Estuary-ocean connectivity: fast physics, slow biology.

Estuaries are connected to both land and ocean so their physical, chemical, and biological dynamics are influenced by climate patterns over watersheds and ocean basins. We explored climate-driven oceanic variability as a source of estuarine variability by comparing monthly time series of temperature and chlorophyll-a inside San Francisco Bay with those in adjacent shelf waters of the California Current System (CCS) that are strongly responsive to wind-driven upwelling. Monthly temperature fluctuations inside and outside the Bay were synchronous, but their correlations weakened with distance from the ocean. These results illustrate how variability of coastal water temperature (and associated properties such as nitrate and oxygen) propagates into estuaries through fast water exchanges that dissipate along the estuary. Unexpectedly, there was no correlation between monthly chlorophyll-a variability inside and outside the Bay. However, at the annual scale Bay chlorophyll-a was significantly correlated with the Spring Transition Index (STI) that sets biological production supporting fish recruitment in the CCS. Wind forcing of the CCS shifted in the late 1990s when the STI advanced 40 days. This shift was followed, with lags of 1-3 years, by 3- to 19-fold increased abundances of five ocean-produced demersal fish and crustaceans and 2.5-fold increase of summer chlorophyll-a in the Bay. These changes reflect a slow biological process of estuary-ocean connectivity operating through the immigration of fish and crustaceans that prey on bivalves, reduce their grazing pressure, and allow phytoplankton biomass to build. We identified clear signals of climate-mediated oceanic variability in this estuary and discovered that the response patterns vary with the process of connectivity and the timescale of ocean variability. This result has important implications for managing nutrient inputs to estuaries connected to upwelling systems, and for assessing their responses to changing patterns of upwelling timing and intensity as the planet continues to warm.

Benthic nitrite exchanges in the Seine River (France): An early diagenetic modeling analysis.

Nitrite is a toxic intermediate compound in the nitrogen (N) cycle. Elevated concentrations of nitrite have been observed in the Seine River, raising questions about its sources and fate. Here, we assess the role of bottom sediments as potential sources or sinks of nitrite along the river continuum. Sediment cores were collected from two depocenters, one located upstream, the other downstream, from the largest wastewater treatment plant (WWTP) servicing the conurbation of Paris. Pore water profiles of oxygen, nitrate, nitrite and ammonium were measured. Ammonium, nitrate and nitrite fluxes across the sediment-water interface (SWI) were determined in separate core incubation experiments. The data were interpreted with a one-dimensional, multi-component reactive transport model, which accounts for the production and consumption of nitrite through nitrification, denitrification, anammox and dissimilatory nitrate reduction to ammonium (DNRA). In all core incubation experiments, nitrate uptake by the sediments was observed, indicative of high rates of denitrification. In contrast, for both sampling locations, the sediments in cores collected in August 2012 acted as sinks for nitrite, but those collected in October 2013 released nitrite to the overlying water. The model results suggest that the first step of nitrification generated most pore water nitrite at the two locations. While nitrification was also the main pathway consuming nitrite in the sediments upstream of the WWTP, anammox dominated nitrite removal at the downstream site. Sensitivity analyses indicated that the magnitude and direction of the benthic nitrite fluxes most strongly depend on bottom water oxygenation and the deposition flux of labile organic matter.

Modelling the fate of nitrite in an urbanized river using experimentally obtained nitrifier growth parameters.

Maintaining low nitrite concentrations in aquatic systems is a major issue for stakeholders due to nitrite's high toxicity for living species. This study reports on a cost-effective and realistic approach to study nitrite dynamics and improve its modelling in human-impacted river systems. The implementation of different nitrifying biomasses to model riverine communities and waste water treatment plant (WWTP)-related communities enabled us to assess the impact of a major WWTP effluent on in-river nitrification dynamics. The optimal kinetic parameters and biomasses of the different nitrifying communities were determined and validated by coupling laboratory experiments and modelling. This approach was carried out in the Seine River, as an example of a large human-impacted river with high nitrite concentrations. The simulation of nitrite fate was performed at a high spatial and temporal resolution (Δt = 10 min, dx¯ = 500 m) including water and sediment layers along a 220 km stretch of the Seine River for a 6-year period (2007-2012). The model outputs were in good agreement with the peak of nitrite downstream the WWTP as well as its slow decrease towards the estuary. Nitrite persistence between the WWTP and the estuary was mostly explained by similar production and consumption rates of nitrite in both water and sediment layers. The sediment layer constituted a significant source of nitrite, especially during high river discharges (0.1-0.4 mgN h(-1) m(-2)). This points out how essential it is to represent the benthic layer in river water quality models, since it can constitute a source of nitrite to the water-column. As a consequence of anthropogenic emissions and in-river processes, nitrite fluxes to the estuary were significant and varied from 4.1 to 5.5 TN d(-1) in low and high water discharge conditions, respectively, over the 2007-2012 period. This study provides a methodology that can be applied to any anthropized river to realistically parametrize autochthonous and WWTP-related nitrifier communities and simulate nitrite dynamics. Based on simulation analysis, it is shown that high spatio-temporal resolution hydro-ecological models are efficient to 1) estimate water quality criteria and 2) forecast the effect of future management strategies. Process-based simulations constitute essential tools to complete our understanding of nutrient cycling, and to decrease monitoring costs in the context of water quality and eutrophication management in river ecosystems.