High-throughput amplicon sequencing and stream benthic bacteria: identifying the best taxonomic level for multiple-stressor research

Community structures of mangrove endophytic and rhizosphere bacteria in Zhangjiangkou National Mangrove Nature Reserve

Bacterial communities play an important role in mangrove ecosystems. In order to gain information on the bacterial communities in mangrove species and rhizospheres grown in Zhangjiangkou National Mangrove Nature Reserve, this study collected root, branch, and leaf samples from five mangrove species as well as rhizosphere and non-rhizosphere samples and analyzed the community structure of endophytic bacteria and bacteria in rhizosphere and non-rhizosphere using Illumina high-throughput sequencing technique. Bacteria in 52 phyla, 64 classes, 152 orders, 295 families, and 794 genera were identified, which mainly belonged to Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Fusobacteria, and Nitrospirota. At each taxonomic level, the community structure of the rhizosphere bacteria varied slightly with mangrove species, but endophytic bacteria differed greatly with plant species. The diversity indices of endophytic bacteria in branch and leaf samples of Acanthus ilicifolius were significantly lower, and endophytic bacteria in the plant tissues had higher abundance in the replication/repair and translation Clusters of Orthologous Genes functional categories but lower abundance in the carbohydrate metabolism category. This study helps to understand the community structure and diversity characteristics of endophytic and rhizosphere bacteria in different mangrove plants. Provide a theoretical basis for in-depth research on the functions of mangrove ecosystems.

A combination of machine-learning and eDNA reveals the genetic signature of environmental change at the landscape levels

The current advances of environmental DNA (eDNA) bring profound changes to ecological monitoring and provide unique insights on the biological diversity of ecosystems. The very nature of eDNA data is challenging yet also revolutionizing how biological monitoring information is analysed. In particular, new metrics and approaches should take full advantage of the extent and detail of molecular data produced by genetic methods. In this perspective, machine learning algorithms are particularly promising as they can capture complex relationships between the multiple environmental pressures and the diversity of biological communities. We investigated the potential of a new generation of biomonitoring tools that implement machine-learning techniques to fully exploit eDNA datasets. We trained a machine learning model to discriminate between reference and impacted communities of freshwater macroinvertebrates and assessed its performances using a large eDNA dataset collected at 64 standard federal monitoring sites across Switzerland. We show that a model trained on eDNA is significantly better than a naive model and performs similarly to a model trained on traditional data. Our proof-of-concept shows that such a combination of eDNA and machine learning approaches has the potential to complement or even replace traditional environmental monitoring, and could be scaled along temporal or spatial dimensions.

The Roles of Microbes in Stream Restorations

The goods and services provided by riverine systems are critical to humanity, and our reliance increases with our growing population and demands. As our activities expand, these systems continue to degrade throughout the world even as we try to restore them, and many efforts have not met expectations. One way to increase restoration effectiveness could be to explicitly design restorations to promote microbial communities, which are responsible for much of the organic matter breakdown, nutrient removal or transformation, pollutant removal, and biomass production in river ecosystems. In this paper, we discuss several design concepts that purposefully create conditions for these various microbial goods and services, and allow microbes to act as ecological restoration engineers. Focusing on microbial diversity and function could improve restoration effectiveness and overall ecosystem resilience to the stressors that caused the need for the restoration. Advances in next-generation sequencing now allow the use of microbial 'omics techniques (e.g., metagenomics, metatranscriptomics) to assess stream ecological conditions in similar fashion to fish and benthic macroinvertebrates. Using representative microbial communities from stream sediments, biofilms, and the water column may greatly advance assessment capabilities. Microbes can assess restorations and ecosystem function where animals may not currently be present, and thus may serve as diagnostics for the suitability of animal reintroductions. Emerging applications such as ecological metatranscriptomics may further advance our understanding of the roles of specific restoration designs towards ecological services as well as assess restoration effectiveness.

Meta-analysis of three-stressor combinations on population-level fitness reveal substantial higher-order interactions

Although natural populations are typically subjected to multiple stressors, most past research has focused on single-stressor and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 142 ecological three-stressor interactions on species' populations from 38 published papers; the vast majority of these studies were from the past 10 years. We found that 95.8 % (n = 136) of the three-stressor combinations had either not been categorized before or resulted in different interactions than previously reported. We also found substantial levels of emergent properties-interactions that are not due to strong pairwise interactions within the combination but rather uniquely due to all three stressors being combined. Calculating net interactions-the overall accounting for all possible interactions within a combination including the emergent and all pairwise interactions-we found that the most prevalent interaction type is antagonism, corresponding to a smaller than expected effect based on single stressor effects. In contrast, for emergent interactions, the most prevalent interaction type is synergistic, resulting in a larger than expected effect based on single stressor effects. Additionally, we found that hidden suppressive interactions-where a pairwise interaction is suppressed by a third stressor-are found in the majority of combinations (74 %). Collectively, understanding multiple stressor interactions through applying an appropriate framework is crucial for answering fundamental questions in ecology and has implications for conservation biology and population management. Crucially, identifying emergent properties can reveal hidden suppressive interactions that could be particularly important for the ecological management of at-risk populations.

Denitrification dynamics in unsaturated soils with different porous structures and water saturation degrees: A focus on the shift in microbial community structures

Despite its environmental significance, little is known about denitrification in vadose zones owing to the complexity of such environments. Here, we investigated denitrification in unsaturated soils with different pore distributions. To this end, we performed batch-type denitrification experiments and analyzed microbial community shifts before and after possible reactions with nitrates to clarify the relevant denitrifying mechanism in the microcosms. For quantitative comparison, pore distribution in the test soil samples was characterized based on the uniformity coefficient (C_u) and water saturation degree (SD). Micro-CT analysis of the soil pore distribution confirmed that the proportion of bigger-sized pores increased with decreasing C_u. However, oxygen diffusion into the system was controlled by SD rather than C_u. Within a certain SD range (51-67%), the pore condition changed abruptly from an oxic to an anoxic state. Consequently, denitrification occurred even under unsaturated soil conditions when the SD increased beyond 51-67%. High throughput sequencing revealed that the same microbial species were potentially responsible for denitrification under both partially (SD 67%), and fully saturated (SD of 100%) conditions, implying that the mechanism of denitrification in a vadose zone, if it exists, might be possibly similar under varying conditions.

Temporal Patterns of Bacterial and Viral Communities during Algae Blooms of a Reservoir in Macau

Compositions of microbial communities associated with blooms of algae in a storage reservoir in Macau, China were investigated between 2013 and 2016. Algae were enumerated by visible light microscopy. Profiles of organisms in water were examined by 16S rRNA sequences and viral metagenomics, based on next generation sequencing. Results of 16S rRNA sequencing indicated that majority of the identified organisms were bacteria closely related to Proteobacteria, Cyanobacteria, Verrucomicrobia, Bacteroidetes, and Actinobacteria. Metagenomics sequences demonstrated that the dominant virus was Phycodnavirus, accounting for 70% of the total population. Patterns of relative numbers of bacteria in the microbial community and their temporal changes were determined through alpha diversity indices, principal coordinates analysis (PCoA), relative abundance, and visualized by Venn diagrams. Ways in which the bacterial and viral communities are influenced by various water-related variables were elucidated based on redundancy analysis (RDA). Relationships of the relative numbers of bacteria with trophic status in a reservoir used for drinking water in Macau, provided insight into associations of Phycodnavirus and Proteobacteria with changes in blooms of algae.

A Standard Scale to Measure Equine Keeper Status and the Effect of Metabolic Tendency on Gut Microbiome Structure

Simple Summary

Horses with different metabolic tendencies are anecdotally referred to as “easy” or “hard” keepers. Easy keepers tend to gain weight easily while hard keepers require extra feed to maintain condition. Both easy and hard keeper horses carry a managerial and financial burden which can be a dissuading factor for horse shoppers. This research uses energy intake/need and body condition to develop a standard Equine Keeper Status Scale (EKSS) for assigning keeper status. The microbiome compositions based on EKSS assignments are then compared to explore microbiome differences based on metabolic tendencies of each group. The EKSS can be used by owners to accurately assess their horses’ metabolic tendencies and make improved feeding decisions to meet their horses’ needs. Understanding microbiome differences between easy, medium and hard keeper horses points to potential microbial roles in these metabolic tendencies.

Abstract

Thriftiness in horses has been associated with more efficient nutrient harvesting in digestion, absorption and/or utilization, but the relative contribution of the gut microbiome to host metabolic tendency is not well understood. Recognizing the unreliability of owner reported assignment of keeper status, this research describes a novel tool for calculating whether a horse is an easy (EK) or hard (HK) keeper and then characterizes microbiome differences in these groups. The Equine Keeper Status Scale (EKSS) was developed and validated based on data gathered from 240 horses. Estimates of dietary energy intakes and requirements to achieve the optimal BCS score of 5 were used in EKSS assignments. Sixty percent of owners’ characterizations disagreed with EKSS identified keeper assignments. Equine fecal 16S rRNA profiles (n = 73) revealed differences in α and β diversities and taxa abundances based on EKSS assignments. EK communities had more Planctomycetes and fewer Euryarcheaota, Spirochaetes and Proteobacteria than HK indicating functional differences in nutrient harvesting between groups. Differences in the gut microbiomes of horses based on keeper assignment point to host/microbial interactions that may underlie some differences in metabolic tendency. The EKSS enables robust, repeatable determination of keeper status which can be used by researchers and horse owners.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Expanding ecological assessment by integrating microorganisms into routine freshwater biomonitoring

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.

Two different approaches of microbial community structure characterization in riverine epilithic biofilms under multiple stressors conditions: Developing molecular indicators

Microbial communities are major players in the biogeochemical processes and ecosystem functioning of river networks. Despite their importance in the ecosystem, biomonitoring tools relying on prokaryotes are still lacking. Only a few studies have employed both metabarcoding and quantitative techniques such as catalysed reported deposition fluorescence in situ hybridization (CARD-FISH) to analyse prokaryotic communities of epilithic biofilms in river ecosystems. We intended to investigate the efficacy of both techniques in detecting changes in microbial community structure associated with environmental drivers. We report a significant correlation between the prokaryotic community composition and pH in rivers from two different geographical areas in Norway. Both CARD-FISH and metabarcoding data were following the pattern of the environmental variables, but the main feature distinguishing the community composition was the regional difference itself. Beta-dispersion analyses on both CARD-FISH abundance and metabarcoding data revealed higher accuracy of metabarcoding to differentiate regions and river systems. The CARD-FISH results showed high variability, even for samples within the same river, probably due to some unmeasured microscale ecological variability which we could not resolve. We also present a statistical method, which uses variation coefficient and overall prevalence of taxonomic groups, to detect possible biological indicators among prokaryotes using metabarcoding data. The development of new prokaryotic bioindicators would benefit from both techniques used in this study, but metabarcoding seems to be faster and more reliable than CARD-FISH for large scale bio-assessment.

Impacts of multiple anthropogenic stressors on stream macroinvertebrate community composition and functional diversity

Ensuring the provision of essential ecosystem services in systems affected by multiple stressors is a key challenge for theoretical and applied ecology. Trait-based approaches have increasingly been used in multiple-stressor research in freshwaters because they potentially provide a powerful method to explore the mechanisms underlying changes in populations and communities. Individual benthic macroinvertebrate traits associated with mobility, life history, morphology, and feeding habits are often used to determine how environmental drivers structure stream communities. However, to date multiple-stressor research on stream invertebrates has focused more on taxonomic than on functional metrics. We conducted a fully crossed, 4-factor experiment in 64 stream mesocosms fed by a pristine montane stream (21 days of colonization, 21 days of manipulations) and investigated the effects of nutrient enrichment, flow velocity reduction and sedimentation on invertebrate community, taxon, functional diversity and trait variables after 2 and 3 weeks of stressor exposure. 89% of the community structure metrics, 59% of the common taxa, 50% of functional diversity metrics, and 79% of functional traits responded to at least one stressor each. Deposited fine sediment and flow velocity reduction had the strongest impacts, affecting invertebrate abundances and diversity, and their effects translated into a reduction of functional redundancy. Stressor effects often varied between sampling occasions, further complicating the prediction of multiple-stressor effects on communities. Overall, our study suggests that future research combining community, trait, and functional diversity assessments can improve our understanding of multiple-stressor effects and their interactions in running waters.

Diversity of the microbial community and antioxidant activity during fermentation of red raspberry Enzymes

The diversity and succession of microbial community and antioxidant activity present during the preparation of red raspberry Enzymes with and without starter cultures were investigated by high-throughput sequencing of 16S rRNA and ITS1 genes and correlation analysis of the microbial diversity and antioxidant activity. The results showed that the sample inoculated with mixed fermentation had higher antioxidant activity than the sample without inoculated fermentation. The antioxidant capacity of red raspberry Enzymes increased significantly as the fermentation time increased. Firmicutes and Ascomycota were the predominant phyla of bacteria and fungi in all samples. At the genus level, Rhodococcus and Lactobacillus were the predominating bacteria throughout the fermentation process. The genus Kodamaea dominated the fungal community of early-fermentation samples with microbial inoculated fermentation. Candida spp. grew rapidly in the late stage of fermentation in the samples with spontaneous fermentation. Unweighted pair-group and PCA analysis revealed that the microbiota structures differed between the two groups. RDA and CCA showed that Rhodococcus and Kodamaea had positive effects on the DPPH scavenging ability and other antioxidant indicators, and the total phenol content had a significant and positive correlation coefficient with Gluconobacter. The results indicated that the fermentation by microorganisms significantly improves the oxidation resistance and helps to improve the quality of the red raspberry Enzymes.

Fine sediment and flow velocity impact bacterial community and functional profile more than nutrient enrichment

Freshwater ecosystems face many simultaneous pressures due to human activities. Consequently, there has been a rapid loss of freshwater biodiversity and an increase in biomonitoring programs. Our study assessed the potential of benthic stream bacterial communities as indicators of multiple-stressor impacts associated with urbanization and agricultural intensification. We conducted a fully crossed four-factor experiment in 64 flow-through mesocosms fed by a pristine montane stream (21 d of colonization, 21 d of manipulations) and investigated the effects of nutrient enrichment, flow-velocity reduction and added fine sediment after 2 and 3 weeks of stressor exposure. We used high-throughput sequencing and metabarcoding techniques (16S rRNA genes), as well as curated biological databases (METAGENassit, MetaCyc), to identify changes in bacterial relative abundances and predicted metabolic functional profile. Sediment addition and flow-velocity reduction were the most pervasive stressors. They both increased α-diversity and had strong taxon-specific effects on community composition and predicted functions. Sediment and flow velocity also interacted frequently, with 88% of all bacterial response variables showing two-way interactions and 33% showing three-way interactions including nutrient enrichment. Changes in relative abundances of common taxa were associated with shifts in dominant predicted functions, which can be extrapolated to underlaying stream-wide mechanisms such as carbon use and bacterial energy production pathways. Observed changes were largely stable over time and occurred after just 2 weeks of exposure, demonstrating that bacterial communities can be well-suited for early detection of multiple stressors. Overall, added sediment and reduced flow velocity impacted both bacterial community structure and predicted function more than nutrient enrichment. In future research and stream management, a holistic approach to studying multiple-stressor impacts should include multiple trophic levels with their functional responses, to enhance our mechanistic understanding of complex stressor effects and promote establishment of more efficient biomonitoring programs.

Disturbance history can increase functional stability in the face of both repeated disturbances of the same type and novel disturbances

Climate change is expected to increase the incidences of extremes in environmental conditions. To investigate how repeated disturbances affect microbial ecosystem resistance, natural lake bacterioplankton communities were subjected to repeated temperature disturbances of two intensities (25 °C and 35 °C), and subsequently to an acidification event. We measured functional parameters (bacterial production, abundance, extracellular enzyme activities) and community composition parameters (richness, evenness, niche width) and found that, compared to undisturbed control communities, the 35 °C treatment was strongly affected in all parameters, while the 25 °C treatment did not significantly differ from the control. Interestingly, exposure to multiple temperature disturbances caused gradually increasing stability in the 35 °C treatment in some parameters, while others parameters showed the opposite, indicating that the choice of parameters can strongly affect the outcome of a study. The acidification event did not lead to stronger changes in community structure, but functional resistance of bacterial production towards acidification in the 35 °C treatments increased. This indicates that functional resistance in response to a novel disturbance can be increased by previous exposure to another disturbance, suggesting similarity in stress tolerance mechanisms for both disturbances. These results highlight the need for understanding function- and disturbance-specific responses, since general responses are likely to be unpredictable.

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems. However, traditional reliance on morphological identification generally makes it cost-prohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Multiple Stressors Determine Community Structure and Estimated Function of River Biofilm Bacteria

Freshwater ecosystems are exposed to multiple stressors, but their individual and combined effects remain largely unexplored. Here, we investigated the response of stream biofilm bacterial communities to warming, hydrological stress, and pesticide exposure. We used 24 artificial streams on which epilithic (growing on coarse sediments) and epipsammic (growing on fine sediments) stream biofilms were maintained. Bacterial community composition and estimated function of biofilms exposed during 30 days to individual and combined stressors were assessed using 16S rRNA gene metabarcoding. Among the individual effects by stressors, hydrological stress (i.e., a simulated low-flow situation) was the most relevant, since it significantly altered 57% of the most abundant bacterial taxa (n = 28), followed by warming (21%) and pesticide exposure (11%). Regarding the combined effects, 16% of all stressor combinations resulted in significant interactions on bacterial community composition and estimated function. Antagonistic responses prevailed (57 to 89% of all significant interactions), followed by synergisms (11 to 43%), on specific bacterial taxa, indicating that multiple-stressor scenarios could lead to unexpected shifts in the community composition and associated functions of riverine bacterial communities.IMPORTANCE Freshwater ecosystems such as rivers are of crucial importance for human well-being. However, human activities result in many stressors (e.g., toxic chemicals, increased water temperatures, and hydrological alterations) cooccurring in rivers and streams worldwide. Among the many organisms inhabiting rivers and streams, bacteria are ecologically crucial; they are placed at the base of virtually all food webs and they recycle the organic matter needed for bigger organisms. Most of these bacteria are in close contact with river substratum, where they form the biofilms. There is an urgent need to evaluate the effects of these stressors on river biofilms, so we can anticipate future environmental problems. In this study, we experimentally exposed river biofilms to a pesticide mixture, an increase in water temperature and a simulated low-flow condition, in order to evaluate the individual and joint effects of these stressors on the bacterial community composition and estimated function.

Interactions between dicyandiamide and periphytic biofilms in paddy soils and subsequent effects on nitrogen cycling

Dicyandiamide (DCD) is commonly used as nitrification inhibitors which has the potential to reduce nitrogen loss from paddy soils. In paddy systems, periphytic biofilms are commonly presented at the soil/water interface and show significant effects on nutrient cycling. However, the interaction between DCD and periphytic biofilms in paddy and subsequent effects on nitrogen cycling is unclear. In this work, microcosm experiments were carried out to study the interaction between the periphytic biofilms and DCD and the potential influence on nitrogen cycling from in paddy. Results showed that DCD affected the development of periphytic biofilms, while the presence of periphytic biofilms accelerated DCD degradation. Results also showed DCD application reduced nitrification potential mainly by inhibiting ammonia-oxidizing bacteria (AOB). Higher DCD dosage increased NH₃ volatilization loss. However, presence of periphytic biofilm reduced the NH₃ volatilization loss but increased denitrification. Our work contributes to a better understanding on the nitrogen cycling processes in paddy, and provides useful information for the improvement of nitrogen utilization efficiency and the control of non-point source pollution.

Anthropogenic stressors affect fungal more than bacterial communities in decaying leaf litter: A stream mesocosm experiment

Despite the progress made in environmental microbiology techniques and knowledge, the succession and functional changes of the microbial community under multiple stressors are still poorly understood. This is a substantial knowledge gap as microbial communities regulate the biogeochemistry of stream ecosystems. Our study assessed the structural and temporal changes in stream fungal and bacterial communities associated with decomposing leaf litter under a multiple-stressor scenario. We conducted a fully crossed 4-factor experiment in 64 flow-through mesocosms fed by a pristine montane stream (21 days of colonisation, 21 days of manipulations) and investigated the effects of nutrient enrichment, flow velocity reduction and sedimentation after 2 and 3 weeks of stressor exposure. We used high-throughput sequencing and metabarcoding techniques (16S and 18S rRNA genes) to identify changes in microbial community composition. Our results indicate that (1) shifts in relative abundances of the pre-existing terrestrial microbial community, rather than changes in community identity, drove the observed responses to stressors; (2) changes in relative abundances within the microbial community paralleled decomposition rate patterns with time; (3) both fungal and bacterial communities had a certain resistance to stressors, as indicated by relatively minor changes in alpha diversity or multivariate community structure; (4) overall, stressor interactions were more common than stressor main effects when affecting microbial diversity metrics or abundant individual genera; and (5) stressor effects on microbes often changed from 2 weeks to 3 weeks of stressor exposure, with several response patterns being reversed. Our study suggests that future research should focus more on understanding the temporal dynamics of fungal and bacterial communities and how they relate to ecosystem processes to advance our understanding of the mechanisms associated with multiple-stressor interactions.

Towards a unified study of multiple stressors: divisions and common goals across research disciplines

Anthropogenic environmental changes, or 'stressors', increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

The spatial variations of correlation between microbial diversity and groundwater quality derived from a riverbank filtration site, northeast China

To identify the relationship between microbial communities and groundwater quality parameters, especially typical groundwater contaminants including ammonium (NH₄⁺), iron (Fe²⁺), and manganese (Mn²⁺), groundwater samples and aquifer media were collected from a riverbank filtration (RBF) site in Harbin city, northeast China. The structures of the microbial communities of aquifer media at different depths were illustrated through 16S rRNA sequencing using the Illumina MiSeq platform, and the correlation between microbial communities and water quality parameters was quantitatively demonstrated by redundancy analysis (RDA). The results revealed that the diversity of microbial communities decreased along the groundwater flow path at the south bank of Songhua river. The richness and diversity in the unsaturated zone (0-5 m) were significantly higher than those in the saturated zone (5-50 m) because of physiochemical properties of aquifer media and the redox environment in the RBF system. Core taxa, which were significantly related to the biotransformation behavior of iron, manganese, and ammonium, were Pseudomonas, Acinetobacter, Ochrobactrum, Sphingobium, and Sphingomonas. RDA results indicated that the critical physiochemical parameters that significantly influenced the composition of microbial communities were different in the saturated and unsaturated zones, and the total organic carbon (TOC), electrical conductivity (EC), nitrate (NO₃^-), and manganese (Mn²⁺) levels were the four principal factors affecting the function and composition of microbial communities in the whole RBF system. Proteobacteria, Sphingomonadales, and Sphingobium were the dominant bacteria at the phylum, order, and genus levels with 39.8%, 59.2%, and 65.3% contribution to the overall groundwater quality, respectively. The results obtained from this study should improve the understanding of the relationship between the structure of microbial communities (especially, bacteria related to the biotransformation of NH₄⁺, Fe²⁺, and Mn²⁺) and physiochemical parameters.

Multiple-stressor effects of dicyandiamide (DCD) and agricultural stressors on trait-based responses of stream benthic algal communities

Agricultural practices often result in multiple stressors affecting stream ecosystems, and interacting stressors complicate environmental assessment and management of impacted streams. The nitrification inhibitor dicyandiamide (DCD) is used for nitrogen management on farmland. Effects of leached DCD on stream ecosystems are still largely unstudied, even though it could be relevant as a stressor on its own or in combination with other agricultural stressors. We conducted two experiments in 128 outdoor stream-fed mesocosms to assess stressor effects on biomass, cell density, taxon richness, evenness and functional trait composition of benthic algal communities. First, we examined responses to a wide DCD gradient (eight concentrations, 0-31 mg L^-1) and two additional stressors, deposited fine sediment (none, high) and nutrient enrichment (ambient, enriched). Second, we determined algal responses to four stressors: DCD, sediment, nutrients, and reduced flow velocity. Here DCD treatments included controls, constant application (1.4 mg L^-1) and two pulsed treatments mimicking concentration patterns in real streams (peaks 3.5 mg L^-1, 2.2 mg L^-1). Sediment and nutrient enrichment were influential stressors in both experiments, with fine sediment having the most pervasive effects. In Experiment 2, reduced flow velocity had pervasive effects and stressor interactions were mainly restricted to two-way interactions. DCD had few, weak stressor main effects, especially at field-realistic concentrations (Experiment 2). At the highest concentrations in Experiment 1 (above levels observed in real streams), DCD effects were still rare but some significant stressor interactions occurred. Analyses of functional traits were helpful in identifying potential mechanisms driving changes in densities and community composition. These findings suggest that, while DCD on its own may be a minor stressor, it could have adverse effects on algal communities already exposed to other stressors, a scenario common in agricultural streams.

Effects of multiple stressors on river biofilms depend on the time scale

Global change exposes ecosystems to a myriad of stressors differing in their spatial (i.e. surface of stressed area) and temporal (i.e. exposure time) components. Among freshwater ecosystems, rivers and streams are subject to physical, chemical and biological stressors, which interact with each other and might produce diverging effects depending on exposure time. We conducted a manipulative experiment using 24 artificial streams to examine the individual and combined effects of warming (1.6 °C increase in water temperature), hydrological stress (simulated low-flow situation) and chemical stress caused by pesticide exposure (15.1-156.7 ng L-1) on river biofilms. We examined whether co-occurring stressors could lead to non-additive effects, and if these differed at two different exposure times. Specifically, structural and functional biofilm responses were assessed after 48 hours (short-term effects) and after 30 days (long-term effects) of exposure. Hydrological stress caused strong negative impacts on river biofilms, whereas effects of warming and pesticide exposure were less intense, although increasing on the long term. Most stressor combinations (71%) resulted in non-significant interactions, suggesting overall additive effects, but some non-additive interactions also occurred. Among non-additive interactions, 59% were classified as antagonisms after short-term exposure to the different stressor combinations, rising to 86% at long term. Our results indicate that a 30-day exposure period to multiple stressors increases the frequency of antagonistic interactions compared to a 48-hour exposure to the same conditions. Overall, the impacts of multiple-stressor occurrences appear to be hardly predictable from individual effects, highlighting the need to consider temporal components such as duration when predicting the effects of multiple stressors.

Desiccation events change the microbial response to gradients of wastewater effluent pollution

While wastewater treatment plant (WWTP) effluents have become increasingly recognized as a stressor for receiving rivers, their effects on river microbial communities remain elusive. Moreover, global change is increasing the frequency and duration of desiccation events in river networks, and we ignore how desiccation might influence the response of microbial communities to WWTP effluents. In this study, we evaluated the interaction between desiccation events and WWTP effluents under different dilution capacities. Specifically, we used artificial streams in a replicated regressional design, exposing first a section of the streams to a 7-day desiccation period and then the full stream to different levels of a realistic WWTP effluent dilution, from 0% to 100% of WWTP effluent proportion of the total stream flow. The microbial community response was assessed by means of high-throughput sequencing of 16S rRNA gene amplicons and quantitative PCR targeting ecologically-relevant microbial groups. Threshold Indicator Taxa Analysis (TITAN) was used, together with model fitting, to determine community thresholds and potential indicator taxa. Results show significant interactions between WWTP effluents and desiccation, particularly when sediment type is considered. Indicator taxa included members of Proteobacteria, Actinobacteria and Cyanobacteria, with abrupt changes in community structure at WWTP effluent proportion of the total flow above 50%, which is related to nutrient levels ranging 4.6-5.2 mg N-NO₃^-L^-1, 0.21-0.32 mg P-PO₄^3-L^-1 and 7.09-9.00 mg DOC L^-1. Our work indicates that situations where WWTP effluents account for >50% of the total river flow might risk of dramatic microbial community structure changes and should be avoided.

Groundwater contamination and land drainage induce divergent responses in boreal spring ecosystems

Degradation of freshwater ecosystems has engendered legislative mandates for the protection and management of surface waters while groundwater-dependent ecosystems (GDEs) have received much less attention. This is so despite biodiversity and functioning of GDEs are currently threatened by several anthropogenic stressors, particularly intensified land use and groundwater contamination. We assessed the impacts of land drainage (increased input of dissolved organic carbon, DOC, from peatland drainage) and impaired groundwater chemical quality (NO₃^--N enrichment from agricultural or urban land use) on biodiversity and ecosystem functioning in 20 southern Finnish cold-water springs using several taxonomic and functional measures. Groundwater contamination decreased macroinvertebrate and bacterial diversity and altered their community composition. Changes in macroinvertebrate and bacterial communities along the gradient of water-quality impairment were caused by the replacement of native with new taxa rather than by mere disappearance of some of the original taxa. Also species richness of habitat specialist (but not headwater generalist) bryophytes decreased due to impaired groundwater quality. Periphyton accrual rate showed a subsidy-stress response to elevated nitrate concentrations, with peak values at around 2500 μg L^-1, while drainage-induced spring water brownification (increased DOC) reduced both periphyton accrual and leaf decomposition rates already at very low concentrations. Our results highlight the underutilized potential of ecosystem-level functional measures in GDE bioassessment as they seem to respond to the first signs of spring ecosystem impairment, at least for the anthropogenic stressors studied by us.

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.

Responses of stream microbes to multiple anthropogenic stressors in a mesocosm study

Stream ecosystems are affected by multiple anthropogenic stressors worldwide. Even though effects of many single stressors are comparatively well studied, the effects of multiple stressors are difficult to predict. In particular bacteria and protists, which are responsible for the majority of ecosystem respiration and element flows, are infrequently studied with respect to multiple stressors responses. We conducted a stream mesocosm experiment to characterize the responses of single and multiple stressors on microbiota. Two functionally important stream habitats, leaf litter and benthic phototrophic rock biofilms, were exposed to three stressors in a full factorial design: fine sediment deposition, increased chloride concentration (salinization) and reduced flow velocity. We analyzed the microbial composition in the two habitat types of the mesocosms using an amplicon sequencing approach. Community analysis on different taxonomic levels as well as principle component analyses (PCoAs) based on realtive abundances of operational taxonomic units (OTUs) showed treatment specific shifts in the eukaryotic biofilm community. Analysis of variance (ANOVA) revealed that Bacillariophyta responded positively salinity and sediment increase, while the relative read abundance of chlorophyte taxa decreased. The combined effects of multiple stressors were mainly antagonistic. Therefore, the community composition in multiply stressed environments resembled the composition of the unstressed control community in terms of OTU occurrence and relative abundances.

Repeated disturbances affect functional but not compositional resistance and resilience in an aquatic bacterioplankton community

Disturbances are believed to be one of the main factors influencing variations in community diversity and functioning. Here we investigated if exposure to a pH press disturbance affected the composition and functional performance of a bacterial community and its resistance, recovery and resilience to a second press disturbance (salt addition). Lake bacterial assemblages were initially exposed to reduced pH in six mesocosms whereas another six mesocosms were kept as reference. Seven days after the pH disturbance, three tanks from each treatment were exposed to a salt disturbance. Both bacterial production and enzyme activity were negatively affected by the salt treatment, regardless if the communities had been subject to a previous disturbance or not. However, cell-specific enzyme activity had a higher resistance in communities pre-exposed to the pH disturbance compared to the reference treatment. In contrast, for cell-specific bacterial production resistance was not affected, but recovery was faster in the communities that had previously been exposed to the pH disturbance. Over time, bacterial community composition diverged among treatments, in response to both pH and salinity. The difference in functional recovery, resilience and resistance may depend on differences in community composition caused by the pH disturbance, niche breadth or acquired stress resistance.

Ecological patterns and adaptability of bacterial communities in alkaline copper mine drainage

Environmental gradient have strong effects on community assembly processes. In order to reveal the effects of alkaline mine drainage (AlkMD) on bacterial and denitrifying bacterial community compositions and diversity in tailings reservoir, here we conducted an experiment to examine all and core bacterial taxa and denitrifying functional genes's (nirS, nirK, nosZ_Ι) abundance along a chemical gradient in tailings water in Shibahe copper tailings in Zhongtiaoshan, China. Differences in bacterial and denitrifying bacterial community compositions in different habitats and their relationships with environmental parameters were analyzed. The results showed that the richness and diversity of bacterial community in downstream seeping water (SDSW) were the largest, while that in upstream tailings water (STW1) were the lowest. The diversity and abundance of bacterial communities tended to increase from STW1 to SDSW. The variation of bacterial community diversity was significantly related to electroconductibility (EC), nitrate (NO₃^-), nitrite (NO₂^-), total carbon (TC), inorganic carbon (IC) and sulfate (SO₄^2-), but was not correlated with geographic distance in local scale. Core taxa from class to genus were all significantly related to NO₃^- and NO₂^-. Core taxa Rhodobacteraceae, Rhodobacter, Acinetobacter and Hydrogenophaga were typical denitrifying bacteria. The variation trends of these groups were consistent with the copy number of nirS, nirK and nosZ_Ι, demonstrating their importance in the process of nitrogen reduction. The copy number of nirK, nosZ_Ι and nirS/16S rDNA, nirK/16Sr DNA correlated strongly with NO₃^-, NO₂^- and IC, but nirS and nosZ_I/16SrDNA had no significant correlation with NO₃^- and NO₂^-. The copy numbers of denitrifying functional genes (nirS, nirK and nosZ_Ι) were negatively correlated with heavy metal plumbum (Pb) and zinc (Zn). It showed that heavy metal contamination was an important factor affecting the structure of denitrifying bacterial community in AlkMD. In this study we have identified the distribution pattern of bacterial community along physiochemical gradients in alkaline tailings reservoir and displayed the driving force of shaping the structure of bacterial community. The influence of NO₃^-, NO₂^-, IC and heavy metal Pb and Zn on bacterial community might via their influence on the functional groups involving nitrogen, carbon and metal metabolisms.