Separating natural from human enhanced methane emissions in headwater streams.

Headwater streams are natural sources of methane but are suffering severe anthropogenic disturbance, particularly land use change and climate warming. The widespread intensification of agriculture since the 1940s has increased the export of fine sediments from land to streams, but systematic assessment of their effects on stream methane is lacking. Here we show that excess fine sediment delivery is widespread in UK streams (n = 236) and, set against a pre-1940s baseline, has markedly increased streambed organic matter (23 to 100 g m-2), amplified streambed methane production and ultimately tripled methane emissions (0.2 to 0.7 mmol CH4 m-2 d-1, n = 29). While streambed methane production responds strongly to organic matter, we estimate the effect of the approximate 0.7 °C of warming since the 1940s to be comparatively modest. By separating natural from human enhanced methane emissions we highlight how catchment management targeting the delivery of excess fine sediment could mitigate stream methane emissions by some 70%.

Machine learning approach towards explaining water quality dynamics in an urbanised river.

Human activities alter river water quality and quantity, with consequences for the ecosystems of urbanised rivers. Quantifying the role of human-induced drivers in controlling spatio-temporal patterns in water quality is critical to develop successful strategies for improving the ecological health of urban rivers. Here, we analyse high-frequency electrical conductivity and temperature data collected from the River Chess in South-East England during a Citizen Science project. Utilizing machine learning, we find that boosted trees outperform GAM and accurately describe water quality dynamics with less than 1% error. SHapley Additive exPlanations reveal the importance of and the (inter)dependencies between the individual variables, such as river level and Wastewater Treatment Works (WWTW) outflow. WWTW outflows give rise to diurnal variations in electrical conductivity, which are detectable throughout the year, and to an increase in average water temperature of 1 [Formula: see text] in a 2 km reach downstream of the wastewater treatment works during low flows. Overall, we showcase how high-frequency water quality measurements initiated by a Citizen Science project, together with machine learning techniques, can help untangle key drivers of water quality dynamics in an urbanised chalk stream.

Hydrological properties predict the composition of microbial communities cycling methane and nitrogen in rivers.

Sediment microbial communities drive the biogeochemical cycles that make rivers globally important sources and sinks of carbon (C) and nitrogen (N). The structure of these communities is strongly determined by the local physico-chemical environment. However, we currently lack an understanding of the factors that determine microbial community structures at the catchment scale. Here, we show that the contribution of groundwater to total river flow (quantified as base flow index; BFI) predicts the structure and diversity of the different microbial functional groups that cycle N and C across nine UK rivers, spanning a geological BFI gradient from 0.23 (clay sediment) to 0.95 (chalk gravel sediment). Furthermore, the GC-content (percentage of guanine-cytosine bases in a DNA sequence) and codon-usage bias of ammonia monooxygenase DNA sequences, and the hydrophobicity and net-charge of the corresponding amino acid sequences, were all strongly correlated with BFI, likely reflecting physiological adaptations to different riverbed sediment structure along the BFI gradient. Our results offer an opportunity to overcome the "paradox of scales" that has seen microbial ecologists focus on small- rather than large-scale environmental variables, enabling us to scale-up our understanding of microbial biogeochemistry to the catchment and beyond.

Fluctuations of water quality time series in rivers follow superstatistics.

Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate water quality time series (such as dissolved oxygen concentrations and electrical conductivity) as measured in rivers and provide evidence that they exhibit superstatistical behavior. Our main example is time series as recorded in the River Chess in South East England. Specifically, we use seasonal detrending and empirical mode decomposition to separate trends from fluctuations for the measured data. With either detrending method, we observe heavy-tailed fluctuation distributions, which are well described by log-normal superstatistics for dissolved oxygen. Contrarily, we find a double peaked non-standard superstatistics for the electrical conductivity data, which we model using two combined χ 2 -distributions.

Towards a microbial process-based understanding of the resilience of peatland ecosystem service provisioning - A research agenda.

Peatlands are wetland ecosystems with great significance as natural habitats and as major global carbon stores. They have been subject to widespread exploitation and degradation with resulting losses in characteristic biota and ecosystem functions such as climate regulation. More recently, large-scale programmes have been established to restore peatland ecosystems and the various services they provide to society. Despite significant progress in peatland science and restoration practice, we lack a process-based understanding of how soil microbiota influence peatland functioning and mediate the resilience and recovery of ecosystem services, to perturbations associated with land use and climate change. We argue that there is a need to: in the short-term, characterise peatland microbial communities across a range of spatial and temporal scales and develop an improved understanding of the links between peatland habitat, ecological functions and microbial processes; in the medium term, define what a successfully restored 'target' peatland microbiome looks like for key carbon cycle related ecosystem services and develop microbial-based monitoring tools for assessing restoration needs; and in the longer term, to use this knowledge to influence restoration practices and assess progress on the trajectory towards 'intact' peatland status. Rapid advances in genetic characterisation of the structure and functions of microbial communities offer the potential for transformative progress in these areas, but the scale and speed of methodological and conceptual advances in studying ecosystem functions is a challenge for peatland scientists. Advances in this area require multidisciplinary collaborations between peatland scientists, data scientists and microbiologists and ultimately, collaboration with the modelling community. Developing a process-based understanding of the resilience and recovery of peatlands to perturbations, such as climate extremes, fires, and drainage, will be key to meeting climate targets and delivering ecosystem services cost effectively.

Application of the microbial community coalescence concept to riverine networks.

Flows of water, soil, litter, and anthropogenic materials in and around rivers lead to the mixing of their resident microbial communities and subsequently to a resultant community distinct from its precursors. Consideration of these events through a new conceptual lens, namely, community coalescence, could provide a means of integrating physical, environmental, and ecological mechanisms to predict microbial community assembly patterns better in these habitats. Here, we review field studies of microbial communities in riverine habitats where environmental mixing regularly occurs, interpret some of these studies within the community coalescence framework and posit novel hypotheses and insights that may be gained in riverine microbial ecology through the application of this concept. Particularly in the face of a changing climate and rivers under increasing anthropogenic pressures, knowledge about the factors governing microbial community assembly is essential to forecast and/or respond to changes in ecosystem function. Additionally, there is the potential for microbial ecology studies in rivers to become a driver of theory development: riverine systems are ideal for coalescence studies because regular and predictable environmental mixing occurs. Data appropriate for testing community coalescence theory could be collected with minimal alteration to existing study designs.

Reach-scale river metabolism across contrasting sub-catchment geologies: Effect of light and hydrology.

We investigated the seasonal dynamics of in-stream metabolism at the reach scale (∼ 150 m) of headwaters across contrasting geological sub-catchments: clay, Greensand, and Chalk of the upper River Avon (UK). Benthic metabolic activity was quantified by aquatic eddy co-variance while water column activity was assessed by bottle incubations. Seasonal dynamics across reaches were specific for the three types of geologies. During the spring, all reaches were net autotrophic, with rates of up to 290 mmol C m-2 d-1 in the clay reach. During the remaining seasons, the clay and Greensand reaches were net heterotrophic, with peak oxygen consumption of 206 mmol m-2 d-1 during the autumn, while the Chalk reach was net heterotrophic only in winter. Overall, the water column alone still contributed to ∼ 25% of the annual respiration and primary production in all reaches. Net ecosystem metabolism (NEM) across seasons and reaches followed a general linear relationship with increasing stream light availability. Sub-catchment specific NEM proved to be linearly related to the local hydrological connectivity, quantified as the ratio between base flow and stream discharge, and expressed on a timescale of 9 d on average. This timescale apparently represents the average period of hydrological imprint for carbon turnover within the reaches. Combining a general light response and sub-catchment specific base flow ratio provided a robust functional relationship for predicting NEM at the reach scale. The novel approach proposed in this study can help facilitate spatial and temporal upscaling of riverine metabolism that may be applicable to a broader spectrum of catchments.

Modelling flow and inorganic nitrogen dynamics on the Hampshire Avon: Linking upstream processes to downstream water quality.

Managing diffuse pollution in catchments is a major issue for environmental managers planning to meet water quality standards and comply with the EU Water Framework Directive. A major source of diffuse pollution is from nitrogen, with high nitrate concentrations affecting water supplies and in-stream ecology. A dynamic, process based model of flow, nitrate and ammonium (INCA-N) has been applied to the Hampshire Avon as part of the NERC Macronutrient Cycles Programme to link upstream and downstream measurements of water chemistry. The model has been calibrated and validated against Environment Agency discharge and solute chemistry data, as well as a data set collected from a river site immediately upstream of the estuary tidal limit. Upstream measurements of denitrification at six sites have been used to evaluate nitrate removal rates in vegetated and non-vegetated conditions. Results show that sediments underlying vegetation were associated with significantly higher rates of nitrate removal than un-vegetated sediments (with an average increase of 245%). These data have been used to scale up rates of nitrate loss to the whole catchment scale and have been implemented via the model. The effects of streambed geology and macrophyte cover on catchment-scale nitrogen dynamics are explored and nutrient fluxes entering the estuary are evaluated. The model is used to test a strategy for nitrogen reduction assessed using a nitrate vulnerable zone (NVZ) methodology. It suggests that nitrate and ammonium concentrations could be reduced by 10% in 10years and much lower nitrogen level can be achieved but only over a long time period.

Fine-scale in situ measurement of riverbed nitrate production and consumption in an armored permeable riverbed.

Alteration of the global nitrogen cycle by man has increased nitrogen loading in waterways considerably, often with harmful consequences for aquatic ecosystems. Dynamic redox conditions within riverbeds support a variety of nitrogen transformations, some of which can attenuate this burden. In reality, however, assessing the importance of processes besides perhaps denitrification is difficult, due to a sparseness of data, especially in situ, where sediment structure and hydrologic pathways are intact. Here we show in situ within a permeable riverbed, through injections of (15)N-labeled substrates, that nitrate can be either consumed through denitrification or produced through nitrification, at a previously unresolved fine (centimeter) scale. Nitrification and denitrification occupy different niches in the riverbed, with denitrification occurring across a broad chemical gradient while nitrification is restricted to more oxic sediments. The narrow niche width for nitrification is in effect a break point, with the switch from activity "on" to activity "off" regulated by interactions between subsurface chemistry and hydrology. Although maxima for denitrification and nitrification occur at opposing ends of a chemical gradient, high potentials for both nitrate production and consumption can overlap when groundwater upwelling is strong.

River bed carbon and nitrogen cycling: state of play and some new directions.

The significance of freshwaters as key players in the global budget of both carbon dioxide and methane has recently been highlighted. In particular, rivers clearly do not act simply as inert conduits merely piping carbon from catchment to coast, but, on the whole, their metabolic activity transforms a considerable fraction of the carbon that they convey. In addition, nitrogen is cycled, sometimes in tight unison with carbon, with appreciable amounts being 'denitrified' between catchment and coast. However, shortfalls in our knowledge about the significance of exchange and interaction between rivers and their catchments, particularly the significance of interactions mediated through hyporheic sediments, are still apparent. From humble beginnings of quantifying the consumption of oxygen by small samples of gravel, to an integrated measurement of reach scale transformations of carbon and nitrogen, our understanding of the cycling of these two macro elements in rivers has improved markedly in the past few decades. However, recent discoveries of novel metabolic pathways in both the nitrogen and carbon cycle across a spectrum of aquatic ecosystems, highlights the need for new directions and a truly multidisciplinary approach to quantifying the flux of carbon and nitrogen through rivers.