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The clarification of drinking water leads to the production of large quantities of water treatment residuals (WTRs). DNA was extracted from six WTR samples collected from water treatment plants within the UK to compare their bacterial communities and examine whether factors such as coagulant usage (aluminium versus iron salt), the type of water source (reservoir or river), or leachable chemical composition influence these communities. Bacterial 16S variable region 4 (V4) was amplified and sequenced using Illumina MiSeq sequencing. The most abundant phyla in WTR samples were Proteobacteria, Actinobacteria, Bacteroidetes, Acidobacteria, and Firmicutes, collectively representing 92.77-97.8% of the total bacterial sequences. Statistical analysis of microbial profiles indicated that water source played a significant role in microbial community structure, diversity, and richness, however coagulant type did not. PERMANOVA analysis showed that no single chemical variable (pH, organic matter, or extractable element concentration) influenced microbial composition significantly; however, canonical correspondence analysis of WTR microbiomes yielded a model using all these variables that could be used to explain variations in microbial community structures of WTRs (p < 0.05). No common, potentially toxic cyanobacteria, or related pathogens of concern were found. Analysis with PICRUSt showed that WTRs all had similar predicted microbial functional profiles. Overall, the results indicate that WTRs analysed in this study are unlikely to pose any threat to soil microbial community structure when applied to land as a soil conditioner or enhancer and may help to enhance the soil microbial community., (© 2023. The Author(s).)

Pharmaceuticals are a ubiquitous group of emerging pollutants of considerable importance due to their biological potency and potential to elicit effects in wildlife and humans. Pharmaceuticals have been quantified in terrestrial, marine, fresh, and transitional waters, as well as the fauna and macro-flora that inhabit them. Pharmaceuticals can enter water ways through different human and veterinary pathways with traditional wastewater treatment, unable to completely remove pharmaceuticals, discharging often unknown quantities to aquatic ecosystems. However, there is a paucity of available information regarding the effects of pharmaceuticals on species at the base of aquatic food webs, especially on phytoplankton, with research typically focussing on fish and aquatic invertebrates. Diatoms are one of the main classes of phytoplankton and are some of the most abundant and important organisms in aquatic systems. As primary producers, diatoms generate ∼40 % of the world's oxygen and are a vital food source for primary consumers. Diatoms can also be used for bioremediation of polluted water bodies but perhaps are best known as bio-indicators for water quality studies. However, this keystone, non-target group is often ignored during ecotoxicological studies to assess the effects of pollutants of concern. Observed effects of pharmaceuticals on diatoms have the potential to be used as an indicator of pharmaceutical-induced impacts on higher trophic level organisms and wider ecosystem effects. The aim of this review is to present a synthesis of research on pharmaceutical exposure to diatoms, considering ecotoxicity, bioremediation and the role of diatoms as bio-indicators. We highlight significant omissions and knowledge gaps which need addressing to realise the potential role of diatoms in future risk assessment approaches and help evaluate the impacts of pharmaceuticals in the aquatic environment at local and global scales., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Rapidly assessing biodiversity is essential for environmental monitoring; however, traditional approaches are limited in the scope needed for most ecological systems. Environmental DNA (eDNA) based assessment offers enhanced scope for assessing biodiversity, while also increasing sampling efficiency and reducing processing time, compared to traditional methods. Here we investigated the effects of landuse and seasonality on headwater community richness and functional diversity, via spatio-temporal dynamics, using both eDNA and traditional sampling. We found that eDNA provided greater resolution in assessing biodiversity dynamics in time and space, compared to traditional sampling. Community richness was seasonally linked, peaking in spring and summer, with temporal turnover having a greater effect on community composition compared to localized nestedness. Overall, our assessment of ecosystem function shows that community formation is driven by regional resource availability, implying regional management requirements should be considered. Our findings show that eDNA based ecological assessment is a powerful, rapid and effective assessment strategy that enables complex spatio-temporal studies of community diversity and ecosystem function, previously infeasible using traditional methods.

Dissolved organic carbon (DOC) turnover in aquatic environments is modulated by the presence of other key macronutrients, including nitrogen (N) and phosphorus (P). The ratio of these nutrients directly affects the rates of microbial growth and nutrient processing in the natural environment. The aim of this study was to investigate how labile DOC metabolism responds to changes in nutrient stoichiometry using 14 C tracers in conjunction with untargeted analysis of the primary metabolome in upland peat river sediments. N addition led to an increase in 14 C-glucose uptake, indicating that the sediments were likely to be primarily N limited. The mineralisation of glucose to 14 CO 2 reduced following N addition, indicating that nutrient addition induced shifts in internal carbon (C) partitioning and microbial C use efficiency (CUE). This is directly supported by the metabolomic profile data which identified significant differences in 22 known metabolites (34% of the total) and 30 unknown metabolites (16% of the total) upon the addition of either N or P. 14 C-glucose addition increased the production of organic acids known to be involved in mineral P dissolution (e.g. gluconic acid, malic acid). Conversely, when N was not added, the addition of glucose led to the production of the sugar alcohols, mannitol and sorbitol, which are well known microbial C storage compounds. P addition resulted in increased levels of several amino acids (e.g. alanine, glycine) which may reflect greater rates of microbial growth or the P requirement for coenzymes required for amino acid synthesis. We conclude that inorganic nutrient enrichment in addition to labile C inputs has the potential to substantially alter in-stream biogeochemical cycling in oligotrophic freshwaters., (Copyright © 2019. Published by Elsevier B.V.)

Dissolved organic matter (DOM) represents a key component of carbon (C) cycling in freshwater ecosystems. While the behaviour of bulk dissolved organic carbon (DOC) in aquatic ecosystems is well studied, comparatively little is known about the turnover of specific DOC compounds. The aim of this study was to investigate the persistence of 14 C-labelled low molecular weight (LMW) DOC at a wide range of concentrations (0.1 µM to 10 mM), in sediments and waters from oligotrophic and mesotrophic rivers within the same catchment. Overall, rates of DOC loss varied between compound groups (amino acids > sugars = organic acids > phenolics). Sediment-based microbial communities contributed to higher DOC loss from river waters, which was attributed, in part, to its greater microbial biomass. At higher DOC compound concentrations, DOC loss was greater in mesotrophic rivers in comparison to oligotrophic headwaters. A lag-phase in substrate use within sediments provided evidence of microbial growth and adaptation, ascribed here to the lack of inorganic nutrient limitation on microbial C processing in mesotrophic communities. We conclude that the higher microbial biomass and available inorganic nutrients in sediments enables the rapid processing of LMW DOC, particularly during high C enrichment events and in N and P-rich mesotrophic environments.

Riparian areas, the interface between land and freshwater ecosystems, are considered to play a pivotal role in the supply of regulating, provisioning, cultural and supporting services. Most previous studies, however, have tended to focus on intensive agricultural systems and only on a single ecosystem function. Here, we present the first study which attempts to assess a wide range of ecological processes involved in the provision of the ecosystem service of water quality regulation across a diverse range of riparian typologies. Specifically, we focus on 1) evaluating the spatial variation in riparian soils properties with respect to distance with the river and soil depth in contrasting habitat types; 2) gaining further insights into the underlying mechanisms of pollutant removal (i.e. pesticide sorption/degradation, denitrification, etc.) by riparian soils; and 3) quantify and evaluate how riparian vegetation across different habitat types contribute to the provision of watercourse shading. All the habitats were present within a single large catchment and included: (i) improved grassland, (ii) unimproved (semi-natural) grassland, (iii) broadleaf woodland, (iv) coniferous woodland, and (iv) mountain, heath and bog. Taking all the data together, the riparian soils could be statistically separated by habitat type, providing evidence that they deliver ecosystem services to differing extents. Overall, however, our findings seem to contradict the general assumption that soils in riparian area are different from neighbouring (non-riparian) areas and that they possess extra functionality in terms of ecosystem service provision. Watercourse shading was highly habitat specific and was maximal in forests (ca. 52% shade cover) in comparison to the other habitat types (7-17%). Our data suggest that the functioning of riparian areas in less intensive agricultural areas, such as those studied here, may be broadly predicted from the surrounding land use, however, further research is required to critically test this across a wider range of ecosystems., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Soil organic matter (SOM) content is a key indicator of riparian soil functioning and in the provision of ecosystem services such as water retention, flood alleviation, pollutant attenuation and carbon (C) sequestration for climate change mitigation. Here, we studied the importance of microbial biomass and nutrient availability in regulating SOM turnover rates. C stabilisation in soil is expected to vary both vertically, down the soil profile and laterally across the riparian zone. In this study, we evaluated the influence of five factors on C mineralisation (C min ): (i) substrate quantity, (ii) substrate quality, (iii) nutrient (C, N and P) stoichiometry, (iv) soil microbial activity with proximity to the river (2 to 75 m) and (v) as a function of soil depth (0-3 m). Substrate quality, quantity and nutrient stoichiometry were evaluated using high and low molecular weight 14 C-labelled dissolved organic (DOC) along with different nutrient additions. Differences in soil microbial activity with proximity to the river and soil depth were assessed by comparing initial (immediate) C min rates and cumulative C mineralised at the end of the incubation period. Overall, microbial biomass C (MBC), organic matter (OM) and soil moisture content (MC) proved to be the major factors controlling rates of C min at depth. Differences in the immediate and medium-term response (42 days) of C min suggested that microbial growth increased and carbon use efficiency (CUE) decreased down the soil profile. Inorganic N and/or P availability had little or no effect on C min suggesting that microbial community growth and activity is predominantly C limited. Similarly, proximity to the watercourse also had relatively little effect on C min . This work challenges current theories suggesting that areas adjacent to watercourse process C differently from upslope areas. In contrast, our results suggest that substrate quality and microbial biomass are more important in regulating C processing rates rather than proximity to a river.

Dissolved organic matter (DOM) plays a central role in regulating productivity and nutrient cycling in freshwaters. It is therefore vital that we can representatively sample and preserve DOM in freshwaters for subsequent analysis. Here we investigated the effect of filtration, temperature (5 and 25°C) and acidification (HCl) on the persistence of low molecular weight (MW) dissolved organic carbon (DOC), nitrogen (DON) and orthophosphate in oligotrophic and eutrophic freshwater environments. Our results showed the rapid loss of isotopically-labelled glucose and amino acids from both filtered (0.22 and 0.45μm) and unfiltered waters. We ascribe this substrate depletion in filtered samples to the activity of ultra-small (<0.45μm) microorganisms (bacteria and archaea) present in the water. As expected, the rate of C, N and P loss was much greater at higher temperatures and was repressed by the addition of HCl. Based on our results and an evaluation of the protocols used in recently published studies, we conclude that current techniques used to sample water for low MW DOM characterisation are frequently inadequate and lack proper validation. In contrast to the high degree of analytical precision and rigorous statistical analysis of most studies, we argue that insufficient consideration is still given to the presence of ultra-small microorganisms and potential changes that can occur in the low MW fraction of DOM prior to analysis., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

We studied how soil pH (pHs 4 to 8) influenced the mineralization of low-molecular-weight (LMW)-dissolved organic carbon (DOC) compounds, and how this compared with differences in microbial community structure. The mineralization of LMW-DOC compounds was not systematically connected to differences in soil pH, consistent with soil respiration. In contrast, the microbial community compositions differed dramatically. This suggests that microbial community composition data will be of limited use in improving the predictive power of soil C models.