Temperature, productivity, and habitat characteristics collectively drive lake food web structure.

While many efforts have been devoted to understand variations in food web structure among terrestrial and aquatic ecosystems, the environmental factors influencing food web structure at large spatial scales remain hardly explored. Here, we compiled biodiversity inventories to infer food web structure of 67 French lakes using an allometric niche-based model and tested how environmental variables (temperature, productivity, and habitat) influence them. By applying a multivariate analysis on 20 metrics of food web topology, we found that food web structural variations are represented by two distinct complementary and independent structural descriptors. The first is related to the overall trophic diversity, whereas the second is related to the vertical structure. Interestingly, the trophic diversity descriptor was mostly explained by habitat size (26.7% of total deviance explained) and habitat complexity (20.1%) followed by productivity (dissolved organic carbon: 16.4%; nitrate: 9.1%) and thermal variations (10.7%). Regarding the vertical structure descriptor, it was mostly explained by water thermal seasonality (39.0% of total deviance explained) and habitat depth (31.9%) followed by habitat complexity (8.5%) and size (5.5%) as well as annual mean temperature (5.6%). Overall, we found that temperature, productivity, and habitat characteristics collectively shape lake food web structure. We also found that intermediate levels of productivity, high levels of temperature (mean and seasonality), as well as large habitats are associated with the largest and most complex food webs. Our findings, therefore, highlight the importance of focusing on these three components especially in the context of global change, as significant structural changes in aquatic food webs could be expected under increased temperature, pollution, and habitat alterations.

Unexpected spatial stability of water chemistry in headwater stream networks.

Understanding how water and solutes enter and propagate through freshwater landscapes in the Anthropocene is critical to protecting and restoring aquatic ecosystems and ensuring human water security. However, high hydrochemical variability in headwater streams, where most carbon and nutrients enter river networks, has hindered effective modelling and management. We developed an analytical framework informed by landscape ecology and catchment hydrology to quantify spatiotemporal variability across scales, which we tested in 56 headwater catchments, sampled periodically over 12 years in western France. Unexpectedly, temporal variability in dissolved carbon, nutrients and major ions was preserved moving downstream and spatial patterns of water chemistry were stable on annual to decadal timescales, partly because of synchronous variation in solute concentrations. These findings suggest that while concentration and flux cannot be extrapolated among subcatchments, periodic sampling of headwaters provides valuable information about solute sources and subcatchment resilience to disturbance.

Deep denitrification: Stream and groundwater biogeochemistry reveal contrasted but connected worlds above and below.

Excess nutrients from agricultural and urban development have created a cascade of ecological crises around the globe. Nutrient pollution has triggered eutrophication in most freshwater and coastal ecosystems, contributing to a loss in biodiversity, harm to human health, and trillions in economic damage every year. Much of the research conducted on nutrient transport and retention has focused on surface environments, which are both easy to access and biologically active. However, surface characteristics of watersheds, such as land use and network configuration, often do not explain the variation in nutrient retention observed in rivers, lakes, and estuaries. Recent research suggests subsurface processes and characteristics may be more important than previously thought in determining watershed-level nutrient fluxes and removal. In a small watershed in western France, we used a multi-tracer approach to compare surface and subsurface nitrate dynamics at commensurate spatiotemporal scales. We combined 3-D hydrological modeling with a rich biogeochemical dataset from 20 wells and 15 stream locations. Water chemistry in the surface and subsurface showed high temporal variability, but groundwater was substantially more spatially variable, attributable to long transport times (10-60 years) and patchy distribution of the iron and sulfur electron donors fueling autotrophic denitrification. Isotopes of nitrate and sulfate revealed fundamentally different processes dominating the surface (heterotrophic denitrification and sulfate reduction) and subsurface (autotrophic denitrification and sulfate production). Agricultural land use was associated with elevated nitrate in surface water, but subsurface nitrate concentration was decoupled from land use. Dissolved silica and sulfate are affordable tracers of residence time and nitrogen removal that are relatively stable in surface and subsurface environments. Together, these findings reveal distinct but adjacent and connected biogeochemical worlds in the surface and subsurface. Characterizing how these worlds are linked and decoupled is critical to meeting water quality targets and addressing water issues in the Anthropocene.

Direct habitat descriptors improve the understanding of the organization of fish and macroinvertebrate communities across a large catchment.

In large-scale aquatic ecological studies, direct habitat descriptors (e.g. water temperature, hydraulics in river reaches) are often approximated by coarse-grain surrogates (e.g. air temperature, discharge respectively) since they are easier to measure or model. However, as biological variability can be very strong at the habitat scale, surrogate variables may have a limited ability to capture all of this variability, which may lead to a lesser understanding of the ecological processes or patterns of interest. In this study, we aimed to compare the capacity of direct habitat descriptors vs. surrogate environmental variables to explain the organization of fish and macroinvertebrate communities across the Loire catchment in France (105 km2). For this purpose, we relied on high-resolution environmental data, extensive biological monitoring data (>1000 sampling stations) and multivariate analyses. Fish and macroinvertebrate abundance datasets were considered both separately and combined to assess the value of a cross-taxa approach. We found that fish and macroinvertebrate communities exhibited weak concordance in their organization and responded differently to the main ecological gradients. Such variations are probably due to fundamental differences in their life-history traits and mobility. Regardless of the biological group considered, direct habitat descriptors (water temperature and local hydraulic variables) consistently explained the organization of fish and macroinvertebrate communities better than surrogate descriptors (air temperature and river discharge). Furthermore, the organization of fish and macroinvertebrate communities was slightly better explained by the combination of direct or surrogate environmental variables when the two biological groups were considered together than when considered separately. Tied together, these results emphasize the importance of using a cross-taxa approach in association with high-resolution direct habitat variables to more accurately explain the organization of aquatic communities.

Long-term impacts of nutrient control, climate change, and invasive clams on phytoplankton and cyanobacteria biomass in a large temperate river.

Recent studies suggest that climate change, with warmer water temperatures and lower and longer low flows, may enhance harmful planktic cyanobacterial growth in lakes and large rivers. Concomitantly, controlling nutrient loadings has proven effective in reducing phytoplankton biomass especially in North America and Western Europe. In addition, the impact of invasive benthic filter-feeder species such as Corbicula on phytoplankton has largely been overlooked in large rivers, leading to even more uncertainty in predicting future trajectories in river water quality. To investigate how nutrient control, climate change and invasion of benthic filter-feeders may affect phytoplankton biomass and composition, we assembled a large database on the entire water course of the River Loire (France) over three decades (1991-2019). We focus on cyanobacteria to provide an in-depth analysis of the 30-year trend and insights on future possible trajectories. Since 1991, total phytoplankton and cyanobacteria biomasses have decreased 10-fold despite warmer water temperature (+0.23 °C·decade-1) and lower summer flow (-0.25 L·s-1·km-2·decade-1). In the long-term, the contribution of planktic cyanobacteria to total biomass was on average 2.8%. The main factors driving total phytoplankton and cyanobacteria biomasses were total phosphorus (4-fold decrease), the abundance of Corbicula clams (from absence before 1998 to 250-1250 individuals·m-2 after 2010), the duration of summer low flows and the intensity of summer heatwaves. The River Loire constitutes an example in Europe of how nutrient control can be an efficient mitigation strategy, counteracting already visible effects of climate change on the thermal regime and flow pattern of the river. This may hold true under future conditions, but further work is needed to account for the climate trajectory, land and water use scenarios, the risk of enhanced benthic biofilm and macrophyte proliferation, together with the spread of invasive filter-feeding bivalves.

Thermal signatures identify the influence of dams and ponds on stream temperature at the regional scale.

Anthropogenic impoundments (e.g. large dams, small reservoirs, and ponds) are expanding in number globally, influencing downstream temperature regimes in a diversity of ways that depend on their structure and position along the river continuum. Because of the manifold downstream thermal responses, there has been a paucity of studies characterizing cumulative effect sizes at the catchment scale. Here, we introduce five thermal indicators based on the stream-air temperature relationship that together can identify the altered thermal signatures of dams and ponds. We used this thermal signature approach to evaluate a regional dataset of 330 daily stream temperature time series from stations throughout the Loire River basin, France, from 2008 to 2018. This basin (105 km2) is one of the largest European catchments with contrasting natural and anthropogenic characteristics. The derived thermal signatures were cross-validated with several known catchment characteristics, which strongly supported separation into dam-like, pond-like and natural-like signatures. We characterize the thermal regime of each thermal signature and contextualize it using a set of ecologically relevant thermal metrics. Results indicate that large dams decreased summer stream temperature by 2 °C and delayed the annual stream temperature peak by 23 days relative to the natural regimes. In contrast, the cumulative effects of upstream ponds increased summer stream temperature by 2.3 °C and increased synchrony with air temperature regimes. These thermal signatures thus allow for identifying and quantifying downstream thermal and ecological influences of different types of anthropogenic infrastructures without prior information on the source of modification and upstream water temperature conditions.

Eutrophication: A new wine in an old bottle?

Eutrophication is one of the most common causes of water quality impairment of inland and marine waters. Its best-known manifestations are toxic cyanobacteria blooms in lakes and waterways and proliferations of green macro algae in coastal areas. The term eutrophication is used by both the scientific community and public policy-makers, and therefore has a myriad of definitions. The introduction by the public authorities of regulations to limit eutrophication is a source of tension and debate on the activities identified as contributing or having contributed decisively to these phenomena. Debates on the identification of the driving factors and risk levels of eutrophication, seeking to guide public policies, have led the ministries in charge of the environment and agriculture to ask for a joint scientific appraisal to be conducted on the subject. Four French research institutes were mandated to produce a critical scientific analysis on the latest knowledge of the causes, mechanisms, consequences and predictability of eutrophication phenomena. This paper provides the methodology and the main findings of this two years exercise involving 40 scientific experts.

Widespread diminishing anthropogenic effects on calcium in freshwaters.

Calcium (Ca) is an essential element for almost all living organisms. Here, we examined global variation and controls of freshwater Ca concentrations, using 440 599 water samples from 43 184 inland water sites in 57 countries. We found that the global median Ca concentration was 4.0 mg L-1 with 20.7% of the water samples showing Ca concentrations ≤ 1.5 mg L-1, a threshold considered critical for the survival of many Ca-demanding organisms. Spatially, freshwater Ca concentrations were strongly and proportionally linked to carbonate alkalinity, with the highest Ca and carbonate alkalinity in waters with a pH around 8.0 and decreasing in concentrations towards lower pH. However, on a temporal scale, by analyzing decadal trends in >200 water bodies since the 1980s, we observed a frequent decoupling between carbonate alkalinity and Ca concentrations, which we attributed mainly to the influence of anthropogenic acid deposition. As acid deposition has been ameliorated, in many freshwaters carbonate alkalinity concentrations have increased or remained constant, while Ca concentrations have rapidly declined towards or even below pre-industrial conditions as a consequence of recovery from anthropogenic acidification. Thus, a paradoxical outcome of the successful remediation of acid deposition is a globally widespread freshwater Ca concentration decline towards critically low levels for many aquatic organisms.

Trends and seasonality of river nutrients in agricultural catchments: 18years of weekly citizen science in France.

Agriculture and urbanization have disturbed three-quarters of global ice-free land surface, delivering huge amounts of nitrogen and phosphorus to freshwater ecosystems. These excess nutrients degrade habitat and threaten human food and water security at a global scale. Because most catchments are either currently subjected to, or recovering from anthropogenic nutrient loading, understanding the short- and long-term responses of river nutrients to changes in land use is essential for effective management. We analyzed a never-published, 18-year time series of anthropogenic (NO3- and PO43-) and naturally derived (dissolved silica) riverine nutrients in 13 catchments recovering from agricultural pollution in western France. In a citizen science initiative, high-school students sampled catchments weekly, which ranged from 26 to 1489km2. Nutrient concentrations decreased substantially over the period of record (19 to 50% for NO3- and 14 to 80% for PO43-), attributable to regional, national, and international investment and regulation, which started immediately prior to monitoring. For the majority of catchments, water quality during the summer low-flow period improved faster than during winter high-flow conditions, and annual minimum concentrations improved relatively faster than annual maximum concentrations. These patterns suggest that water-quality improvements were primarily due to elimination of discrete nutrient sources with seasonally-constant discharge (e.g. human and livestock wastewater), agreeing with available land-use and municipal records. Surprisingly, long-term nutrient decreases were not accompanied by changes in nutrient seasonality in most catchments, attributable to persistent, diffuse nutrient stocks. Despite decreases, nutrient concentrations in almost all catchments remained well above eutrophication thresholds, and because additional improvements will depend on decreasing diffuse nutrient sources, future gains may be much slower than initial rate of recovery. These findings demonstrate the value of citizen science initiatives in quantifying long-term and seasonal consequences of changes in land management, which are necessary to identify sustainable limits and predict recovery timeframes.

Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data.

Modelling river temperature at the catchment scale is needed to understand how aquatic communities may adapt to current and projected climate change. In small and medium rivers, riparian vegetation can greatly reduce maximum water temperature by providing shade. It is thus important that river temperature models are able to correctly characterise the impact of this riparian shading. In this study, we describe the use of a spatially-explicit method using LiDAR-derived data for computing the riparian shading on direct and diffuse solar radiation. The resulting data are used in the T-NET one-dimensional stream temperature model to simulate water temperature from August 2007 to July 2014 for 270km of the Loir River, an indirect tributary of the Loire River (France). Validation is achieved with 4 temperature monitoring stations spread along the Loir River. The vegetation characterised with the LiDAR approach provides a cooling effect on maximum daily temperature (Tmax) ranging from 3.0°C (upstream) to 1.3°C (downstream) in late August 2009. Compared to two other riparian shading routines that are less computationally-intensive, the use of our LiDAR-based methodology improves the bias of Tmax simulated by the T-NET model by 0.62°C on average between April and September. However, difference between the shading routines reaches up to 2°C (monthly average) at the upstream-most station. Standard deviation of errors on Tmax is not improved. Computing the impact of riparian vegetation at the hourly timescale using reach-averaged parameters provides results close to the LiDAR-based approach, as long as it is supplied with accurate vegetation cover data. Improving the quality of riparian vegetation data should therefore be a priority to increase the accuracy of stream temperature modelling at the regional scale.

Nutrient inputs and hydrology together determine biogeochemical status of the Loire River (France): Current situation and possible future scenarios.

The Grafs-Seneque/Riverstrahler model was implemented for the first time on the Loire River for the 2002-2014 period, to explore eutrophication after improvement of wastewater treatments. The model reproduced the interannual levels and seasonal trends of the major water quality variables. Although eutrophication has been impressively reduced in the drainage network, a eutrophication risk still exists at the coast, as shown by the N-ICEP indicator, pointing out an excess of nitrogen over silica and phosphorus. From maximum biomass exceeding 120 µgChla l-1 in the 1980's, we observed decreasing maximum values from 80 to 30 µgChla l-1 during the period studied. Several scenarios were explored. Regarding nutrient point sources, a low wastewater treatment scenario, similar to the situation in the 1980's, was elaborated, representing much greater pollution than the reference period (2002-2014). For diffuse sources, two agricultural scenarios were elaborated for reducing nitrogen, one with a strict application of the agricultural directives and another investigating the impact of radical structural changes in agriculture and the population's diet. Although reduced, a risk of eutrophication would remain, even with the most drastic scenario. In addition, a pristine scenario, with no human activity within the basin, was devised to assess water quality in a natural state. The impact of a change in hydrology on the Loire biogeochemical functioning was also explored according to the effect of climate change by the end of the 21st century. The EROS hydrological model was used to force Riverstrahler, considering the most pessimistic SRES A2 scenario run with the ARPEGE model. Nutrient fluxes all decreased due to a >50% reduction in the average annual discharge, overall reducing the risk of coastal eutrophication, but worsening the water quality status of the river network. The Riverstrahler model could be useful to help water managers contend with future threats in the Loire River, at the scale of its basin and at smaller nested scales.

The influence of contrasting suspended particulate matter transport regimes on the bias and precision of flux estimates.

A large database (507 station-years) of daily suspended particulate matter (SPM) concentration and discharge data from 36 stations on river basins ranging from 600 km(2) to 600,000 km(2) in size (USA and Europe) was collected to assess the effects of SPM transport regime on bias and imprecision of flux estimates when using infrequent surveys and the discharge-weighted mean concentration method. By extracting individual SPM concentrations and corresponding discharge values from the database, sampling frequencies from 12 to 200 per year were simulated using Monte Carlo techniques. The resulting estimates of yearly SPM fluxes were compared to reference fluxes derived from the complete database. For each station and given frequency, bias was measured by the median of relative errors between estimated and reference fluxes, and imprecision by the difference between the upper and lower deciles of relative errors. Results show that the SPM transport regime of rivers affects the bias and imprecision of fluxes estimated by the discharge-weighted mean concentration method for given sampling frequencies (e.g. weekly, bimonthly, monthly). The percentage of annual SPM flux discharged in 2% of time (Ms(2)) is a robust indicator of SPM transport regime directly related to bias and imprecision. These errors are linked to the Ms(2) indicator for various sampling frequencies within a specific nomograph. For instance, based on a deviation of simulated flux estimates from reference fluxes lower than +/-20% and a bias lower than 1% or 2%, the required sampling intervals are less than 3 days for rivers with Ms(2) greater than 40% (basin size<10,000 km(2)), between 3 and 5 days for rivers with Ms(2) between 30 and 40% (basin size between 10,000 and 50,000 km(2)), between 5 and 12 days for Ms(2) from 20% to 30% (basin size between 50,000 and 200,000 km(2)), 12-20 days for Ms(2) in the 15-20% range (basin size between 200,000 and 500,000 km(2)).

Assessing N emissions in surface water at the national level: comparison of country-wide vs. regionalized models.

Many countries are developing models to estimate N emissions in rivers as part of national-scale water quality assessments. Generally, models are applied with national databases, while at the regional scale, more detailed databases are sometimes available. This paper discusses pros and cons of developing regionalized models versus applying countrywide models. A case study is used to support the discussion. The model used, called Nutting-N (NUTrient Transfer modelING-Nitrogen), relies on a statistical approach linking nitrogen sources and watershed land and river characteristics and aims to evaluate the risk of water bodies failing to reach quality objectives defined by national and federal policies. After calibration and evaluation at the national scale (France), the predictive quality of the model was compared with two regionalized models in a crystalline massif (Brittany, western France, 27,000 km(2)) and in a sedimentary basin (Seine, Paris basin, 78,000 km(2)), where detailed regional databases are available. The national-scale model provided robust predictions in most conditions encountered in France (efficiency=0.69). Terrestrial retention was related mainly to specific runoff, and its median value was estimated at 49% of the N surplus, whereas median river retention represented 18% of incoming N discharge. Regionalizing the model generally improved goodness-of-fit, as the root mean squared error was reduced by 6-24%. However, precision of parameter estimates degraded when too few monitoring basins were available or when variability in land and river characteristics was too low in the calibration dataset. Hence, regional-scale models should be advocated only after the trade-off between improvement of fit and degradation of parameter estimates is examined.

Estimation of local extreme suspended sediment concentrations in California Rivers.

The total amount of suspended sediment load carried by a stream during a year is usually transported during one or several extreme events related to high river flow and intense rainfall, leading to very high suspended sediment concentrations (SSCs). In this study quantiles of SSC derived from annual maximums and the 99th percentile of SSC series are considered to be estimated locally in a site-specific approach using regional information. Analyses of relationships between physiographic characteristics and the selected indicators were undertaken using the localities of 5-km radius draining of each sampling site. Multiple regression models were built to test the regional estimation for these indicators of suspended sediment transport. To assess the accuracy of the estimates, a Jack-Knife re-sampling procedure was used to compute the relative bias and root mean square error of the models. Results show that for the 19 stations considered in California, the extreme SSCs can be estimated with 40-60% uncertainty, depending on the presence of flow regulation in the basin. This modelling approach is likely to prove functional in other Mediterranean climate watersheds since they appear useful in California, where geologic, climatic, physiographic, and land-use conditions are highly variable.