Aquatic ecosystem recovery from anthropogenic degradation can be hampered by internal feedbacks that stabilize undesirable states. The challenges of managing and predicting alternative states in lakes are well known, but state shifts in rivers and their attendant effects on ecosystem function remain understudied despite strong recent evidence that such shifts can and do occur. Using three decades of measurements of key state variables such as turbidity, nutrient concentrations, Corbicula fluminea clam densities, and chlorophyll a, including hourly dissolved oxygen, we investigated a sudden shift from phytoplankton to macrophyte dominance in the middle Loire River (France), and its associated effects on the rivers metabolic regime. We show, instead, that despite large and synchronous shifts across all state variables, changes in gross primary production and ecosystem respiration were modest (25% and 14% declines, respectively) and that these shifts lagged the ecosystem state changes by a decade or more. The shift to a macrophyte‐dominated state reduced the sensitivity of primary production to abiotic drivers, altered element cycling efficiency, flipped the net carbon balance from positive to negative, and, crucially, weakened the temporal coupling between production and respiration. This weakened coupling, detected using Granger causality, increased the temporal autocorrelation of net ecosystem production, yielding a robust early warning indicator of both state‐ and metabolic‐shifts that may provide valuable guidance for river restoration.

Identifying the main controlling factors of the stream temperature (Tw) variability is important to target streams sensitive to climate and other drivers of change. The thermal sensitivity (TS), based on relationship between air temperature (Ta) and Tw, of a given stream can be used for quantifying the streams sensitivity to future climate change. This study aims to compare TS for a wide range of temperate streams located within a large French catchment (110,000 km²) using 4 years of hourly data (2008–2012) and to cluster stations sharing similar thermal variabilities and thereby identify environmental key drivers that modify TS at the regional scale. Two successive classifications were carried out: (a) first based on Ta–Tw relationship metrics including TS and (b) second to establish a link between a selection of environmental variables and clusters of stations. Based on weekly Ta–Tw relationships, the first classification identified four thermal regimes with differing annual Tw in terms of magnitude and amplitudes in comparison with Ta. The second classification, based on classification and regression tree method, succeeded to link each thermal regime to different environmental controlling factors. Streams influenced by both groundwater inflows and shading are the most moderated with the lowest TS and an annual amplitude of Tw around half of the annual amplitude of Ta. Inversely, stations located on large streams with a high distance from source and not (or slightly) influenced by groundwater inflows nor shading showed the highest TS, and so, they are very climate sensitive. These findings have implications for guiding river basin managers and other stakeholders in implementing thermal moderation measures in the context of a warming climate and global change.

The quantification of solute and sediment export from drainage basins is challenging. A large proportion of annual or decadal loads of most constituents is exported during relatively short periods of time, a “hot moment,” which vary between constituents and catchments. We developed a new framework based on concentration-discharge (C-Q) relationship to characterize the export regime of stream particulates and solutes during high water periods when the majority of annual and inter-annual load is transported. We evaluated the load flashiness index (percentage of cumulative load that occurs during the highest 2% of daily load, M₂), a function of flow flashiness (percentage of cumulative Q during the highest 2% of daily Q, W₂), and export pattern (slope of the logC-logQ relationship for Q higher than the daily median Q, b_50high). We established this relationship based on long-term water quality and discharge datasets of 580 streams sites of France and USA, corresponding to 2,507 concentration time series of total suspended sediments (TSS), total dissolved solutes (TDS), total phosphorus (TP), nitrate (NO₃), and dissolved organic carbon (DOC), generating 1.5 million data points in highly diverse geologic, climatic, and anthropogenic contexts. Load flashiness (M₂) increased with b_50high and/or W₂. Also, M₂ varied as a function of the constituent transported. M₂ had the highest values for TSS and decreased for the other constituents in the following order: TP, DOC, NO₃, TDS. Based on these results, we constructed a load-flashiness diagram to determine optimal monitoring frequency of dissolved or particulate constituents as a function of b_50high and W₂. Based on M₂, optimal temporal monitoring frequency of the studied constituents decreases in the following order: TSS, TP, DOC, NO₃, and TDS. Finally, we analyzed relationships between these metrics and catchments characteristics. Depending on the constituent, we explained between 30 and 40% of their M₂ variance with simple catchment characteristics, such as stream network density or percentage of intensive agriculture. Therefore, catchment characteristics can be used as a first approach to set up water quality monitoring design where no hydrological and/or water quality monitoring exist.

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.

Temperature has been used to characterize groundwater and stream water exchanges for years. One of the many methods used analyzes propagation of the atmosphere-influenced diurnal signal in sediment to infer vertical velocities. However, despite having good accuracy, the method is usually limited by its small spatial coverage. The appearance of fiber optic distributed temperature sensing (FO-DTS) provided new possibilities due to its high spatial and temporal resolution. Methods based on the heat-balance equation, however, cannot quantify diffuse groundwater inflows that do not modify stream temperature. Our research approach consists of coupling groundwater inflow mapping from a previous article (Part I) and deconvolution of thermal profiles in the sediment to obtain vertical velocities along the entire reach. Vertical flows were calculated along a 400 m long reach, and a period of 9 months (October 2016 to June 2017), by coupling a fiber optic cable buried in thalweg sediment and a few thermal lances at the water–sediment interface. When compared to predictions of hyporheic discharge by traditional methods (differential discharge between upstream and downstream of the monitored reach and the mass-balance method), those of our method agreed only for the low-flow period and the end of the high-flow period. Our method underestimated hyporheic discharge during high flow. We hypothesized that the differential discharge and mass-balance methods included lateral inflows that were not detected by the fiber optic cable buried in thalweg sediment. Increasing spatial coverage of the cable as well as automatic and continuous calculation over the reach may improve predictions during the high-flow period. Coupling groundwater inflow mapping and vertical hyporheic flow allows flow to be quantified continuously, which is of great interest for characterizing and modeling fine hyporheic processes over long periods.