 and St. 3 and another one with St. 2 and St. 4. Canonical correspondence analysis (CCA) revealed seasonality as the most important factor determining variability in diatom species composition among sampling sites. There was a distinct seasonal pattern in MPB biomass distribution and benthic diatom cell density during monsoon and post-monsoon seasons. Our results suggest that among various physical and chemical variables studied, greater levels of overlying water nutrients and sediment textures significantly correlated and were conducive factors for MPB. This is the first detailed study on the MPB from these mangrove sediments, providing benchmark data for future studies about these remote groups of Andaman and Nicobar Islands.     

太阳山湿地浮游植物优势功能群季节演替特征及驱动因子分析

为探明太阳山湿地浮游植物优势功能群季节演替规律及其主要驱动因子,于2019年4月(春季)、7月(夏季)、10月(秋季)和2020年1月(冬季)采样分析了太阳山湿地浮游植物的种类组成、优势种、丰度、生物量及季节变化,同时测定了水环境理化因子指标,采用冗余分析方法研究了浮游植物优势功能群的优势度、丰度与水环境因子之间的关系。结果表明:太阳山湿地浮游植物可分为22个功能类群;优势功能群的季节演替和空间分异特征明显,存在一定的规律性。春、秋、冬3个季节的浮游植物以硅藻门为主,夏季以绿藻门和蓝藻门为主。春季优势功能群主要为D、C、P,以硅藻门种类为主;夏季优势功能群主要为J、Lo、TC、M、H1,以硅藻门、绿藻门、蓝藻门种类为主;秋季优势功能群主要为D、S1、MP,以硅藻门、绿藻门种类为主;冬季优势功能群主要为D、X3,以硅藻门种类为主。影响太阳山湿地浮游植物优势功能群季节演替的水环境因子有水温(WT)、pH、溶解氧(DO)、透明度(SD)、盐度(Sal)、氮磷营养元素含量、化学需氧量(COD_Cr)和高锰酸盐指数(COD_Mn)。4个湖区浮游植物优势功能群的时空差异与水环境因子密切相关,其中,西湖区浮游植物优势功能群的季节演替驱动因子为pH、DO、WT、总磷(TP),东湖区为pH、DO、WT、氮磷营养元素含量,南湖区为pH、DO、COD_Cr、五日生化需氧量(BOD₅),小南湖区为pH、DO、WT、BOD₅、COD_Cr、TP。pH、DO、WT、BOD₅、SD等水环境因子的季节差异以及TP、TN、氨氮(NH₃-N)、COD_Mn等水环境因子的湖区差异是太阳山湿地浮游植物优势功能群出现季节演替的主要原因。     

Analysis of macroinvertebrate assemblages in relation to environmental gradients among lotic habitats of California's Central Valley

We assessed relationships between environmental characteristicsand macroinvertebrate assemblages in lotic habitats of California's Central Valley with community metric and multivariate statistical approaches. Using canonical ordinationanalyses, we contrasted results when assemblage structure was assessed with macroinvertebrate metrics, as suggested for use inindices of biotic integrity, or with genera abundances. Our objectives were to identify metrics or taxa diagnostic of loticenvironmental stressors and compare the capacity of theseapproaches to detect stressors in order to suggest how they mightbe used to diagnose stressors. For macroinvertebrate metrics,redundancy analysis (RDA) extracted three axes correlated withchannel morphology and substrates. For genera abundances, canonical correspondence analysis (CCA) extracted two axescorrelated with soluble salts and with channel morphology andsubstrates but did not separate these gradients onto differentaxes. Cluster analyses identified five RDA and five CCA sitegroups, which exhibited differences for environmental variables,metrics, or genera abundances, and agreement between the analysesin partitioning of sites was greater than if sites were partitioned randomly. These approaches differ in their abilityto detect environmental stressors, because they measure differentaspects of assemblages and would be complementary in design ofnew metrics diagnostic of stressors.     

Energy-Based Land Use Predictors of Proximal Factors and Benthic Diatom Composition in Florida Freshwater Marshes

The Landscape Development Intensity index (LDI), which is based on non-renewable energy use and integrates diverse land use activities, was compared to other measures of LU (e.g., %agriculture, %urban) to determine its ability for predicting benthic diatom composition in freshwater marshes of peninsular Florida. In this study, 70 small, isolated herbaceous marshes located along a human disturbance gradient (generally agricultural) throughout peninsular Florida were sampled for benthic diatoms and soil and water physical/chemical parameters (i.e., TP, TKN, pH, specific conductance, etc.). Landscape measures of percent agriculture, percent urban, percent natural, and LDI index values were calculated for a 100 m buffer around each site. The strongest relationships using Mantel's r statistic, which ranges from −1 to 1, were found between benthic diatom composition, the combined soil and water variables, and LDI scores (r=0.51, P<0.0001). Although similar, soil and water variables alone (r=0.45, P<0.0001) or with percent agriculture or percent natural were not as strongly correlated (both Mantel's r=0.46, P<0.0001). Little urban land use was found in the areas surrounding the study wetlands. Diatom data were clustered using flexible beta into 2 groups, and stepwise discriminant analysis identified specific conductance, followed by LDI score, soil pH, water total phosphorus, and ammonia, as cluster-separating variables. The LDI explained slightly more of the variation in species composition than either percent agriculture or percent natural, perhaps because the LDI can combine disparate land uses into a single quantitative value. However, the ecological significance of the difference between land use metrics and diatom composition is controvertible, and additional tests including more varied land uses appear warranted.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

Microbiological and physical–chemical water quality of the rice fields in Sinos River’s basin, Southern Brazil

In this study, we evaluate spatial and temporal variations of the water’s quality used in rice fields. Every 15 days during the different phases of cultivation of the rice—vegetative, reproductive, and maturity—samples were collected from the main irrigation channel, from the surface water in the field, and from the excess-water drainage channel. The differences in the values of 13 variables were analyzed by the analysis of variance system and by the Principal Component Analysis (PCA) technique. The results demonstrate that the values observed for the presence of total coliforms, heat-tolerant coliforms, and pH were higher in the irrigation water and that the calcium and magnesium components were greater in the drainage water. The PCA results indicate that three groups of variance exist and that these three account for 77 % of the observed variances. The first principal component, (39 % of the variances), includes the variables pH, phosphorus, potassium, carbon, and turbidity; the second (28.1 %), calcium, magnesium, and conductivity; while the third accounts for only 9.9 % of the variation and incorporates the variable biological thermotolerant coliforms. The spatial pattern resulting from the distribution of the sampling locations as regards the first two principal components indicates a difference between the irrigation and drainage waters. The variables of the first and third items (except for the turbidity in the second component) reach higher values in the irrigation water, while the variables associated with the second component have higher values in the drainage water. The information provided is important for the analysis of the influence exercised by plantation management decisions on the microbiological, physical, and chemical quality of the water. The results confirm the ability of paddy rice field to filter out some of the chemicals and coliforms from the irrigation water as it passes through the agro ecosystem.     

Correspondence of biological condition models of California streams at statewide and regional scales

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n?=?1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n?≤?75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.     

Can Basin Land Use Effects on Physical Characteristics of Streams Be Determined at Broad Geographic Scales?

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed.     

Assessment of surface water quality using multivariate statistical techniques: a case study of Behrimaz Stream, Turkey

Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis, and factor analysis, were applied for the evaluation of temporal/spatial variations and for the interpretation of a water quality data set of the Behrimaz Stream, obtained during 1 year of monitoring of 20 parameters at four different sites. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified four monitoring sites into two groups (group A and group B), i.e., relatively less polluted (LP) and medium polluted (MP) sites, based on similarities of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the two different groups obtained from cluster analysis, resulted in five latent factors amounting to 88.32% and 88.93% of the total variance in water quality data sets of LP and MP areas, respectively. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to discharge, temperature, and soluble minerals (natural) and nutrients (nonpoint sources: agricultural activities) in relatively less polluted areas; and organic pollution (point source: domestic wastewater) and nutrients (nonpoint sources: agricultural activities and surface runoff from villages) in medium polluted areas in the basin. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and interpretation of data sets and, in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective stream water quality management.     

Influence of spatial resolution on assessing channelization impacts on fish and macroinvertebrate communities in a warmwater stream in the southeastern United States

The choice of spatial and temporal scale used in environmental assessments may influence the observed results. One method of assessing the impact of stream habitat alterations involves the comparison of response variables among treatment categories (i.e., impacted and unimpacted sites). The influence of spatial resolution on patterns of response variables among treatment categories in assessments of stream channelization and other types of habitat alterations has not been evaluated. We examined how patterns of 10 community response variables among channel types and our interpretations of channelization impacts on fish and macroinvertebrate communities differed among three spatial resolutions in a warmwater stream in Mississippi and Alabama. Four fish and three macroinvertebrate community response variables exhibited different patterns among channel types at different spatial resolutions. Our interpretations of the impacts of channelization on fish and macroinvertebrate communities differed among spatial resolutions. Channelization had a negative influence on fish communities either with or without evidence of potential community recovery in one channel type. Channelization impacts on macroinvertebrate communities ranged from a negative influence to no effect. Our results suggest that spatial resolution can influence the observed results and interpretations derived from assessments of stream habitat alterations.     

Diatoms as indicators in the Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW)

As a part of the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program-Surface Waters (EMAP-SW), sedimentary diatom assemblages were studied from 66 lakes in the northeastern U.S.A. to evaluate the applicability of diatoms for this nation-wide monitoring program. Sediment cores were collected from the study lakes and diatoms were analyzed from the top (present-day) and bottom (pre-industrial) sediment samples. Canonical correspondence analysis (CCA) was used to examine which environmental variables correlate most closely with the distributions of diatom taxa in the top (surface) samples. Forward selection and Monte Carlo permutation tests showed that diatom species distributions were significantly related to total lakewater phosphorus (TP), pH, chloride, Secchi depth, and lake size and maximum depth. We developed weighted-averaging calibration and regression models for inferring TP (r ²=0.62), chloride (r ²=0.61), pH (r ²=0.86), and Secchi depth (r ²=0.62). An index of overall lake disturbance was also developed. Our diatom data indicate that marked changes have occurred in the study lakes since pre-industrial times as a result of anthropogenic activity.