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Biological monitoring programmes have gained popularity around the world particularly in southern Africa as they are fast, integrative and cost-effective approaches for assessing the effects of environmental stressors on aquatic ecosystems. This article reviews current efforts that have been made to use bioindicators (i.e. macroinvertebrates, diatoms and fish) in monitoring water resources and to summarise the challenges in employing these biological monitoring tools in southern Africa. In South Africa, macroinvertebrate (South African Scoring System (SASS)) and diatom based indices (e.g. South African diatom index (SADI)) have demonstrated their utility in identifying sources of impairment and determining the extent of impacts thus giving natural resource managers a scientifically defensible rationale for developing guidelines for conservation and management. Despite this advancement in South Africa, however, developing regionally appropriate quantitative tools for diagnosing ecosystem health is a pressing need for several other southern African countries. Together with sound scientific research, it is imperative for southern African countries to develop specific legislation and have mandated agencies, with proper training and funding to implement biomonitoring and bioassessments. We recommend for the advancement and adoption of biological criteria as an integrated approach to assessing the impact of human activities in riverine ecosystems of the southern African region., (Copyright © 2018. Published by Elsevier B.V.)

Elucidating the confounding influence of multiple environmental factors on benthic diatom communities is important in developing water quality predictive models for better guidance of stream management efforts. The objective of this study was to explore the relative impact of metal pollution and hydromorphological alterations in, addition to nutrient enrichment and organic pollution, on diatom taxonomic composition with the view to improve stream diatom-based water quality inference models. Samples were collected twice at 20 sampling stations in the tropical Manyame Catchment, Zimbabwe. Diatom, macroinvertebrate communities and environmental factors were sampled and analysed. The variations in diatom community composition explained by different categories of environmental factors were analysed using canonical correspondence analysis using variance partitioning (partial CCA). The following variations were explained by the different predictor matrices: nutrient levels and organic pollution - 10.4%, metal pollution - 8.3% and hydromorphological factors - 7.9%. Thus, factors other than nutrient levels and organic pollution explain additional significant variation in these diatom communities. Development of diatom-based stream water quality inference models that incorporate metal pollution and hydromorphological alterations, where these are key issues, is thus deemed necessary., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The aim of this study was to determine if benthic diatoms can be used as effective and reliable indicators of ionic composition and conductivity in different stream order categories. Samples were collected on two occasions from 22 sampling sites within the Bloukrans River system, Eastern Cape Province, South Africa. The data collected were subjected to multivariate statistical technique, i.e. CCA, to determine environmental gradients along which the diatom species were distributed as well as to elucidate hypothesised differences in community structure per stream order. Significant differences between the two sampling periods were observed in dissolved oxygen, temperature, Na, B, Ca, Zn, Cu, Cr, K, Fe, phosphate, conductivity, salinity and nitrate, while significant stream order variation was observed for conductivity, salinity, Mg, Ca and sediment nitrates. Study sites were grouped into two broad categories (stream order 1 and 2/3 sites) based on CCA. As pollution increased, low to moderate pollution-tolerant species such as Fragilaria tenera, Cyclostephanos dubius and Gyrosigma acuminatum were replaced by high pollution-tolerant species such as Nitzschia palea, Gomphonema parvulum, Tryblionella apiculata, Diploneis vulgaris and Staurosira elliptica. This shows that diatom assemblages are appropriate indicators of ionic composition/conductivity and hydromorphological characteristics (e.g. stream size) of running waters. The results highlight the importance of creating regional calibration datasets which will make it possible to develop procedures to determine conductivity and ion concentration effects on biota. [ABSTRACT FROM AUTHOR]

The objective of this study was to compare the responses of diatoms, macroinvertebrates and fish to agriculture, urbanization and mining in the Manyame River Basin. Water quality sampling and benthic diatom, macroinvertebrate and fish community data were collected in April (end of the rain season) and September (dry season) 2013 at 44 sampling stations spread out across three land-use categories: commercial agricultural, communal agricultural and urban-mining areas. Commercial agricultural areas were relatively pristine as they were characterized by mature deciduous riparian forest strips which acted as riparian buffers thus protecting water resources from nonpoint source pollution. In communal agricultural areas a combination of poor agricultural practices (stream bank cultivation, overgrazing, soil erosions) and high human population densities had negative effects on water quality of streams draining these areas. Streams in urban-mining areas were highly stressed, being impacted primarily by physical habitat degradation and both point and nonpoint sources of pollution. A suite of environmental variables that varied with land-use pattern was assessed to find the combination of variables that best explained patterns of biota community composition. Community metrics i.e. the Trophic Diatom Index (TDI) based on diatoms, the South African Scoring system version 5 (SASS 5) based on macroinvertebrates and the Fish Assemblage Integrity Index (FAII) were used to determine the ecological status of study streams in relation to human-induced stressors. Data were also subjected to multivariate statistical techniques; canonical correspondence analysis (CCA), mantel test and cluster analysis to determine environmental gradients along which the diatom, macroinvertebrate and fish assemblages were distributed as well as to elucidate hypothesized differences in response to stressors among communities per land-use type. Using CCA, we assessed the individual importance of a set of environmental variables on each biotic community structure. ANOVA, showed a significant difference ( p < 0.05) in physical and chemical variables among commercial agricultural, communal agricultural and urban-mining sampling stations with no significant differences ( p > 0.05) between the 2 sampling periods. Based on CCAs carried out using individual variables, the strengths of relationships between diatoms and macroinvertebrates was generally high for nutrient levels, organic and metal pollution and other variables. However, fish assemblages showed a relatively low association with all water quality variables in the study; this might be explained by the high abundance of omnivores and air breathers which are able to tolerate a variety of environmental conditions. These patterns were also confirmed by the mantel test as well as the other CCAs carried out to investigate the simultaneous effects of environmental variables. These findings indicate that diatoms are more powerful indicators in accessing ecological stream/river quality and have potential for application in routine monitoring programs in tropical streams. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the response of stream diatom assemblages to changes in water quality in different land-use settings. Water quality sampling and benthic diatom community data were collected in April and September 2013 at 95 sampling stations in the Manyame Catchment, Zimbabwe. The data collected were subjected to multivariate statistical techniques; CCA and cluster analysis to determine environmental gradients along which the diatom species were distributed as well as to elucidate hypothesized differences in community structure per land-use type. Three land-use categories were identified in this study: commercial agricultural, communal agricultural and urban-mining areas in order of increasing human disturbance. No significant differences in physical and chemical variables were recorded between the two sampling periods. Study sites were grouped into roughly three broad categories based on CCA and cluster analysis. As pollution increased, low to moderate pollution tolerant species such as Cocconeis placentula, Surirella linearis and Surirella robusta were replaced by high pollution tolerant species such as Pinnularia braunii, Tryblionella coarcata, Luticola goeppertiana and Stauroneis smithii. This shows that diatom assemblages are potential indicators of changes in water quality due to changes in catchment land-use. [ABSTRACT FROM AUTHOR]

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