The Role of Land Use Types and Water Chemical Properties in Structuring the Microbiomes of a Connected Lake System

The role of agricultural drainage, storm-events, and natural filtration on the biogeochemical cycling capacity of aquatic and sediment environments in Lake Erie's drainage basin

Lake Erie is the most at risk of the Great Lakes for degraded water quality due to non-point source pollution caused by agricultural activities in the lake's watershed. The extent and temporal patterns of nutrient loading from these agricultural activities is influenced by the timing of agronomic events, precipitation events, and water flow through areas of natural filtration within the watershed. Downstream impacts of these nutrient loading events may be moderated by the co-loading of functionally relevant biogeochemical cycling microbial communities from agricultural soils. This study quantified loading patterns of these communities from tile drain sources, assessed whether functional communities from agricultural sources influenced downstream microbial functionality, and investigated how distance from agricultural sources, storm events, and areas of natural filtration altered nutrient cycling and nutrient fluxes in aquatic and sediment environments. Water and sediment samples were collected in the Wigle Creek watershed in Ontario, from tile drains through to Lake Erie, from May to November 2021, and microbial nitrogen (N) and phosphorous (P) cycling capacity (quantitative PCR), and nutrient levels were evaluated. Results showed that N and P functional groups were co-loaded with nutrients, with increased loading occurring during storm events and during agricultural activities including fertilization and harvest. Overall functional capacity in the aquatic environment decreased with distance from the agricultural sources and as water transited through natural filtration areas. In contrast, the sediment environment was more resilient to both agricultural disturbances and abiotic factors. This study expands our understanding of when and where different stages of N and P cycling occurs in agriculturally impacted watersheds, and identifies both seasons and regions to target with nutrient mitigation strategies.

A genome catalogue of lake bacterial diversity and its drivers at continental scale

Lakes are heterogeneous ecosystems inhabited by a rich microbiome whose genomic diversity is poorly defined. We present a continental-scale study of metagenomes representing 6.5 million km2 of the most lake-rich landscape on Earth. Analysis of 308 Canadian lakes resulted in a metagenome-assembled genome (MAG) catalogue of 1,008 mostly novel bacterial genomospecies. Lake trophic state was a leading driver of taxonomic and functional diversity among MAG assemblages, reflecting the responses of communities profiled by 16S rRNA amplicons and gene-centric metagenomics. Coupling the MAG catalogue with watershed geomatics revealed terrestrial influences of soils and land use on assemblages. Agriculture and human population density were drivers of turnover, indicating detectable anthropogenic imprints on lake bacteria at the continental scale. The sensitivity of bacterial assemblages to human impact reinforces lakes as sentinels of environmental change. Overall, the LakePulse MAG catalogue greatly expands the freshwater genomic landscape, advancing an integrative view of diversity across Earth's microbiomes.

Unraveling the effect of land use on the bacterioplankton community composition from highly impacted shallow lakes at a regional scale

Bacterioplankton communities play a crucial role in global biogeochemical processes and are highly sensitive to changes induced by natural and anthropogenic stressors in aquatic ecosystems. We assessed the influence of Land Use Land Cover (LULC), environmental, and geographic changes on the bacterioplankton structure in highly connected and impacted shallow lakes within the Salado River basin, Buenos Aires, Argentina. Additionally, we investigated how changes in LULC affected the limnological characteristics of these lakes at a regional scale. Our analysis revealed that the lakes were ordinated by sub-basins (upper and lower) depending on their LULC characteristics and limnological properties. In coincidence, the same ordination was observed when considering the Bacterioplankton Community Composition (BCC). Spatial and environmental predictors significantly explained the variation in BCC, although when combined with LULC the effect was also important. While the pure LULC effect did not explain a significant percentage of BCC variation, the presence of atrazine in water, an anthropogenic variable linked to LULC, directly influenced both the BCC and some Amplicon Sequence Variants (ASVs) in particular. Our regional-scale approach contributes to understanding the complexity of factors driving bacterioplankton structure and how LULC pervasively affect these communities in highly impacted shallow lake ecosystems from the understudied Southern Hemisphere.

Human impact on current environmental state in Chinese lakes

Anthropogenic and natural disturbance to inland aquatic ecosystems displays a notable spatial difference, yet data to measure these differences are scarce. This study encompasses 217 lakes distributed over five lake regions of China and elucidates the environmental factors determining the spatial variability of the water quality and trophic status. A significant correlation between human modification index in surrounding terrestrial systems (HMT) and trophic status of lake ecosystems (TSI) was found, and the regression slope in each region was similar except in the Qinghai-Tibet Plateau region. It was further noted that the pattern of environmental factor network (EF network) differed among freshwater and saline lakes. The EF network was complex for freshwater lakes in less human-influenced areas, but intensive man-made influence disrupted most relationships except for those between total nitrogen, total phosphorus, chlorophyll-a, and water turbidity. As for regions including saline lakes, correlations among water salinity and organic forms of carbon and nitrogen were apparent. Our results suggest that HMT and EF network can be useful indicators of the ecological integrity of local lake ecosystems, and integrating spatial information on a large scale provides conservation planners the option for evaluating the potential risk on inland aquatic systems.

Core and conditionally rare taxa as indicators of agricultural drainage ditch and stream health and function

BACKGROUND

The freshwater microbiome regulates aquatic ecological functionality, nutrient cycling, pathogenicity, and has the capacity to dissipate and regulate pollutants. Agricultural drainage ditches are ubiquitous in regions where field drainage is necessary for crop productivity, and as such, are first-line receptors of agricultural drainage and runoff. How bacterial communities in these systems respond to environmental and anthropogenic stressors are not well understood. In this study, we carried out a three year study in an agriculturally dominated river basin in eastern Ontario, Canada to explore the spatial and temporal dynamics of the core and conditionally rare taxa (CRT) of the instream bacterial communities using a 16S rRNA gene amplicon sequencing approach. Water samples were collected from nine stream and drainage ditch sites that represented the influence of a range of upstream land uses.

RESULTS

The cross-site core and CRT accounted for 5.6% of the total number of amplicon sequence variants (ASVs), yet represented, on average, over 60% of the heterogeneity of the overall bacterial community; hence, well reflected the spatial and temporal microbial dynamics in the water courses. The contribution of core microbiome to the overall community heterogeneity represented the community stability across all sampling sites. CRT was primarily composed of functional taxa involved in nitrogen (N) cycling and was linked to nutrient loading, water levels, and flow, particularly in the smaller agricultural drainage ditches. Both the core and the CRT were sensitive responders to changes in hydrological conditions.

CONCLUSIONS

We demonstrate that core and CRT can be considered as holistic tools to explore the temporal and spatial variations of the aquatic microbial community and can be used as sensitive indicators of the health and function of agriculturally dominated water courses. This approach also reduces computational complexity in relation to analyzing the entire microbial community for such purposes.

Geospatial analysis reveals a hotspot of fecal bacteria in Canadian prairie lakes linked to agricultural non-point sources

Lakes are sentinels of environmental changes within their watersheds including those induced by a changing climate and anthropogenic activities. In particular, contamination originating from point or non-point sources (NPS) within watersheds might be reflected in changes in the bacterial composition of lake water. We assessed the abundance of potentially pathogenic bacteria (PPB) sampled in 413 lakes within 8 southern Canadian ecozones that represent a wide diversity of lakes and watershed land use. The study objectives were (1) to explore the diversity of PPB; (2) to build a fecal multi-indicator from a cluster of co-occurring PPB; and (3) to predict the fecal multi-indicator over thousands of lakes. We identified bacterial taxa based on 16S rRNA amplicon sequencing and clustered 33 PPB matching taxa in the Canadian ePATHogen database using a Sørensen dissimilarity index on binary data across the sampled lakes. One cluster contained Erysipelothrix, Desulfovibrio, Bacteroides, Vibrio and Acholeplasma and was related to the NPS fraction of agriculture and pasture within the watershed as its main driver and thus it was determined as the fecal multi-indicator. We subsequently developed a fecal multi-indicator predictive model across 200 212 southern Canadian lakes which explained 55.1% of the deviance. Mapping the predictions showed higher fecal multi-indicator abundances in the Prairies and Boreal Plains compared to the other ecozones. These results represent the first attempt to map a potential fecal multi-indicator at the continental scale, which may be further improved in the future. Lastly, the study demonstrates the capacity of a multi-disciplinary approach leveraging both datasets derived from remote sensing and DNA sequencing to provide mapping information for public health governmental policies.

Spatio-temporal connectivity of the aquatic microbiome associated with cyanobacterial blooms along a Great Lake riverine-lacustrine continuum

Lake Erie is subject to recurring events of cyanobacterial harmful algal blooms (cHABs), but measures of nutrients and total phytoplankton biomass seem to be poor predictors of cHABs when taken individually. A more integrated approach at the watershed scale may improve our understanding of the conditions that lead to bloom formation, such as assessing the physico-chemical and biological factors that influence the lake microbial community, as well as identifying the linkages between Lake Erie and the surrounding watershed. Within the scope of the Government of Canada's Genomics Research and Development Initiative (GRDI) Ecobiomics project, we used high-throughput sequencing of the 16S rRNA gene to characterize the spatio-temporal variability of the aquatic microbiome in the Thames River-Lake St. Clair-Detroit River-Lake Erie aquatic corridor. We found that the aquatic microbiome was structured along the flow path and influenced mainly by higher nutrient concentrations in the Thames River, and higher temperature and pH downstream in Lake St. Clair and Lake Erie. The same dominant bacterial phyla were detected along the water continuum, changing only in relative abundance. At finer taxonomical level, however, there was a clear shift in the cyanobacterial community, with Planktothrix dominating in the Thames River and Microcystis and Synechococcus in Lake St. Clair and Lake Erie. Mantel correlations highlighted the importance of geographic distance in shaping the microbial community structure. The fact that a high proportion of microbial sequences found in the Western Basin of Lake Erie were also identified in the Thames River, indicated a high degree of connectivity and dispersal within the system, where mass effect induced by passive transport play an important role in microbial community assembly. Nevertheless, some cyanobacterial amplicon sequence variants (ASVs) related to Microcystis, representing less than 0.1% of relative abundance in the upstream Thames River, became dominant in Lake St. Clair and Erie, suggesting selection of those ASVs based on the lake conditions. Their extremely low relative abundances in the Thames suggest additional sources are likely to contribute to the rapid development of summer and fall blooms in the Western Basin of Lake Erie. Collectively, these results, which can be applied to other watersheds, improve our understanding of the factors influencing aquatic microbial community assembly and provide new perspectives on how to better understand the occurrence of cHABs in Lake Erie and elsewhere.

Sources and migration similarly determine nitrate concentrations: Integrating isotopic, landscape, and biological approaches

Rapid land use change has significantly increased nitrate (NO₃^-) loading to rivers, leading to eutrophication, and posing water security problems. Determining the sources of NO₃^- to waters and the underlying influential factors is critical for effectively reducing pollution and better managing water resources. Here, we identified the sources and influencing mechanisms of NO₃^- in a mixed land-use watershed by integrating stable isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-), molecular biology, water chemistry, and landscape metrics measurements. Weak transformation processes of NO₃^- were identified in the river, as evinced by water chemistry, isotopes, species compositions, and predicted microbial genes related to nitrogen metabolism. NO₃^- concentrations were primarily influenced by exogenous inputs (i.e., from soil nitrogen (NS), nitrogen fertilizer (NF), and manure & sewage (MS)). The proportions of NO₃^- sources seasonally varied. In the wet season, the source contributions followed the order of NS (38.6 %) > NF (31.4 %) > atmospheric deposition (ND, 16.2 %) > MS (13.8 %). In the dry season, the contributions were in the order of MS (39.2 %) > NS (29.2 %) > NF (29 %) > ND (2.6 %). Farmland and construction land were the original factors influencing the spatial distribution of NO₃^- in the wet and dry seasons, respectively, while slope, basin relief (HD), hypsometric integral (HI), and COHESION, HD were the primary indicators associated with NO₃^- transport in the wet and dry seasons, respectively. Additionally, spatial scale differences were observed for the effects of landscape structure on NO₃^- concentrations, with the greatest effect at the 1000-m buffer zone scale in the wet season and at the sub-basin scale in the dry season. This study overcomes the limitation of isotopes in identifying nitrate sources by combining multiple approaches and provides new research perspectives for the determination of nitrate sources and migration in other watersheds.

Freshwater microbial metagenomes sampled across different water body characteristics, space and time in Israel

Freshwater bodies are critical components of terrestrial ecosystems. The microbial communities of freshwater ecosystems are intimately linked water quality. These microbes interact with, utilize and recycle inorganic elements and organic matter. Here, we present three metagenomic sequence datasets (total of 182.9 Gbp) from different freshwater environments in Israel. The first dataset is from diverse freshwater bodies intended for different usages - a nature reserve, irrigation and aquaculture facilities, a tertiary wastewater treatment plant and a desert rainfall reservoir. The second represents a two-year time-series, collected during 2013-2014 at roughly monthly intervals, from a water reservoir connected to an aquaculture facility. The third is from several time-points during the winter and spring of 2015 in Lake Kinneret, including a bloom of the cyanobacterium Microcystis sp. These datasets are accompanied by physical, chemical, and biological measurements at each sampling point. We expect that these metagenomes will facilitate a wide range of comparative studies that seek to illuminate new aspects of freshwater microbial ecosystems and inform future water quality management approaches.

Next-Generation High-Throughput Sequencing to Evaluate Bacterial Communities in Freshwater Ecosystem in Hydroelectric Reservoirs

The quality of aquatic ecosystems is a major public health concern. The assessment and management of a freshwater system and the ecological monitoring of microorganisms that are present in it can provide indicators of the environment and water quality to protect human and animal health. with bacteria is. It is a major challenge to monitor the microbiological bacterial contamination status of surface water associated with anthropogenic activities within rivers and freshwater reservoirs. Understanding the composition of aquatic microbial communities can be beneficial for the early detection of pathogens, improving our knowledge of their ecological niches, and characterizing the assemblages of microbiota responsible for the degradation of contaminants and microbial substrates. The present study aimed to characterize the bacterial microbiota of water samples collected alongside the Madeira River and its small tributaries in rural areas near the Santo Antonio Energia hydroelectric power plant (SAE) reservoir in the municipality of Porto Velho, Rondonia state, Western Brazil. An Illumina 16s rRNA metagenomic approach was employed and the physicochemical characteristics of the water sample were assessed. We hypothesized that both water metagenomics and physicochemical parameters would vary across sampling sites. The most abundant genera found in the study were Acinetobacter, Deinococcus, and Pseudomonas. PERMANOVA and ANCOM analysis revealed that collection points sampled at the G4 location presented a significantly different microbiome compared to any other group, with the Chlamidomonadaceae family and Enhydrobacter genus being significantly more abundant. Our findings support the use of metagenomics to assess water quality standards for the protection of human and animal health in this microgeographic region.

The relationship between land cover and microbial community composition in European lakes

Microbes are essential for element cycling and ecosystem functioning. However, many questions central to understanding the role of microbes in ecology are still open. Here, we analyze the relationship between lake microbiomes and the lakes' land cover. By applying machine learning methods, we quantify the covariance between land cover categories and the microbial community composition recorded in the largest amplicon sequencing dataset of European lakes available to date. Our results show that the aggregation of environmental features or microbial taxa before analysis can obscure ecologically relevant patterns. We observe a comparatively high covariation of the lakes' microbial community with herbaceous and open spaces surrounding the lake; nevertheless, the microbial covariation with land cover categories is generally lower than the covariation with physico-chemical parameters. Combining land cover and physico-chemical bioindicators identified from the same amplicon sequencing dataset, we develop analytical data structures that facilitate insights into the ecology of the lake microbiome. Among these, a list of the environmental parameters sorted by the number of microbial bioindicators we have identified for them points towards apparent environmental drivers of the lake microbial community composition, such as the altitude, conductivity, and area covered herbaceous vegetation surrounding the lake. Furthermore, the response map, a similarity matrix calculated from the Jaccard similarity of the environmental parameters' lists of bioindicators, allows us to study the ecosystem's structure from the standpoint of the microbiome. More specifically, we identify multiple clusters of highly similar and possibly functionally linked ecological parameters, including one that highlights the importance of the calcium-bicarbonate equilibrium for lake ecology. Taken together, we demonstrate the use of machine learning approaches in studying the interplay between microbial diversity and environmental factors and introduce novel approaches to integrate environmental molecular diversity into monitoring and water quality assessments.

Diversity and distribution of sediment bacteria across an ecological and trophic gradient

The microbial communities of lake sediments have the potential to serve as valuable bioindicators and integrators of watershed land-use and water quality; however, the relative sensitivity of these communities to physio-chemical and geographical parameters must be demonstrated at taxonomic resolutions that are feasible by current sequencing and bioinformatic approaches. The geologically diverse and lake-rich state of Minnesota (USA) is uniquely situated to address this potential because of its variability in ecological region, lake type, and watershed land-use. In this study, we selected twenty lakes with varying physio-chemical properties across four ecological regions of Minnesota. Our objectives were to (i) evaluate the diversity and composition of the bacterial community at the sediment-water interface and (ii) determine how lake location and watershed land-use impact aqueous chemistry and influence bacterial community structure. Our 16S rRNA amplicon data from lake sediment cores, at two depth intervals, data indicate that sediment communities are more likely to cluster by ecological region rather than any individual lake properties (e.g., trophic status, total phosphorous concentration, lake depth). However, composition is tied to a given lake, wherein samples from the same core were more alike than samples collected at similar depths across lakes. Our results illustrate the diversity within lake sediment microbial communities and provide insight into relationships between taxonomy, physicochemical, and geographic properties of north temperate lakes.

Coupled effects of landscape structures and water chemistry on bacterioplankton communities at multi-spatial scales

Bacterioplankton communities in rivers are strongly influenced by the surrounding landscape, yet the relationships between land use and bacterioplankton communities at multi-spatial scales and the mechanisms that shape bacterioplankton communities remain unclear. Here, we collected surface water samples from 14 tributaries of the Yuan River, a secondary tributary of the Yangtze River, which has been heavily impacted by human activities. We characterized the bacterioplankton communities by high-throughput sequencing techniques, and managed to identify the mechanisms governing bacterioplankton community assembly. The results showed that, in general, both landscape compositions and landscape configurations had significant effects on bacterial communities, and the effects were greater at the buffer scale than at the sub-basin scale. Additionally, there was no distinct distance-decay pattern for the effects of landscape structures on bacterial communities from the near-distance (100 m) to the long-distance (1000 m) buffer zones, with the maximal effects occurring in the 1000 m circular buffer (wet season) and 500 m riparian buffer (dry season) zone, respectively. Land use influenced the bacterioplankton community both directly through exogenous inputs (mass effect) and indirectly by affecting water chemistry (species sorting). Variance partitioning analyses showed that the total explanations of bacterial community variations by water chemistry and the intersections of water chemistry and land use (56.2% in wet season and 50.4% in dry season) were higher than that of land use alone (6.1% in wet season and 25.4% in dry season). These suggest that mass effects and species sorting jointly shaped bacterial community assembly, but that the effects of species sorting outweighed those of mass effects. Nevertheless, more biotic and abiotic factors need to be considered to better understand the microbial assembly mechanisms in anthropogenically influenced riverine ecosystems.

Bioavailable Nutrients (N and P) and Precipitation Patterns Drive Cyanobacterial Blooms in Missisquoi Bay, Lake Champlain

Anthropogenic activities release large amounts of nitrogen (N) and phosphorus (P) nutrients into the environment. Sources of nutrients include surface and sub-surface runoffs from agricultural practices with the application of chemical fertilizers and manure as well as combined sewer overflows (CSOs). Nutrient runoffs contribute to the eutrophication of aquatic ecosystems and enhance the growth of cyanobacteria. Precipitation is an important driving force behind the runoff of nutrients from agricultural fields into surrounding water bodies. To understand the dynamics between nutrient input, precipitation and cyanobacterial growth in Missisquoi Bay, Lake Champlain (Quebec), one location in Pike River (a major tributary into the bay) and four locations in Missisquoi Bay were monitored from April to November in 2017 and 2018. Biweekly water samples were analyzed using chemical methods and high-throughput sequencing of 16S rRNA gene amplicons. High concentrations of N and P were typically measured in April and May. Three major spikes in nutrient concentrations were observed in early and mid-summer as well as early fall, all of which were associated with intense cumulative precipitation events of 40 to 100 mm within 7 days prior to sampling. Despite the high concentrations of nutrients in the spring and early summer, the cyanobacterial blooms appeared in mid to late summer as the water temperature increased. Dolichospermum sp. was the major bloom-forming cyanobacterium during both summers. A second intense bloom event of Microcystis was also observed in the fall (October and November) for both years. Variation in the cyanobacteria population was strongly associated with inorganic and readily available fractions of N and P such as nitrites and nitrates (NOx), ammonia (NH₃) and dissolved organic phosphorus (DOP). During blooms, total Kjeldahl nitrogen (TKN) and total particulate phosphorus (TPP) fractions had a substantial influence on total nitrogen (TN) and total phosphorus (TP) concentrations, respectively. The abundance of bacteria involved in the metabolism of nitrogen compared to that of phosphorus revealed the importance of nitrogen on overall microbial dynamics as well as CB formation in the bay. Our findings emphasize the combined influence of precipitation events, temperature and several bioavailable fractions of nitrogen and phosphorus on cyanobacterial bloom episodes.

Seasonal Dynamics Are the Major Driver of Microbial Diversity and Composition in Intensive Freshwater Aquaculture

Aquaculture facilities such as fishponds are one of the most anthropogenically impacted freshwater ecosystems. The high fish biomass reared in aquaculture is associated with an intensive input into the water of fish-feed and fish excrements. This nutrients load may affect the microbial community in the water, which in turn can impact the fish health. To determine to what extent aquaculture practices and natural seasonal cycles affect the microbial populations, we characterized the microbiome of an inter-connected aquaculture system at monthly resolution, over 3 years. The system comprised two fishponds, where fish are grown, and an operational water reservoir in which fish are not actively stocked. Clear natural seasonal cycles of temperature and inorganic nutrients concentration, as well as recurring cyanobacterial blooms during summer, were observed in both the fishponds and the reservoir. The structure of the aquatic bacterial communities in the system, characterized using 16S rRNA sequencing, was explained primarily by the natural seasonality, whereas aquaculture-related parameters had only a minor explanatory power. However, the cyanobacterial blooms were characterized by different cyanobacterial clades dominating at each fishpond, possibly in response to distinct nitrogen and phosphate ratios. In turn, nutrient ratios may have been affected by the magnitude of fish feed input. Taken together, our results show that, even in strongly anthropogenically impacted aquatic ecosystems, the structure of bacterial communities is mainly driven by the natural seasonality, with more subtle effects of aquaculture-related factors.

Effect of Water Chemistry, Land Use Patterns, and Geographic Distances on the Spatial Distribution of Bacterioplankton Communities in an Anthropogenically Disturbed Riverine Ecosystem

The spatial distribution of bacterioplankton communities in rivers is driven by multiple environmental factors, including local and regional factors. Local environmental condition is associated with effect of river water chemistry (through species sorting); ecological process in region is associated with effects of land use and geography. Here, we investigated variation in bacterioplankton communities (free-living, between 0.22 and 5 μm) in an anthropogenically disturbed river using high-throughput DNA sequencing of community 16S rRNA genes in order to investigate the importance of water chemistry, land use patterns, and geographic distance. Among environmental factors, sulfate (SO₄ ^2-), manganese (Mn), and iron (Fe) concentrations were the water chemistry parameters that best explained bacterioplankton community variation. In addition, forest and freshwater areas were the land use patterns that best explained bacterioplankton community variation. Furthermore, cumulative dendritic distance was the geographic distance parameter that best explained bacterial community variation. Variation partitioning analysis revealed that water chemistry, land use patterns, and geographic distances strongly shaped bacterioplankton communities. In particular, the direct influence of land use was prominent, which alone contributed to the highest proportion of variation (26.2% in wet season communities and 36.5% in dry season communities). These results suggest that the mechanisms of species sorting and mass effects together control bacterioplankton communities, although mass effects exhibited higher contributions to community variation than species sorting. Given the importance of allochthonous bacteria input from various land use activities (i.e., mass effects), these results provide new insights into the environmental factors and determinant mechanisms that shape riverine ecosystem communities.

Using Bioinformatics to Quantify the Variability and Diversity of the Microbial Community Structure in Pond Ecosystems of a Subtropical Catchment

Background:

In rural China, many natural water bodies and farmlands have been converted into fish farming ponds as an economic developmental strategy. There is still a limited understanding of how the diversity and structure of microbial communities change in nature and become managed fish pond ecosystems.

Objective:

We aimed to identify the changes of the diversity and structure of microbial community and driving mechanism in pond ecosystems.

Methods:

The datasets of 16S rRNA amplicon sequencing and the concentrations of N and P fractions were achieved in water samples of pond ecosystems. Bioinformatics analysis was used to analyze the diversity and structure of the microbial communities.

Results:

Our results indicated that the diversity and structure of the microbial communities in the natural ponds were significantly different from ones in managed fish ponds. The nutrients of N and P and water environmental factors were responsible for 46.3% and 19.5% of the changes in the structure and diversity of the microbial community, respectively.

Conclusion:

The N and P fractions and water environmental factors influenced the microbial community structure and diversity in pond ecosystems. Fish farming indirectly affected the microbial community by altering the contents of N and P fractions in water bodies of ponds, when a natural pond was converted into a managed fish pond.

Temporal Resistome and Microbial Community Dynamics in an Intensive Aquaculture Facility with Prophylactic Antimicrobial Treatment

Excessive use of antimicrobials in aquaculture is concerning, given possible environmental ramifications and the potential contribution to the spread of antimicrobial resistance (AR). In this study, we explored seasonal abundance of antimicrobial resistance genes and bacterial community composition in the water column of an intensive aquaculture pond stocked with Silver Carp (Hypophthalmichthys molitrix) prophylactically treated with sulfamethoprim (25% sulfadiazine; 5% trimethoprim), relative to an adjacent unstocked reservoir. Bacterial community composition was monitored using high-throughput sequencing of 16S rRNA gene amplicons in eight sampling profiles to determine seasonal dynamics, representing principal stages in the fish fattening cycle. In tandem, qPCR was applied to assess relative abundance of selected antimicrobial resistance genes (sul1, sul2, dfrA1, tetA and blaTEM) and class-1 integrons (int1). Concomitantly, resistomes were extrapolated from shotgun metagenomes in representative profiles. Analyses revealed increased relative abundance of sulfonamide and tetracycline resistance genes in fishpond-03, relative to pre-stocking and reservoir levels, whereas no significant differences were observed for genes encoding resistance to antimicrobials that were not used in the fishpond-03. Seasons strongly dictated bacterial community composition, with high abundance of cyanobacteria in summer and increased relative abundance of Flavobacterium in the winter. Our results indicate that prophylactic use of sulfonamides in intensive aquaculture ponds facilitates resistance suggesting that prophylactic use of these antimicrobials in aquaculture should be restricted.

The direct and indirect effects of land use and water quality on phytoplankton communities in an agriculture-dominated basin

Understanding the factors that control biodiversity in rivers is challenging due to the variety of potential sources, linkages, and processes. This research assesses the effects of land use on phytoplankton communities across water quality gradients. By employing abiotic and biotic datasets of 149 catchments in Lake Chaohu basin, China, and a structural equation model (SEM), the direct and indirect effects of land use and water quality on phytoplankton dynamic were analyzed. Both land use and water quality had statistically significant direct effects on phytoplankton community attribute and diversity, although these effects differed among these indices. For instance, farmland was found to positively affect the abundance and diversity indices, while total nitrogen (TN) had significant positive effects on species richness and abundance. Importantly, the average indirect effects strengthened the effects of land use (e.g., built-up land and woodland) up to 82.4% mainly through nutrients, while the average indirect effects weakened the effects of land use (e.g., farmland) by as much as 49.9% mainly due to nutrients, thus indicating the prevailing role of the effects of land use on phytoplankton based on nutrient concentrations. The results suggest that nutrients can regulate the effect of land use on phytoplankton community attribute and diversity indices. This study highlights the advantages of using an SEM because the potential linkages for phytoplankton diversities are more likely to be identified with this method than with a classical linear regression model. Therefore, SEM has wide application prospects in the field of the conservation of biodiversity in freshwater rivers.

A large-scale assessment of lakes reveals a pervasive signal of land use on bacterial communities

Lakes play a pivotal role in ecological and biogeochemical processes and have been described as "sentinels" of environmental change. Assessing "lake health" across large geographic scales is critical to predict the stability of their ecosystem services and their vulnerability to anthropogenic disturbances. The LakePulse research network is tasked with the assessment of lake health across gradients of land use on a continental scale. Bacterial communities are an integral and rapidly responding component of lake ecosystems, yet large-scale responses to anthropogenic activity remain elusive. Here, we assess the ecological impact of land use on bacterial communities from over 200 lakes covering more than 660,000 km² across Eastern Canada. In addition to community variation between ecozones, land use across Eastern Canada also appeared to alter diversity, community composition, and network structure. Specifically, increasing anthropogenic impact within the watershed lowered diversity. Likewise, community composition was significantly correlated with agriculture and urban development within a watershed. Interaction networks showed decreasing complexity and fewer keystone taxa in impacted lakes. Moreover, we identified potential indicator taxa of high or low lake water quality. Together, these findings point to detectable bacterial community changes of largely unknown consequences induced by human activity within lake watersheds.