Sediment oxygen demand in streams : lab measurements underestimate in situ rates substantially

Global warming is expected to affect stream metabolism significantly; and higher temperatures may lead to higher respiration and thus higher risk of oxygen depletion. It is, therefore, crucial to obtain reliable data on the oxygen dynamics in the different stream compartments. Determination of sediment oxygen demand (SOD) is typically based on lab or field measurement using cores or benthic chamber in which the actual physical conditions in the streams are not possible to mimic perfectly. We compared SOD based on lab core incubations with SOD measured in situ in stream sections where the oxygen exchange between water and air was eliminated artificially. The in situ SOD increased with increasing oxygen concentrations and both the temperature and the oxygen dependency of SOD increased with increasing organic content in the surface sediment. The laboratory rates reached 17 - 83% of the rates obtained in situ. The percentages were especially low at low stream velocity, likely reflecting a pure imitation of the physical conditions near the sediment in the lab when the sediment organic content was high (at low velocity). Therefore, alternative methods, simulating the natural horizontal water flow, are needed to provide reliable information on SOD in streams.

Partitioning Inorganic Carbon Fluxes from Paired O2 - CO2 Gas Measurements in a Neotropical Headwater Stream, Costa Rica

The role of rivers and streams in the global carbon (C) cycle remains unconstrained, especially in headwater streams where CO2 evasion (FCO2) to the atmosphere is high. Stream C cycling is understudied in the tropics compared to temperate streams, and tropical streams may have among the highest FCO2 due to higher temperatures, continuous organic matter inputs, and high respiration rates both in-stream and in surrounding soils. In this paper, we present paired in-stream O2 and CO2 sensor data from a headwater stream in a lowland rainforest in Costa Rica to explore temporal variability in ecosystem processes. Further, we estimate groundwater CO2 inputs (GWCO2) from riparian well CO2 measurements and assess all fluxes to examine the relative contributions of sinks and sources of dissolved inorganic C (DIC) to a headwater stream. Paired O2 - CO2 data reveal stream CO2 supersaturation driven by groundwater CO2 inputs and large in-stream production of CO2. Areal fluxes in our study reach show FCO2 is supported by both GWCO2 inputs and in-stream metabolism and the seasonality in GWCO2 reflects the hydrology of the site. Using a mass balance approach, we show FCO2 is the dominant loss of DIC from the stream, greater than dissolved exports, and is sustained by both internal production of DIC and terrestrial inputs of DIC. Our results underscore the importance of tropical headwater streams as large contributors of greenhouse gases to the atmosphere among inland waters and show of this C derives from both in-stream and terrestrial sources.

Large spatiotemporal variability in metabolic regimes for an urban stream draining four wastewater treatment plants with implications for dissolved oxygen monitoring

Urbanization and subsequent expansion of wastewater treatment plant (WWTP) capacity has the potential to alter stream metabolic regimes, but the magnitude of this change remains unknown. Indeed, our understanding of downstream WWTP effects on stream metabolism is spatially and temporally limited, and monitoring designs with upstream-downstream comparison sites are rare. Despite this, and despite observed spatiotemporal variability in stream metabolic regimes, regulators typically use snapshot monitoring to assess ecosystem function in receiving streams, potentially leading to biased conclusions about stream health. To address these important practical issues, we assessed the spatiotemporal variability in stream metabolism at nine sites upstream and downstream of four WWTPs in a suburban stream. We used one year (2017–2018) of high-frequency dissolved oxygen (DO) data to model daily gross primary productivity (GPP) and ecosystem respiration (ER). We found that GPP was 1.7–4.0 times higher and ER was 1.2–7.2 times higher downstream of the WWTPs, especially in spring when light was not limited by canopy shading. Critically, we observed that these effects were spatially limited to the kilometer or so just downstream of the plant. These effects were also temporally limited, and metabolic rates upstream of WWTPs were not different from sites downstream of the plant after leaf-out at some sites. Across sites, regardless of their relation to WWTPs, GPP was positively correlated with potential incident light suggesting that light is the dominant control on GPP in this system. Temporal windowing of DO to proposed regulatory monitoring lengths revealed that the violation frequency of water quality criteria depended on both the monitoring interval and start date. We conclude that spatiotemporal variability in metabolism and DO are crucial considerations when developing monitoring programs to assess ecosystem function, and that evidence of WWTP effects may only arise during high light conditions and at limited scales.

The Metabolic Regimes at the Scale of an Entire Stream Network Unveiled Through Sensor Data and Machine Learning

Streams and rivers form dense networks that drain the terrestrial landscape and are relevant for biodiversity dynamics, ecosystem functioning, and transport and transformation of carbon. Yet, resolving in both space and time gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) at the scale of entire stream networks has been elusive so far. Here, combining Random Forest (RF) with time series of sensor data in 12 reach sites, we predicted annual regimes of GPP, ER, and NEP in 292 individual stream reaches and disclosed properties emerging from the network they form. We further predicted available light and thermal regimes for the entire network and expanded the library of stream metabolism predictors. We found that the annual network-scale metabolism was heterotrophic yet with a clear peak of autotrophy in spring. In agreement with the River Continuum Concept, small headwaters and larger downstream reaches contributed 16% and 60%, respectively, to the annual network-scale GPP. Our results suggest that ER rather than GPP drives the metabolic stability at the network scale, which is likely attributable to the buffering function of the streambed for ER, while GPP is more susceptible to flow-induced disturbance and fluctuations in light availability. Furthermore, we found large terrestrial subsidies fueling ER, pointing to an unexpectedly high network-scale level of heterotrophy, otherwise masked by simply considering reach-scale NEP estimations. Our machine learning approach sheds new light on the spatiotemporal dynamics of ecosystem metabolism at the network scale, which is a prerequisite to integrate aquatic and terrestrial carbon cycling at relevant scales.

Moderate increases in channel discharge are positively related to ecosystem respiration in forested Ozark streams

ABSTRACTThe natural flow regime is considered the “master variable” in lotic systems, controlling structure and function at organismal, population, community, and ecosystem levels. We sought to estimate forested headwater stream metabolism across two dominant flow regimes (Runoff and Groundwater) in northern Arkansas and evaluate potential differences in, and drivers of, gross primary production, ecosystem respiration, and net ecosystem metabolism. Flow regimes differed in intermittency, substrate heterogeneity, hyporheic connectivity, and dominant water source (subsurface runoff vs. groundwater), which we expected to result in differences in primary production and respiration. Average daily gross primary production (GPP) and ecosystem respiration (ER) estimated from field data collected from May 2015-June 2016 tended to be greater in Groundwater streams. Respiration was positively related to discharge (R2= 0.98 p< 0.0001) and net metabolism became more heterotrophic with increasing average annual discharge across sites (R2= 0.94, p= 0.0008). Characterizing ecosystem-level responses to differences in flow can reveal mechanisms governing stream metabolism and, in turn, provide information regarding trophic state and energy inputs as efforts continue to determine global trends in aquatic carbon sources and fates.

Resistance and resilience of stream metabolism to high flow disturbances

Streams are ecosystems organized by disturbance. One of the most frequent and variable disturbances in running waters is elevated flow. Yet, we still have few estimates of how ecosystem processes, such as stream metabolism (gross primary production and ecosystem respiration; GPP and ER), respond to high flow events. Furthermore, we lack a predictive frame- work for understanding controls on within-site metabolic responses to flow disturbances. Using five years of high-frequency dissolved oxygen data from an urban- and agriculturally-influenced stream, we estimated daily GPP and ER and analyzed metabolic changes across 15 isolated high flow events. Metabolism was variable from day to day, even during lower flows. Thus, we calculated metabolic resistance as the magnitude of departure from the dynamic equilibrium during antecedent lower flows and quantified resilience from the days until GPP and ER returned to the range of antecedent dynamic equilibrium. We evaluated correlations between metabolic resistance and resilience with characteristics of each high flow event, antecedent conditions, and time since last flow disturbance. ER was more resistant and resilient than GPP. GPP was typically suppressed following flow disturbances, regardless of disturbance intensity. In contrast, the ER magnitude of departure increased with disturbance intensity. Additionally, GPP was less resilient and took longer to recover (0 to > 9 days, mean = 2.2) than ER (0 to 2 days, mean = 0.6). Given the flashy nature of streams draining human-altered landscapes and the variable consequences of flow for GPP and ER, testing how ecosystem processes respond to flow disturbances is essential to an integrative understanding of ecosystem function.