Aquatic Eddy Correlation: Quantifying the Artificial Flux Caused by Stirring-Sensitive O2 Sensors

In the last decade, the aquatic eddy correlation (EC) technique has proven to be a powerful approach for non-invasive measurements of oxygen fluxes across the sediment water interface. Fundamental to the EC approach is the correlation of turbulent velocity and oxygen concentration fluctuations measured with high frequencies in the same sampling volume. Oxygen concentrations are commonly measured with fast responding electrochemical microsensors. However, due to their own oxygen consumption, electrochemical microsensors are sensitive to changes of the diffusive boundary layer surrounding the probe and thus to changes in the ambient flow velocity. The so-called stirring sensitivity of microsensors constitutes an inherent correlation of flow velocity and oxygen sensing and thus an artificial flux which can confound the benthic flux determination. To assess the artificial flux we measured the correlation between the turbulent flow velocity and the signal of oxygen microsensors in a sealed annular flume without any oxygen sinks and sources. Experiments revealed significant correlations, even for sensors designed to have low stirring sensitivities of ~0.7%. The artificial fluxes depended on ambient flow conditions and, counter intuitively, increased at higher velocities because of the nonlinear contribution of turbulent velocity fluctuations. The measured artificial fluxes ranged from 2-70 mmol m(-2) d(-1) for weak and very strong turbulent flow, respectively. Further, the stirring sensitivity depended on the sensor orientation towards the flow. For a sensor orientation typically used in field studies, the artificial flux could be predicted using a simplified mathematical model. Optical microsensors (optodes) that should not exhibit a stirring sensitivity were tested in parallel and did not show any significant correlation between O2 signals and turbulent flow. In conclusion, EC data obtained with electrochemical sensors can be affected by artificial flux and we recommend using optical microsensors in future EC-studies

Assessing the importance of a self-generated detachment process in river biofilm models

1. Epilithic biofilm biomass was measured for 14 months in two sites, located up- and downstream of the city of Toulouse in the Garonne River (south-west France). Periodical sampling provided a biomass data set to compare with simulations from the model of Uehlinger, Bürher and Reichert (1996: Freshwater Biology, 36, 249–263.), in order to evaluate the impact of hydraulic disturbance. 2. Despite differences in application conditions (e.g. river size, discharge, frequency of disturbance), the base equation satisfactorily predicted biomass between low and high water periods of the year, suggesting that the flood disturbance regime may be considered a universal mechanism controlling periphyton biomass. 3. However modelling gave no agreement with biomass dynamics during the 7-month long low water period that the river experienced. The influence of other biomass-regulating factors (temperature, light and soluble reactive phosphorus) on temporal biomass dynamics was weak. 4. Implementing a supplementary mechanism corresponding to a temperature-dependent self-generated loss because of heterotrophic processes allowed us to accurately reproduce the observed pattern: a succession of two peaks. This case study suggests that during typical summer low water periods (flow stability and favourable temperature) river biofilm modelling requires self-generated detachment to be considered

Two-Step Wind Power Prediction Approach With Improved Complementary Ensemble Empirical Mode Decomposition and Reinforcement Learning

The strong stochastic nature of wind power generation makes it extremely challenging to accurately predict and support the planning and operation of modern power systems with significant penetration of renewable energy. This article proposes a two-step wind power prediction method, which consists of two phases: long time-scale coarse prediction and short time-scale fine correction. In the long time-scale phase, a complementary ensemble empirical mode decomposition-based sigma point Kalman filter approach is proposed to coarsely predict wind power merely with historical data. In the short time-scale phase, a deep deterministic policy gradient approach learns from real-time weather information to correct the coarse prediction result, which results in an improved prediction accuracy. A real-life case study confirms that the proposed method can properly predict wind power generation and have a better prediction accuracy than existing techniques, thus offering a viable and promising alternative for predicting wind power generation

An assessment of the precision and confidence of aquatic eddy correlation measurements

The quantification of benthic fluxes with the aquatic eddy correlation (EC) technique is based on simultaneous measurement of the current velocity and a targeted bottom water parameter (e. g., O-2, temperature). High-frequency measurements (64Hz) are performed at a single point above the seafloor using an acoustic Doppler velocimeter (ADV) and a fast-responding sensor. The advantages of aquatic EC technique are that 1) it is noninvasive, 2) it integrates fluxes over a large area, and 3) it accounts for in situ hydrodynamics. The aquatic EC has gained acceptance as a powerful technique; however, an accurate assessment of the errors introduced by the spatial alignment of velocity and water constituent measurements and by their different response times is still needed. Here, this paper discusses uncertainties and biases in the data treatment based on oxygen EC flux measurements in a large-scale flume facility with well-constrained hydrodynamics. These observations are used to review data processing procedures and to recommend improved deployment methods, thus improving the precision, reliability, and confidence of EC measurements. Specifically, this study demonstrates that 1) the alignment of the time series based on maximum cross correlation improved the precision of EC flux estimations; 2) an oxygen sensor with a response time of <0.4 s facilitates accurate EC fluxes estimates in turbulence regimes corresponding to horizontal velocities <11 cm s(-1); and 3) the smallest possible distance (<1 cm) between the oxygen sensor and the ADV's sampling volume is important for accurate EC flux estimates, especially when the flow direction is perpendicular to the sensor's orientation

The Bits of Silence : Redundant Traffic in VoIP

Human conversation is characterized by brief pauses and so-called turn-taking behavior between the speakers. In the context of VoIP, this means that there are frequent periods where the microphone captures only background noise – or even silence whenever the microphone is muted. The bits transmitted from such silence periods introduce overhead in terms of data usage, energy consumption, and network infrastructure costs. In this paper, we contribute by shedding light on these costs for VoIP applications. We systematically measure the performance of six popular mobile VoIP applications with controlled human conversation and acoustic setup. Our analysis demonstrates that significant savings can indeed be achievable - with the best performing silence suppression technique being effective on 75% of silent pauses in the conversation in a quiet place. This results in 2-5 times data savings, and 50-90% lower energy consumption compared to the next better alternative. Even then, the effectiveness of silence suppression can be sensitive to the amount of background noise, underlying speech codec, and the device being used. The codec characteristics and performance do not depend on the network type. However, silence suppression makes VoIP traffic network friendly as much as VoLTE traffic. Our results provide new insights into VoIP performance and offer a motivation for further enhancements, such as performance-aware codec selection, that can significantly benefit a wide variety of voice assisted applications, as such intelligent home assistants and other speech codec enabled IoT devices.Peer reviewe

A review of carbon offset strategies with seaweed aquaculture – feasibility, current knowledge, and suggestions for future research. The Scottish Association for Marine Science, Oban, UK. Report prepared for the Scottish Government

In September 2022, a group of international collaborators gathered from six European countries (hereby referred to as the ‘working group’) to take part in a workshop at the Scottish Association for Marine Science (SAMS), Oban. The workshop was funded as part of Marine Scotland’s Blue Carbon International Policy Challenge (BCIPC). The main aim of the workshop was to produce a document outlining the potential for carbon offset by macroalgal aquaculture. The discussions held at the workshop focused on various concepts and hypotheses surrounding carbon drawdown by seaweed aquaculture and the potential for mitigation of atmospheric CO2. The key points of these discussions have been compiled into a policy brief which aims to highlight important areas for future research, uncertainties and challenges faced by the industry, policy makers and other stakeholders

Global estimates of the extent and production of macroalgal forests

Aim Macroalgal habitats are believed to be the most extensive and productive of all coastal vegetated ecosystems. In stark contrast to the growing attention on their contribution to carbon export and sequestration, understanding of their global extent and production is limited and these have remained poorly assessed for decades. Here we report a first data-driven assessment of the global extent and production of macroalgal habitats based on modelled and observed distributions and net primary production (NPP) across habitat types. Location Global coastal ocean. Time period Contemporary. Major taxa studied Macroalgae. Methods Here we apply a comprehensive niche model to generate an improved global map of potential macroalgal distribution, constrained by incident light on the seafloor and substrate type. We compiled areal net primary production (NPP) rates across macroalgal habitats from the literature and combined this with our estimates of the global extent of these habitats to calculate global macroalgal NPP. Results We show that macroalgal forests are a major biome with a global area of 6.06–7.22 million km2, dominated by red algae, and NPP of 1.32 Pg C/year, dominated by brown algae. Main conclusions The global macroalgal biome is comparable, in area and NPP, to the Amazon forest, but is globally distributed as a thin strip around shorelines. Macroalgae are expanding in polar, subpolar and tropical areas, where their potential extent is also largest, likely increasing the overall contribution of algal forests to global carbon sequestration

Seafloor primary production in a changing Arctic Ocean

Phytoplankton and sea ice algae are traditionally considered to be the main primary producers in the Arctic Ocean. In this Perspective, we explore the importance of benthic primary producers (BPPs) encompassing microalgae, macroalgae, and seagrasses, which represent a poorly quantified source of Arctic marine primary production. Despite scarce observations, models predict that BPPs are widespread, colonizing ~3 million km2 of the extensive Arctic coastal and shelf seas. Using a synthesis of published data and a novel model, we estimate that BPPs currently contribute ~77 Tg C y−1 of primary production to the Arctic, equivalent to ~20 to 35% of annual phytoplankton production. Macroalgae contribute ~43 Tg C y−1, seagrasses contribute ~23 Tg C y−1, and microalgae-dominated shelf habitats contribute ~11 to 16 Tg C y−1. Since 2003, the Arctic seafloor area exposed to sunlight has increased by ~47,000 km2 y−1, expanding the realm of BPPs in a warming Arctic. Increased macrophyte abundance and productivity is expected along Arctic coastlines with continued ocean warming and sea ice loss. However, microalgal benthic primary production has increased in only a few shelf regions despite substantial sea ice loss over the past 20 y, as higher solar irradiance in the ice-free ocean is counterbalanced by reduced water transparency. This suggests complex impacts of climate change on Arctic light availability and marine primary production. Despite significant knowledge gaps on Arctic BPPs, their widespread presence and obvious contribution to coastal and shelf ecosystem production call for further investigation and for their inclusion in Arctic ecosystem models and carbon budgets.publishedVersio

Light in the Polar Night

How much light isa vailable for biological processes during Polar Night? This question appears simple enough. But the reality is that conventional light sen- sors for measuring visible light (~350 to ~700 nm) have not been sensitive enough to answer it. Beyond this technical challenge, “light” is a general term that must be qualified in terms of “light climate” before it has meaning for biological systems. In this chapter, we provide an answer to the question posed above and explore aspects of light climate during Polar Night with relevance to biology, specifically, how Polar Night is defined by solar elevation, atmospheric light in Polar Night and its propaga- tion underwater, bioluminescence in Polar Night and the concept of Polar Night as a deep-sea analogue, light pollution, and future perspectives. This chapter focuses on the quantity and quality of light present during Polar Night, while subsequent chapters in this volume focus on specific biological effects of this light for algae (Chap. “Marine Micro- and Macroalgae in the Polar Night”), zooplankton (Chaps.“Zooplankton in the Polar Night” and “Biological Clocks and Rhythms in Polar Organisms”), and fish (Chap. “Fish Ecology in the Polar Night”)