High Temporal Resolution Measurements Research Articles

Correction of Sensible Heat Flux from Flux-Gradient Method to Eddy Covariance Method Based on Multi-Layer Perceptron

Abstract. Understanding surface-atmosphere interactions is critical for environmental and meteorological studies. Sensible heat flux, a key component in this interaction, is typically measured using methods such as Eddy Covariance (EC) and Flux-Gradient (FG). The EC method, known for its high temporal resolution and direct measurement capabilities of wind speed, temperature, and humidity changes, requires the use of expensive and complex equipment, making it costly and challenging to implement. On the contrary, the FG method is more accessible and economical, relying on simpler instruments, but often lacks the precision of the EC method. To harness the benefits of both methods, this article uses the Multi-Layer Perceptron (MLP) machine learning method to enhance the accuracy of the FG method's sensible heat flux calculations. Through the MLP model, this paper aims to determine the optimal parameter settings for the specific measurement environment, thereby improving the FG methods accuracy. The data was measured from Guandu Village, Anhui Province, China. This research seeks to demonstrate that the trained MLP model can be applied to similar measurement environments, thus enhancing the FG method's applicability and precision.

Temporal variability and predictability predict alpine plant community composition and distribution patterns.

One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species-environment associations. In this study, we evaluated how two components of temporal environmental variation-variability and predictability-impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long-Term Ecological Research site, we used in situ, high-resolution temporal measurements of soil moisture and temperature from 13 locations ("nodes") distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within-day) and seasonal (2- to 4-month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.

A Highly Sensitive NiO Flexible Temperature Sensor Prepared by Low-Temperature Sintering Electrohydrodynamic Direct Writing.

Flexible temperature sensors have diverse applications and a great potential in the field of temperature monitoring, including healthcare, smart homes and the automotive industry. However, the current flexible temperature sensor preparation generally suffers from process complexity, which limits its development and application. In this paper, a nickel oxide (NiO) flexible temperature sensor based on a low-temperature sintering technology is introduced. The prepared NiO flexible temperature sensor has a high-resolution temperature measurement performance and good stability, including temperature detection over a wide temperature range of (25 to 70 °C) and a high sensitivity performance (of a maximum TCR of -5.194%°C-1 and a thermal constant of 3938 K). The rapid response time of this temperature sensor was measured to be 2 s at 27-50 °C, which ensures the accuracy and reliability of the measurement. The NiO flexible temperature sensor prepared by electrohydrodynamic direct writing has a stable performance and good flexibility in complex environments. The temperature sensor can be used to monitor the temperature status of the equipment and prevent failure or damage caused by overheating.

Quantitative Optical Imaging of Oxygen in Brain Vasculature.

The intimate relationship between neuronal activity and cerebral oxygenation underpins fundamental brain functions like cognition, sensation, and motor control. Optical imaging offers a noninvasive approach to assess brain oxygenation and often serves as an indirect proxy for neuronal activity. However, deciphering neurovascular coupling─the intricate interplay between neuronal activity, blood flow, and oxygen delivery─necessitates independent, high spatial resolution, and high temporal resolution measurements of both microvasculature oxygenation and neuronal activation. This Perspective examines the established optical techniques employed for brain oxygen imaging, specifically functional near-infrared spectroscopy, photoacoustic imaging, optical coherence tomography, and two-photon phosphorescent lifetime microscopy, highlighting their fundamental principles, strengths, and limitations. Several other emerging optical techniques are also introduced. Finally, we discuss key technological challenges and future directions for quantitative optical oxygen imaging, paving the way for a deeper understanding of oxygen metabolism in the brain.

Acoustic propagation modeling using sound velocity profiles estimated from high resolution temperature data

An accurate sound velocity profile (SVP) is an important input for underwater acoustic propagation modeling. The SVP is largely driven by the temperature of the water column, especially at shallower depths. Measuring the SVP in high spatial and temporal resolution is challenging with traditional instrumentation, however techniques exist to produce high resolution temperature measurements that can be used to derive estimates of the SVP. Fiber optic distributed temperature sensing (DTS) offers an improvement of several orders of magnitude over traditional singular point measurement devices and has the ability to measure temperature over large range and depth scales in an efficient manner. A DTS system was towed for 172 nm off the coast of New England over several days. The measured temperature data was used to estimate the SVP across the range and depth and will be compared to traditional environmental data sets, such as HYCOM. A comparison of modeled acoustic propagation using different resolution SVPs will be presented.

Temporal variability of air-water gas exchange of carbon dioxide in clam and fish aquaculture ponds

The growing trend of land-based aquaculture has heightened the significance of comprehensively assessing air-water carbon dioxide (CO2) gas exchange in these inland waters, given their potential impact on carbon neutral strategies. However, temporal variations of partial pressure of CO2 (pCO2) and CO2 flux in clam and fish aquaculture ponds were barely investigated. We assessed the water surface pCO2 in one to five months intervals by deploying a lab-made buoy in three clam ponds and three fishponds located in tropical and subtropical climates. Measurements were conducted over a 24 h period each time, spanning from April 2021 to June 2022, covering the stocking, middle, and harvesting stages of the culture cycle. Diurnal pCO2 variations were dominantly controlled by biologically driven changes in dissolved inorganic carbon and total alkalinity (~97 %), while temperature and salinity effects were minor (~3 %). Clam ponds acted as a sink of atmospheric CO2 during stocking stages and transitioned to a source during middle to harvesting stages. In contrast, fishponds acted as a source of atmospheric CO2 throughout culture cycles and CO2 flux strengthened when reaching harvesting stages. Overall, clam ponds acted as a weak sink for atmospheric CO2 (−2.8 ± 17.3 mmol m−2 d−1), whereas fishponds acted as a source (16.8 ± 21.7 mmol m−2 d−1). CO2 emission was stronger during daytime coinciding with higher windspeeds compared to nighttime in fishponds. We suggest incorporating high temporal resolution measurements to account for diurnal and culture-stage variations, enabling more accurate estimates of air-water CO2 flux in aquaculture ponds. Moreover, the findings of this study highlight the importance of feeding, aeration, and biological activities (photosynthesis, remineralization, and calcification) in controlling the air-water CO2 flux in aquaculture ponds and such information can be used in implementing better strategies to achieve carbon neutral goals.

Bedload transport fluctuations, flow conditions, and disequilibrium ratio at the Swiss Erlenbach stream: results from 27 years of high-resolution temporal measurements

Abstract. Based on measurements with the Swiss plate geophone system with a 1 min temporal resolution, bedload transport fluctuations were analysed as a function of the flow and transport conditions in the Swiss Erlenbach stream. The study confirms a finding from an earlier event-based analysis of the same bedload transport data, which showed that the disequilibrium ratio of measured to calculated transport rate (disequilibrium condition) influences the sediment transport behaviour. To analyse the transport conditions, the following elements were examined to characterise bedload transport fluctuations: (i) the autocorrelation coefficient of bedload transport rates as a function of lag time (memory effect), (ii) the critical discharge at the start and end of a transport event, (iii) the variability in the bedload transport rates, and (iv) a hysteresis index as a measure of the strength of bedload transport during the rising and falling limb of the hydrograph. This study underlines that above-average disequilibrium conditions, which are associated with a larger sediment availability on the streambed, generally have a stronger effect on subsequent transport conditions than below-average disequilibrium conditions, which are associated with comparatively less sediment availability on the streambed. The findings highlight the important roles of the sediment availability on the streambed, the disequilibrium ratio, and the hydraulic forcing in view of a better understanding of the bedload transport fluctuations in a steep mountain stream.

A ground-breaking Distributed fiber-optic Pressure Sensor for geohydraulic applications

Distributed fiber optic (DFO) technology has provided significant insight into various engineering problems by enabling high spatial resolution and accurate temperature and strain measurements. Recently, a novel distributed fiber-optic pressure sensor (DPS) has been developed at the University of Applied Sciences of Eastern Switzerland (OST), which may change the paradigm of monitoring geohydraulic structure monitoring. The key innovation of the sensor is its ability to measure hydrostatic pressure with high spatial resolution and over long distances.This study provides a comprehensive characterization of this novel sensor for two different applications. In the first application the DPS was tested in a water column to measure the vertical hydraulic pressure. In the second application the sensor is tested in a laboratory-scale dike (1:4). The DPS was embedded directly into the earth structures, providing real-time monitoring of pore pressure variations during saturation. For both applications, the DPS measurements were compared with conventional pressure and piezometer sensors, demonstrating good agreement.The results of these two applications illustrate the potential of the DPS to revolutionize geohydraulic monitoring and improve our understanding of dynamic processes in water-related structures. The implementation of this technology promises to improve the safety, predictability, and performance of critical infrastructure.

Investigating methods to quantifying uncertainty in PM2.5 emission rates from cooking by toasting bread

Exposure to airborne fine particulate matter (PM2.5) is linked to multiple negative health effects and indoor sources are important contributors to personal exposure. Cooking is a common indoor source, but reported emission rates have high variability. Methods to quantify uncertainty in PM2.5 cooking emission rates are investigated so that they can be used in probabilistic exposure models to evaluate interventions. Controlled tests were conducted to measure emission rates from the toasting of bread because it is simple and repeatable. Two methods were compared: residential kitchen field tests and large chamber tests. The theoretical peak calculation method was used to determine emission rates from time-resolved PM2.5 concentration measurements. The large chamber tests produced more consistent results than the residential field tests, with a coefficient of variance almost an order of magnitude lower due to the improved control of variables. Then, the emission rates were normally distributed with mean 0.23mg/min and standard deviation 0.067mg/min. However, this distribution may be less representative of normal behaviour. The resulting dataset can be combined with other sources to represent housing stock exposures in probabilistic models, enabling the exploration of exposure uncertainties and interventions. More generally, key recommendations when measuring PM2.5 emission rates include: high temporal resolution measurements; custom calibration factors; identifying periods for emissions, mixing, and decay; constant ventilation rates; quantifying mixing conditions; and ensuring high quality decay data.

Micro-infrared thermometry for characterizing microscale heating devices

Infrared thermometry is a non-destructive and non-contact temperature measurement technique that allows for real-time, full-field imaging. However, the limited spatial resolution of infrared detectors and the scarcity of mid- and far-infrared lenses have hindered its use in microscale applications. To address this, we introduce an infrared microscope that employs a bolometer-type infrared detector and a reflective objective lens, enabling high-resolution temperature measurements of microscale heating devices. The reflective objective lens used in the microscope introduces intensity reduction due to magnification and undesirable background radiation caused by its cavity effect. To mitigate these issues, we utilized a custom-built micro-blackbody for calibrating intensity reduction and eliminating background radiation. The proposed micro-infrared thermometry setup was characterized by MDTD and MRTD measurements, as well as an MTF curve with a pixel resolution of 6.7μm/pixel and a spatial resolution of 12.5μm. To evaluate the effectiveness of the micro-infrared thermometry, we fabricated a suspended microscale heating device that can exhibit a clear temperature distribution. The temperature distribution obtained using both the differential conversion and Fast Fourier-Transform methods to eliminate background radiation agreed well, with a maximum difference of 3.2°C and 4.1°C in the range from room temperature to 77°C and 145°C, respectively. Furthermore, we compared our experimental results with COMSOL simulations and found them to be reasonably consistent, with a maximum difference of 6.1°C and 7.0°C in the range from room temperature to 77°C and 145°C, respectively.

High-resolution temporal variations of nitrate in a high-elevation pond in alpine tundra (NW Italian Alps)

High-resolution temporal measurements in remote, high-elevation surface waters are required to better understand the dynamics of nitrate (NO3−) in response to changes in meteoclimatic conditions. This study reports on the first use of a UV–Vis submersible spectrophotometric probe (UV–Vis probe) to measure the hourly concentration of nitrate nitrogen (NO3−-N) in a pond located at 2722 m a.s.l. in an alpine tundra area (NW Italian Alps), during two snow-free seasons (July–October) in 2014 and 2015. Weekly analyses of NO3−-N and stable isotopes of water (δ18O and δ2H), together with continuous meteorological, water temperature, and turbidity measurements, were performed over the same period. The integration of in-situ UV–Vis spectrophotometric measurements with weekly samples allowed depicting the role of summer precipitation, snow melt, and temperature (air and water) in influencing NO3− dynamics. Short-duration meteorological events (e.g., summer storms and rain-on-snow events) produced rapid variations of in-pond NO3− concentration, i.e., fivefold increase in 18 h, that would not be detectable using the traditional manual collection of discrete samples. The observed seasonal variability of NO3− concentration, negatively correlated with water temperature, highlighted the important role of in-pond biological processes leading to an enhanced N uptake and to the lowest NO3− concentration in the warmer periods. The occurrence of heavy rainfall events critically altered the expected seasonal NO3− trends, increasing the N supply to the pond. The comparison of N dynamics in two years characterised by extremely different meteoclimatic conditions allowed us to obtain insights on the potential effects of climate changes (e.g., high air temperature, heavy rainfalls, and rain-on-snow events) on sensitive aquatic ecosystems as high-elevation ponds.

Properties of the mixing layer height retrieved from ceilometer measurements in Slovakia and its relationship to the air pollutant concentrations.

Mixing layer height (MLH) is an important meteorological parameter for air quality since it significantly affects ground-level pollution in the atmosphere. This study examined the properties of the MLH on diurnal and seasonal timescales over a 3-year period (2020-2022) using high temporal resolution measurements from eight Vaisala CL31 ceilometers situated around Slovakia. Hourly averaged MLH data was retrieved from the BL-View software using merged method. The highest daily maxima for the MLH occurred mostly in summer and spring, while the lowest values occurred predominantly during winter and autumn. The average MLH daily maximum in summer was 2229m, and just 859m in winter. During summer, the spatial distribution of the MLH daily maxima was more uniform compared to winter, when the air masses within the individual valleys did not mix well. Correlations between ground-level pollutant concentrations and hourly mean/daily mean MLH were analyzed. The highest correlation, R≈0.6, was found for O3. For PM10, PM2.5, and NOx, the anticorrelations with MLH were found with maximum in winter (R ≈ - 0.3 for hourly data and R ≈ - 0.5 for daily mean data) but no relation in summer. Lastly, the ceilometer MLH was compared to the radiosonde retrieved MLH for various cloud covers. Our analysis is based on an extensive set of empirical data, which can improve the accuracy and effectiveness of meteorological and atmospheric chemistry models. The findings can support air pollution forecasting and warning systems, providing valuable insights for policymakers and researchers.

Micropollutant concentration fluctuations in combined sewer overflows require short sampling intervals

Combined sewer overflows (CSOs) are an important pathway of organic micropollutants from urban areas to open water bodies. Understanding the temporal dynamics of these micropollutants during overflow events is crucial for applying appropriate sampling methods and implementing effective management strategies. Yet, little is known about the dynamics of micropollutants in CSOs, because most studies report concentrations from single grab samples or event mean concentrations (EMCs). With unique high temporal resolution measurements (3 min), we show the real dynamics of polar organic micropollutants in CSOs of one small (2,700 people: P) and one large (159,000 P) urban catchment, for two micropollutant categories: (i) 33 micropollutants in municipal wastewater and (ii) 13 micropollutants from urban surface runoff. The concentration dynamics depend on the substance source and the catchment size. Indoor substances such as pharmaceuticals show high temporal dynamics with changes of 1 to 2 orders of magnitude within 9 min in the CSO of the small catchment. In contrast, outdoor substances at the small catchment and all substances at the large catchment display considerably lower variation. We tested various time-proportional sampling strategies to assess the range of error when estimating EMCs. We recommend an interval of 3 min to capture the dynamics of indoor substances in CSOs from small catchments. The results highlight that both future monitoring campaigns and the planning and management of urban wet-weather treatment systems will benefit from high temporal sampling resolutions, not only to understand dynamics but also to minimize errors of estimated EMCs.

Saline bolus for negative contrast perfusion imaging in magnetic particle imaging.

Objective.Magnetic particle imaging (MPI) is capable of high temporal resolution measurements of the spatial distribution of magnetic nanoparticles and therefore well suited for perfusion imaging, which is an important tool in medical diagnosis. Perfusion imaging in MPI usually requires a fresh bolus of tracer material to capture the key signal dynamics. Here, we propose a method to decouple the imaging sequence from the injection of additional tracer material, without further increasing the administered iron dose in the body with each image.Approach.A bolus of physiological saline solution without any particles (negative contrast) diminishes the steady-state concentration of a long-circulating tracer during passage. This depression in the measured concentration contributes to the required contrast dynamics. The presence of a long-circulating tracer is therefore a prerequisite to obtain the negative contrast. As a quantitative tracer based imaging method, the signal is linear in the tracer concentration for any location that contains nanoparticles and zero in the surrounding tissue which does not provide any intrinsic signal. After tracer injection, the concentration over time (positive contrast) can be utilized to calculate dynamic diagnostic parameters like perfusion parameters in vessels and organs. Every acquired perfusion image thus requires a new bolus of tracer with a sufficiently large iron dose to be visible above the background.Main results.Perfusion parameters are calculated based on the time response of the proposed negative bolus and compared to a positive bolus. Results from phantom experiments show that normalized signals from positive and negative boli are concurrent and deviations of calculated perfusion maps are low.Significance.Our method opens up the possibility to increase the total monitoring time of a future patient by utilizing a positive-negative contrast sequence, while minimizing the iron dose per acquired image.

In vivo brain temperature mapping using polymer optical fiber Bragg grating sensors.

Variation of the brain temperature is strongly affected by blood flow, oxygen supply, and neural cell metabolism. Localized monitoring of the brain temperature is one of the most effective ways to correlate brain functions and diseases such as stroke, epilepsy, and mood disorders. While polymer optical fibers (POFs) are considered ideal candidates for temperature sensing in the brain, they have never been used so far in vivo. Here, we developed for the first, to the best of our knowledge, time an implantable probe based on a microstructured polymer optical fiber Bragg grating (FBG) sensor for intracranial brain temperature mapping. The temperature at different depths of the brain (starting from the cerebral cortex) and the correlation between the brain and body core temperature of a rat were recorded with a sensitivity of 33 pm/°C and accuracy <0.2°C. Our in vivo experimental results suggest that the proposed device can achieve real-time and high-resolution local temperature measurement in the brain, as well as being integrated with existing neural interfaces.

Hydrosedimentary behavior of a field combining surface drains and tile drains

In agricultural fields, soil erosion is usually associated to surface runoff. However, in drained fields, tile drains are additional pathways for soil particles. Few studies have quantified erosion in drained fields and they mainly focused on tile drained fields, without considering fields combining surface and tile drainage. These studies show high inter-site and inter-annual variabilities that highlight the need for more annual quantifications of erosion in drained fields. Consequently, it is still difficult to quantify the relative importance of the factors affecting soil erosion in drained fields. In addition to a comprehensive review of the existing studies of erosion through drainage, this study aims at quantifying surface and subsurface erosion in a 5 ha cultivated field combining surface and tile drainage. Suspended sediments (SS) and water fluxes have been monitored during two years (2019–2020 and 2020–2021) at a high temporal resolution (1 min), both at the outlet of the tile drain network and at the outlet of the surface drainage rill. SS yield was 0.49 t ha−1 and 1.08 t ha−1 in 2019–2020 and 2020–2021, respectively. During 2019–2020 and 2020–2021, tile drainage contribution to the total runoff was 46% and 21%, respectively and its contribution to SS yield was 9% and 11%, respectively. High temporal resolution measurements of runoff and SS concentrations showed the suspended sediment concentration in the surface drain runoff only increase by 17% from the first to the second study year. Conversely, for tile drainage, average suspended sediment concentrations increased by 260%. These variations and the increase of surface runoff rate suggest a shift in water and sediment connectivity at the field scale. Cropping practices could have generated a slumping of the soil surface during the second year and, at the same time, the development of a macropore network in the subsoil. Cropping practices induced changes of surface horizon characteristics and their impact on the hydrosedimentary behavior of drained soils need to be further studied. This study confirms previous results concerning the temporal dynamics of SS exports in a drained context under temperate climate and adds a new quantification of hydrosedimentary fluxes in a surface and tile drained field separating surface drains and tile drains contributions.

Tactile Sensor Structure Optimized for Sliding Motion With High Resolution Recording of Surface Topography

The demand for tactile devices with human-like exquisiteness has recently been increasing in various fields. Among the various parameters that humans feel through the tactile system, temperature and surface topography are the most important parameters to achieve artificial tactile devices with human level precision. Here, we present a new tactile sensor with high resolution surface topography recording and temperature measurement. Our tactile sensor was designed to have a surface topography sensing part driven by P(VDF-TrFE) and a thermistor part for temperature sensing. Even though the sensor touched the same temperature object, the sliding condition showed different resistance change values. Therefore, the correlation factors of the sliding velocity to temperature were defined with a simple relation function. To achieve high resolution recording, ‘zig-zag’ arrayed tactile sensor can overcome the limitations of simple matrix cell design. The design eliminates empty spaces between sensor cells. By using these systems, a resolution of ~500μm to x-direction was achieved. This tactile sensor has linear sensitivity to pressure with a superior response time of 10ms for dynamic sensing. By integrating the dynamic piezoelectric signals during the sliding motion, we can reconstruct the surface topography of various objects.

High temporal resolution measurement of the curing process of nanometer-thick photocurable liquid films using the fiber wobbling method

We established a method for assessing the curing process of a nanometer-thick photocurable liquid film by monitoring changes in shear viscoelasticity at a high temporal resolution. The originally developed nano-rheometry method (the fiber wobbling method) was applied for the viscoelastic measurements. We succeeded in measuring the curing process of a 100 nm thick liquid film with a time resolution of 1 ms. The experimental results suggested that the confinement effect in the nanogap suppresses liquid curing. Thus, the proposed evaluation method can be used for developing nanoimprint lithography and high-precision 3D printing.

Liquid-Core-Microtubule-Enhanced Laser Sensor for High-Resolution Temperature Measurement

We present a fiber laser temperature sensor based on temperature dependence whisper gallery mode-based microcavity. Three different thermo-optic coefficient liquids are injected into a thin wall thickness microtubule for different temperature sensitivity of whisper gallery mode shift. The sensor temperature sensitivity increases with the absolute value of the liquid core thermo-optic coefficient. The theoretical model of whisper gallery mode temperature response is analyzed. A liquid core microtubule is inserted into the erbium-doped fiber ring laser cavity as the optical filter and sensing unit simultaneously, so the lasing wavelength can be used to detect the temperature change of the medium. Due to the narrow spectral width of sensing laser, a high sensing resolution system is experimentally confirmed. With the combination of liquid core to increase the sensitivity and fiber ring laser cavity to increase sensing resolution, the high sensitivity 112.8 pm/°C of sensing system is demonstrated and the thermal resolution is 8.16 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> °C.

Direct and indirect effects of salinisation on riverine biota: a case study from river Wipper, Germany

Salinisation has direct and detrimental physiological effects on freshwater organisms, yet little is known about its indirect effects. Here, we present a study that investigated the primary and secondary effects of salinisation on aquatic macroinvertebrates. We analysed macroinvertebrate samples from nine sites in river Wipper, Germany against nine stressor variables (water quality, salinisation, hydromorphological degradation). A Principal Component Analysis showed water quality deterioration and physical habitat degradation to constitute the main stressor gradients. Two macroinvertebrate community metrics (index of general degradation and percent Ephemeroptera-Plecoptera-Trichoptera specimens) revealed strong and significant positive correlations with water quality, but only weak and insignificant positive correlations with hydromorphological quality. High-resolution temporal measurements revealed notable oxygen deficits at a salinised and macrophyte-rich site that was dominated by the salt-tolerant macrophyte species Stuckenia [Potamogeton] pectinata (L.) Börner. At the site, oxygen levels frequently dropped below 6 mg/L during nighttime, suggesting an interaction of osmoregulatory stress (through salinisation) and respiratory stress (through plant mitochondrial respiration) that is caused by the mass development of a salt-tolerant macrophyte species. This biologically driven interaction of direct and indirect salinisation effects adds another level of complexity to the influence of multiple stressors in lotic systems and requires consideration in river management and restoration.