Comparing likely effectiveness of urban Nature-based Solutions worldwide: The example of riparian tree planting and water quality.

Amongst a spectrum of benefits, Nature-based Solutions (NBS) are increasingly being advocated as improving the quality of aquatic environments in urban areas. Of these, a widely adopted measure is tree planting. Yet, because of the local complexities and spatial variability of urban hydrological response, it is difficult to predict to what extent improvements in water quality will arise. To overcome this barrier, a standardised approach to process-based model simulation of urban river quality is described (QUESTOR-YARDSTICK (QUESTOR-YS)). The approach eliminates the influence of point sources of pollution and harmonises the way in which river hydrodynamics and contributory catchment size are represented. Thereby, it focuses on differences in water quality between cities due solely to climate, river discharge and urban diffuse nutrient pollution factors. The relative sensitivity to NBS establishment between urban water bodies in different cities anywhere across the world can also potentially be quantified. The method can be readily extended to include wastewater effluents. The validity of the approach is demonstrated for a small river in Birmingham, UK; and thence demonstrated for the case of 10 km of riparian tree planting in Birmingham, Oslo (Norway) and Aarhus (Denmark). Modelling suggests that riparian tree planting can substantially improve water quality in each example city for three key indicators of water quality in sensitive summer conditions (water temperature, chlorophyll-a and dissolved oxygen). Results show the level of benefit achievable in response to a fixed amount of planting will depend on the existing level of riparian tree occupancy.

Detectable Serum Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load (RNAemia) Is Closely Correlated With Drastically Elevated Interleukin 6 Level in Critically Ill Patients With Coronavirus Disease 2019.

BACKGROUND: Although the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load in respiratory specimens has been widely used to diagnose coronavirus disease 2019 (COVID-19), it is undeniable that serum SARS-CoV-2 nucleic acid (RNAemia) could be detected in a fraction of COVID-19 patients. However, it is not clear whether testing for RNAemia is correlated with the occurrence of cytokine storms or with the specific class of patients. METHODS: This study enrolled 48 patients with COVID-19 admitted to the General Hospital of Central Theater Command, People's Liberation Army, a designated hospital in Wuhan, China. The patients were divided into 3 groups according to the Diagnosis and Treatment of New Coronavirus Pneumonia (sixth edition) guidelines issued by the National Health Commission of China. Clinical and laboratory data were collected, and the serum viral load and interleukin 6 (IL-6) level were determined. RESULTS: Analysis of clinical characteristics of 48 cases of COVID-19 showed that RNAemia was diagnosed only in the critically ill group and seemed to reflect the severity of the disease. Furthermore, the level of the inflammatory cytokine IL-6 in critically ill patients increased significantly, almost 10 times that in other patients. More importantly, the extremely high IL-6 level was closely correlated with the detection of RNAemia (R = 0.902). CONCLUSIONS: Detectable serum SARS-CoV-2 RNA (RNAemia) in patients with COVID-19 was associated with elevated IL-6 concentration and poor prognosis. Because elevated IL-6 may be part of a larger cytokine storm that could worsen outcome, IL-6 could be a potential therapeutic target for critically ill patients with an excessive inflammatory response.

MAKING WAVES: Effluent to estuary: Does sunshine or shade reduce downstream footprints of cities?

Riparian tree canopies are key components of river systems, and influence the provision of many essential ecosystem services. Their management provides the potential for substantial control of the downstream persistence of pollutants. The recent advent of new advances in mass spectrometry to detect a large suite of emerging contaminants, high-frequency observations of water quality and gas exchange (e.g., aquatic eddy covariance), and improved spatial resolution in remote sensing (e.g., hyperspectral measurements and high-resolution imagery), presents new opportunities to understand and more comprehensively quantify the role of riparian canopies as Nature-based Solutions. The paper outlines how we may now couple these advances in observational technologies with developments in water quality modelling to integrate simulation of eutrophication impacts with organic matter dynamics and fate of synthetic toxic compounds. In particular regarding solar radiation drivers, this enables us to scale-up new knowledge of canopy-mediated photodegradation processes at a basin level, and integrate it with ongoing improvements in understanding of thermal control, eutrophication, and ecosystem metabolism.

Significant improvement in freshwater invertebrate biodiversity in all types of English rivers over the past 30 years.

There remains a persistent concern that freshwater biodiversity is in decline and being threatened by pollution. As the UK, and particularly England, is a densely populated nation with rivers of modest dilution capacity, this location is very suitable to examine how freshwater biodiversity has responded to human pressures over the past 30 years. A long-term dataset of 223,325 freshwater macroinvertebrate records from 1989 to 2018 for England was retrieved and examined. A sub-set of approximately 200 sites per English Region (1515 sites in total with 62,514 samples), with the longest and most consistent records were matched with predicted wastewater exposure, upstream land cover and terrain characteristics (latitude, altitude, slope gradient and flow discharge). To understand changes in macroinvertebrate diversity and sensitivity with respect to these parameters, the biotic indices of (i) overall family richness, (ii) Ephemeroptera, Plecoptera, Trichoptera (EPT) family richness, and (iii) the Biological Monitoring Working Party (BMWP) scores of NTAXA (number of scoring taxa) and (iv) ASPT (average score per taxon) were selected. A review of how close the BMWP scores come to those expected at minimally impacted reference sites was included. For all latitudes, altitudes, channel slope, river size, wastewater exposure levels, and differing proportions of upstream woodland, seminatural, arable and urban land cover, all diversity or sensitivity indices examined improved over this period, although this improvement has slowed in some cases post 2003. Mean overall family richness has increased from 15 to 25 family groups, a 66 % improvement. The improvement in mean EPT family richness (3 to 10 families, >300 % improvement), which are considered to be particularly sensitive to pollution, implies macroinvertebrate diversity has benefited from a national improvement in critical components of water quality.

Distinct indicators of land use and hydrology characterize different aspects of riverine phytoplankton communities.

Given the many threats to freshwater biodiversity, we need to be able to resolve which of the multiple stressors present in rivers are most important in driving change. Phytoplankton are a key component of the aquatic ecosystem, their abundance, species richness and functional richness are important indicators of ecosystem health. In this study, spatial variables, physiochemical conditions, water flow alterations and land use patterns were considered as the joint stressors from a lowland rural catchment. A modeling approach combining an ecohydrological model with machine learning was applied. The results implied that land use and flow regime, rather than nutrients, were most important in explaining differences in the phytoplankton community. In particular, the percentage of water body area and medium level residential urban area were key to driving the rising phytoplankton abundance in this rural catchment. The proportion of forest and pasture area were the leading factors controlling the variations of species richness. In this case deciduous forest cover affected the species richness in a positive way, while, pasture share had a negative effect. Indicators of hydrological alteration were found to be the best predictors for the differences in functional richness. This integrated model framework was found to be suitable for analysis of complex environmental conditions in river basin management. A key message would be the significance of forest area preservation and ecohydrological restoration in maintaining both phytoplankton richness and their functional role in river ecosystems.

Using integrated models to analyze and predict the variance of diatom community composition in an agricultural area.

With the growing demand of assessing the ecological status, there is the need to fully understand the relationship between the planktic diversity and the environmental factors. Species richness and Shannon index have been widely used to describe the biodiversity of a community. Besides, we introduced the first ordination value from non-metric multidimensional scaling (NMDS) as a new index to represent the community similarity variance. In this study, we hypothesized that the variation of diatom community in rivers in an agricultural area was influenced by hydro-chemical variables. We collected daily mixed water samples using ISCO auto water samplers for diatoms and for water-chemistry analysis at the outlet of a lowland river for a consecutive year. An integrated modeling was adopted including random forest (RF) to decide the importance of the environmental factors influencing diatoms, generalized linear models (GLMs) combined with 10-folder cross validation to analyze and predict the diatom variation. The hierarchical analysis highlighted antecedent precipitation index (API) as the controlling hydrological variable while water temperature, Si2+ and PO4-P as the main chemical controlling factors in our study area. The generalized linear models performed better prediction for Shannon index (R2 = 0.44) and NMDS (R2 = 0.51) than diatom abundance (R2 = 0.25) and species richness (R2 = 0.25). Our findings confirmed that Shannon index and the NMDS as an index showed good performance in explaining the relationship between stream biota and its environmental factors and in predicting the diatom community development based on the hydro-chemical predictors. Our study showed and highlighted the important hydro-chemical factors in the agricultural rivers, which could contribute to the further understanding of predicting diatom community development and could be implemented in the future water management protocol.

Influences of pesticides, nutrients, and local environmental variables on phytoplankton communities in lentic small water bodies in a German lowland agricultural area.

Agrochemicals such as pesticides and nutrients are concurrent chemical stressors in freshwater aquatic ecosystems surrounded by agricultural areas. Lentic small water bodies (LSWB) are ecologically significant habitats especially for maintaining biodiversity but highly understudied. Phytoplankton are ideal indicator species for stress responses. Functional features of the phytoplankton are important in revealing the processes that determine the structure of the communities. In this study, we investigated the effects of pesticides, nutrients, and local environmental variables on the species composition and functional features of phytoplankton communities in LSWB. We studied pesticide toxicity of ninety-four pesticides, three nutrients (NH4-N, NO3-N and PO4-P) and local environment variables (precipitation, water level change, temperature, dissolved oxygen concentration, electrical conductivity, pH) in five LSWB over twelve weeks during the spring pesticide application period. We explored respective changes in species composition of phytoplankton community and functional features. Redundancy analysis and variance partitioning analysis were applied to correlate phytoplankton community compositions with the pesticide toxicity (as maximum toxicity in toxic units), nutrients and local environment variables. We used multiple linear regression models to identify the main environmental variables driving the functional features of phytoplankton communities. Pesticide toxicity, nutrients and local environmental variables significantly (p < 0.001) contributed to shaping phytoplankton community composition individually. Local environment variables showed the highest pure contribution for driving phytoplankton composition (12%), followed by nutrients (8%) and pesticide toxicity (2%). Functional features (represented by functional diversity and functional redundancy) of the phytoplankton community were significantly affected by pesticide toxicity and nutrients concentrations. The functional richness and functional evenness were negatively affected by PO4-P concentrations. Pesticide toxicity was positively correlated with functional redundancy indices. Our findings emphasized the relative importance of concurrent multiple stressors (e.g., pesticides and nutrients) on phytoplankton community structure, directing potential effects on metacommunity structures in aquatic ecosystems subjected to agricultural runoff.

Riverine phytoplankton shifting along a lentic-lotic continuum under hydrological, physiochemical conditions and species dispersal.

The importance of phytoplankton-based bio-assessment has been recently recognized in lowland rivers which are affected by multi-environmental factors. However, some basic questions remain unclear to date, such as: (i) spatial and temporal variations of phytoplankton, (ii) the impact of upstream lakes on downstream community, (iii) the main drivers for species composition or (iv) the regional biodiversity along a lentic-lotic continuum. To answer these questions, we collected and analyzed the fluvial phytoplankton communities along a lentic-lotic continuum from a German lowland catchment, where a well-established ecohydrological modeling predicted long-term discharges at each sampling site. Our results revealed very high spatial and temporal variations of phytoplankton community. The changes of a lake on downstream phytoplankton assemblages were significant, especially the nearest reach after the lake. However, these influences varied along with seasons and limited in a relatively short distance to the lake. Redundancy analysis and Mantel tests showed that phytoplankton composition and dissimilarities along the lentic-lotic continuum attributed more to local hydrological and physicochemical variables than species dispersal, which confirmed the suitability of lowland phytoplankton-based bioassessment. In addition, our findings highlighted the importance of flow regime in shaping phytoplankton community composition and regional beta diversities. This study emphasized the necessity to include the hydrological variables and their relationship with phytoplankton community in future bio-monitoring investigations.

Phytotoxicity, bioaccumulation and potential risks of plant irrigations using cyanobloom-loading freshwater.

The toxicity of cyanotoxins on plant has been reported. However, in eutrophic waters harmful cyanobacteria are associated with other environmental pollutants, such as persistent organic pollutants (POPs) and metals. Information on the phytotoxicity and bioaccumulation of coexisted cyanotoxins and these environmental pollutants is still lacking. In this study, the combined phytotoxicities of three types of cyanobacteria-associated pollutants, i.e., microcystin-LR (MC-LR), cadmium (Cd), 2, 4, 4'-Trichlorobiphenyl (PCB-28) were systematically investigated. After 7-days exposure, strong synergistic effects can be detected when Arabidopsis thaliana seeds and seedlings exposed to binary mixtures of MC-LR+PCB-28 and PCB-28+Cd. The strongest inhibition occurred when A. thaliana exposed to their ternary mixture under both glasshouse and semi-field conditions. Moreover, bioaccumulation of MC-LR, Cd and PCB-28 was enhanced when seedlings exposed to their binary/ternary mixtures, especially when seedlings were treated with higher concentrations of toxicants (MC-LR, 1mgL-1; Cd, 10mgL-1; PCB-28, 1µgL-1). Additionally, pronounced toxic effects could be determined under 7-days after seedlings were irrigated with raw cyanobloom-containing water (collected from Lake Taihu in China)and its dilutions. Seeds production decreased significantly after the continuous irrigation with cyanoblooms-containing water. Collectively, this work will be an informative implication for risks of cyanoblooms and adequate utilization of freshwater containing cyanoblooms for crop irrigation.

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

Importance of sampling frequency when collecting diatoms.

There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms' temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013-30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1-5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.