Florentina Moatar

How much of the excess CO ₂ in running waters comes from in‐stream respiration of organic carbon? To answer this, we developed a 30‐yr metabolism‐carbonate system database at an hourly resolution for the Loire River, France, a large, alkaline river. We asked the following questions: what are the intra‐annual patterns of in‐stream (“internal”) CO ₂ production, what processes drive these patterns, and how do these patterns depend on autotrophic community composition? We estimated internal CO ₂ production as the ratio of net ecosystem production to CO ₂ water‐to‐air flux (FCO ₂ ). We also estimated the daily ecosystem quotient (EQ, O ₂ released: dissolved inorganic carbon [DIC] consumed) and the prevalence of non‐CO ₂ autotrophic DIC uptake pathways under CO ₂ depletion. Median internal CO ₂ production was 49% of FCO ₂ in the Loire from 1990 to 2022. The river predictably shifted from a heterotrophic, CO ₂ source to an autotrophic, CO ₂ sink as a function of discharge, leading to four trophic‐flux (“trophlux”) states: autotrophic‐sink, autotrophic‐source, heterotrophic‐sink, and heterotrophic‐source. During autotrophic states (41% of the time), CO ₂ depletion (FCO ₂ ≤ 0, median pCO ₂ = 135 μ atm) led to the use of and of CO ₂ released by CaCO ₃ precipitation as alternative DIC sources to autotrophs to support their high rates of primary production (occurring on average for 33% of the growing season). Finally, during a period of phytoplankton dominance, the median EQ was 1.3, which was reduced to 1.0 under macrophyte dominance. This work describes a dynamic coupling among autotrophic communities, calcium carbonate equilibria, and discharge‐controlled FCO ₂ that together imply lower‐than‐predicted FCO ₂ magnitude and greater‐than‐predicted internal CO ₂ production for the Loire River.

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.

Stream dissolved oxygen (DO) dynamics are an outcome of metabolic activity and subsequently regulate ecosystem functions such as in‐stream solute and sediment reactions. The synchronization of DO signals in and across stream networks is both a cause and effect of the mode and timing of these functions, but there is limited empirical evidence for network patterns of DO synchrony. We used high frequency DO measurements at 42 sites spanning five catchments and stream orders to evaluate DO signal synchrony in response to variation in light (a driver of photosynthesis) and discharge (a control on DO signal spatial extent). We hypothesized that stream network DO synchrony arises when regional controls dominate: when light inputs are synchronous and when longitudinal hydrologic connectivity is high. By complement, we predicted that DO signal synchrony decreases as light becomes more asynchronous and stream flows decline or become discontinuous. Our results supported this hypothesis: greater DO signal synchrony arose with increasing light synchrony and flow connectivity. A model including these two controls explained 70% of variation in DO synchrony. We conclude that DO synchrony patterns within‐ and across‐networks support the current paradigm of discharge and light control on stream metabolic activity. Finally, we propose that DO synchrony patterns are likely a useful prerequisite for scaling subdaily metabolism estimates to network and regional scales.

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.

Solute and sediment catchment exports from drainage basins are difficult to quantify because they are exported during “hot moments”, generally during high water periods.   We present here a simple model for predicting load flashiness (M2, proportion of load exported during the highest 2% of flows) from flow flashiness (W2, proportion of flows exported during the highest 2% of flows) and export pattern (b50high, linear slope of the log concentration-log discharge relationship based on data above the median flow only). The model is parameterised based on an extensive monthly-sample data set from France, and validated using an independent daily-sample long-term data set from US including several rivers near Lake Erie (altogether over 1.5 Million discharge-concentration Based on this model, we constructed a load-flashiness diagram to determine optimal monitoring frequency of dissolved or particulate constituents as a function of b50high 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 to 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. The load flashiness M2 can also be used to optimize monitoring frequency to reach a certain level of annual load uncertainty (here 10%) for loads trend detection required for instance by international conventions such as OSPAR and HELCOM. Regulatory monitoring in Europe, recommended by the WFD, promotes the monthly sampling for any monitored constituents (dissolved and particulate) and for any basin size. Such standardized monitoring does not take into account the actual variability of the constituent concentration and loads, particularly for the small (100 – 1000 km²) and very small (< 100 km²) basins. For instance, our results show that a 30 days sampling frequency is not appropriate to calculate loads with a reasonable uncertainty (+/- 10%) in more than 90% of cases.

Heat has been used as a tracer to identify and quantify groundwater inflows into streams. Over the last decade, a few methods have used fiber‐optic distributed temperature sensing to facilitate assessment of such inflows into small streams. However, these methods focused mainly on the groundwater percentage and the thermal contrast between groundwater and surface water without considering the flow regime of the surface water. In this study, artificial water inflows into a controlled flume were examined using fiber‐optic distributed temperature sensing to quantify the thermal anomalies induced as a function of the flow regime (turbulent or laminar). Computer simulations were then performed to widen the range of the parameters tested and provide insight into the physical processes involved. Experiments conducted under the turbulent regime were in accordance with results and uncertainties of previous studies. Under the laminar regime, however, the inflow‐induced thermal anomalies were always smaller than those under the turbulent regime for a given inflow percentage. Therefore, the actual inflow percentage may be underestimated when using a classic method under a laminar regime.

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.

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.

Although fiber optic distributed temperature sensing (FO-DTS) has been used in hydrology for the past 10 years to characterize groundwater–streamwater exchanges, it has not been widely applied since the entire annual hydrological cycle has rarely been considered. Properly distinguishing between diffuse and intermittent groundwater inflows requires longer periods (e.g., a few months, 1 year) since punctual changes can be lost over shorter periods. In this study, we collected a large amount of data over a one-year period using a 614 m long cable placed in a stream. We used a framework based on a set of hypotheses approach using thermal contrast between stream temperature and the atmosphere. For each subreach, thermal contrast was normalized using reference points assumed to lie outside of groundwater influence. The concepts and relations developed in this study provide a useful and simple methodology to analyze a large database of stream temperature at high spatial and temporal resolution over a one-year period using FO-DTS. Thus, the study highlighted the importance of streambed topography, since riffles and perched reaches had many fewer inflows than pools. Additionally, the spatial extent of groundwater inflows increased at some locations during high flow. The results were compared to the usual standard deviation of stream temperature calculated over an entire year. The two methods located the same inflows but differed in the mapping of their spatial extent. The temperatures obtained from FO-DTS open perspectives to understand spatial and temporal changes in interactions between groundwater and surface water.