Limnology and Oceanography: Methods最新文献

Accurate measurements of seawater carbonate chemistry are crucial for marine carbon cycle research. Certified reference materials (CRMs) are typically analyzed alongside samples to correct measurements for calibration drift. However, the COVID-19 pandemic led to a limited access to CRMs. In response to this shortage, we prepared and monitored in-house reference materials (IHRMs) for total alkalinity (TA) and dissolved inorganic carbon (DIC), over 12 and 15 months, respectively. Overall, TA was stable, but a slight increase in DIC of about 2 μmol kg⁻¹ occurred over 15 months. The increase could potentially be attributed to bacterial growth, despite mercuric chloride fixation and repeated UV exposure. It is noted that this small increase was most likely within our instrument and measurements uncertainties. Our repeated measurements also identified a few bottles that had TA or DIC concentrations 4–5 μmol kg⁻¹ higher than the rest, indicating issues during cleaning, fixation, or storage of individual bottles. This study emphasizes the importance of careful and continuous monitoring if self-prepared IHRMs are used. Given that the amount of work required is very high, IHRM preparation is only recommended when CRMs are not available.

In shallow coastal systems, sediments are exposed to dramatic and complex variability in environmental conditions that influences sediment processes on short timescales. Sediment oxygen demand (SOD), or consumption of oxygen by sediment-dwelling organisms and chemical reactions within sediments, is one such process and an important metric of aquatic ecosystem functioning and health. The most common instruments used to measure SOD in situ are batch-style benthic chambers, which generally require long measurement periods to resolve fluxes and thus do not capture the high temporal variability in SOD that can be driven by dynamic coastal processes. These techniques also preclude linking changes in SOD through time to specific features of the sediment, for example, shifts in sediment faunal activities which can vary on short time scales and can also be affected by ambient oxygen concentrations. Here we present an in situ semi-flow through instrument to repeatedly measure SOD in discrete areas of sediment. The system isolates patches of sediment in replicate benthic chambers, and measures and records oxygen decrease for a short time before refreshing the overlying water in the chamber with water from the external environment. This results in a sawtooth pattern in which each tooth is an incubation, providing an automated method to produce direct measurements of in situ SOD that can be directly linked to an area of sediment and related to rapid shifts in environmental conditions.

Biodiversity conservation and management requires surveillance that captures the full spectrum of taxa. Here, we showcase the potential for a portfolio of visual, extractive, and molecular methods for detecting previously hidden components of tropical fish biodiversity in an economically and culturally valuable marine site that spans a tropical-temperate ecotone—the Ningaloo Coast World Heritage Area. With scale and practicality in mind, we demonstrate how environmental DNA (eDNA) methods deployed in a stratified sampling design can yield a more comprehensive monitoring program for species presence than current alternatives (e.g., extractive sampling via anesthetic). eDNA from filtered water samples detected up to six times as many cryptobenthic fish species per site than samples collected with anesthetic, indicating it is a potentially powerful tool for assessing biodiversity of tropical fishes. However, there were also species that were only found when using anesthetic and the contribution of cryptobenthic species to overall diversity of the fish assemblage was unexpectedly low, suggesting not all cryptobenthic fish species have been detected with eDNA. There were also distinct differences in cryptobenthic assemblages both among sites and sample depths (2–3 m) when using eDNA from filtered water, suggesting this technique may be able to identify fine scale spatial differences in cryptobenthic fish assemblage. eDNA collected from water detects the most cryptobenthic species and is therefore an efficient tool for rapidly assessing biodiversity, but extractive techniques may still be required for biological and monitoring studies, and when combined with eDNA sampling provides the most comprehensive assessment of cryptobenthic fishes.

Lake morphometry is a driver of limnological processes, yet digitized bathymetry is lacking for most lakes. Here, we describe a method for efficiently extracting hypsography from bathymetric maps using ImageJ. To validate our method, we compared results generated from two independent users to those obtained from digital elevation models for 100 lakes. The mean absolute difference between hypsographic curves extracted using ImageJ vs. digital elevation models (DEMs) was 0.049 (95% CI 0.041–0.056) proportion of lake area, suggesting that ImageJ provides accurate hypsography. We calculated the mean absolute difference between the two users (0.016; 95% CI: 0.011–0.021), which suggests high interobserver reliability. Finally, we compared DEMs to an interpolated hypsography using only the maximum lake depth and found large differences. We apply this method to extract data for 1012 lakes. Our data and approach will be useful where bathymetric maps exist but are not digitized.

Intense biogeochemical transformations in sediments and biofilms may occur over sub-mm distances. Our current understanding of those transformations in such narrowly stratified environments has been facilitated by the introduction of microsensors. Until now most studies have been conducted using individual sensors for the various chemical species, and careful vertical alignment of the sensor tips is then essential for the meaningful interpretation of the resulting data. For instance, the determination of total dissolved sulfide (TDS) at high resolution requires perfect alignment of sensors for H₂S and pH, as the pKa for H₂S is close to ambient pH. In this study, we show how a recently developed TDS sensor and a new combined H₂S/O₂ microsensor can improve the analysis of sulfidic environments including the oxygen–sulfide interface. The TDS sensor does not require pH correction unlike the conventional H₂S sensor, and it thus eliminates the need for a simultaneous pH measurement. The combined sensor allows for perfect alignment of H₂S and O₂ micro profiles and makes it possible to not only more accurately estimate fluxes, but also to determine overlapping zones of oxygen and dissolved sulfide at very high resolution.

Robust sampling of animals is necessary for understanding ocean ecology, but evaluating the effectiveness of our samplers is a challenge. Scientific echosounders were added to two robotic platforms carrying video imaging systems: a remotely operated vehicle (ROV) and an autonomous underwater vehicle (AUV). The vehicles were used to quantitatively sample midwater life in Monterey Bay along horizontal transects at incremental depths ranging from 25 to 1000 m. The echosounders allowed the bulk behavioral responses of animals to be observed up to 200 m forward of each platform. These responses observed included no response, continual avoidance, avoidance to a fixed range resulting in a patch, and attraction. There were strong and interacting effects of depth and platform type on behavioral responses. Measurements of acoustic backscatter showed that animals responded more strongly to the AUV than the ROV. During AUV surveys, there were effects of day/night and the use of artificial illumination on animal responses. Behavioral responses to our sampling were both species- and context-dependent. These data inspired the expansion of an existing mathematical framework that formalized the processes affecting the sampling of motile ocean organisms. Originally developed for net sampling, we generalized the equations to be platform- and sensor-agnostic and incorporated animal decision-making processes to allow for behaviors consistent with the full range of responses we observed. These results and the framework can help move toward more effective sampling of motile animals in the ocean.

Sensors that use ultraviolet (UV) light absorption to measure nitrate in seawater at in situ temperatures require a correction to the calibration coefficients if the calibration and sample temperatures are not identical. This is mostly due to the bromide molecule, which absorbs more UV light as temperature increases. The current correction applied to in situ ultraviolet spectrophotometer (ISUS) and submersible ultraviolet nitrate analyzer (SUNA) nitrate sensors generally follows Sakamoto et al. (2009, Limnol. Oceanogr. Methods 7, 132–143). For waters warmer than the calibration temperature, this correction model can lead to a 1–2 μmol kg⁻¹ positive bias in nitrate concentration. Here we present an updated correction model, which reduces this small but noticeable bias by at least 50%. This improved model is based on additional laboratory data and describes the temperature correction as an exponential function of wavelength and temperature difference from the calibration temperature. It is a better fit to the experimental data than the current model and the improvement is validated using two populations of nitrate profiles from Biogeochemical Argo floats navigating through tropical waters. One population is from floats equipped with ISUS sensors while the other arises from floats with SUNA sensors on board. Although this model can be applied to both ISUS and SUNA nitrate sensors, it should not be used for OPUS UV nitrate sensors at this time. This new approach is similar to that used for OPUS sensors (Nehir et al., 2021, Front. Mar. Sci. 8, 663800) with differing model coefficients. This difference suggests that there is an instrumental component to the temperature correction or that there are slight differences in experimental methodologies.

Bryozoans are becoming an increasingly popular study system in macroevolutionary, ecological, and paleobiological research. Members of this colonial invertebrate phylum display an exceptional degree of division of labor in the form of specialized modules, which allows for the inference of individual allocation of resources to reproduction, defense, and growth using simple morphometric tools. However, morphometric characterizations of bryozoans are notoriously labored. Here, we introduce DeepBryo, a web application for deep-learning-based morphometric characterization of cheilostome bryozoans. DeepBryo is capable of detecting objects belonging to six classes and outputting 14 morphological shape measurements for each object. The users can visualize the predictions, check for errors, and directly filter model outputs on the web browser. DeepBryo was trained and validated on a total of 72,412 structures in six different object classes from images of 109 different families of cheilostome bryozoans. The model shows high (> 0.8) recall and precision for zooid-level structures. Its misclassification rate is low (~ 4%) and largely concentrated in two object classes. The model's estimated structure-level area, height, and width measurements are statistically indistinguishable from those obtained via manual annotation. DeepBryo reduces the person-hours required for characterizing individual colonies to less than 1% of the time required for manual annotation. Our results indicate that DeepBryo enables cost-, labor,- and time-efficient morphometric characterization of cheilostome bryozoans. DeepBryo can greatly increase the scale of macroevolutionary, ecological, taxonomic, and paleobiological analyses, as well as the accessibility of deep-learning tools for this emerging model system.

A highly specific electrochemical reduction method has been developed that enables the trace level measurement of dimethyl sulfoxide (DMSO) concentration in natural waters. Following the sparging of native dimethyl sulfide (DMS) from the sample, DMSO is reduced to DMS using a novel electrochemical workflow that relies upon CuSO₄ as a redox mediator. The DMS produced through DMSO reduction is collected, concentrated, and detected using a previously described Purge & Trap-Atmospheric Pressure Chemical Ionization-Tandem Mass Spectrometry (P&T-APCI-MS/MS) analytical workflow. The method provides a 0.5 pM detection limit for the analysis of DMSO in 10 mL sample volumes, with a demonstrated method precision of 5.4% for the analysis of consecutive 10 nM aqueous standards. The method selectivity for DMSO was evaluated using a range of commonly observed marine organosulfur compounds, none of which were found to interfere with the analysis at a reduction potential of 4 V. Method intercomparison confirmed that the electrochemical reduction provides results that are equivalent (at the 95% confidence level) to an established TiCl₃ reduction protocol for the analysis of both freshwater and seawater samples. Relative to established methods of DMSO reduction, the electrochemical method provides excellent selectivity and reproducibility, and offers the potential for automated, high-throughput analysis. In addition, the new electrochemical method does not require expensive, difficult to procure enzymes or hazardous, corrosive chemical reagents. Depth profile measurements of DMSO, DMS, and dimethylsulfoniopropionate (DMSP) for unfiltered seawater samples collected in Saanich Inlet, a coastal fjord in British Columbia, demonstrate the effectiveness of the DMSO reduction method in an oceanographic context.

The aquatic eddy covariance (AEC) technique is a versatile tool for understanding benthic fluxes, and calculating primary production, respiration, and net ecosystem metabolism rates of benthic communities. A limitation for researchers has been the length of deployments where the major constraints have primarily been sensor breakage and degradation over time and battery consumption. This paper evaluates the design and deployment of a long-term eddy covariance system (LECS) that was deployed in a temperate seagrass meadow for 6 months that resulted in reliable data 79% of the time. The system consisted of a fixed bottom lander that measured the AEC and a surface buoy that transmitted real time data and provided solar power. This study found a gradual reduction in sensor response time, likely due to fouling, that reduced the response time from 1 to 22 s and resulted in a normalized root square mean error of 8% when comparing the LECS with a second short-term AEC system. New spectral analysis techniques allow for these changes in sensor response time to be monitored in real time so the sensor can be replaced or cleaned as needed. This ensures future deployments will be able to collect high-quality data and allow for long-term analyses of benthic fluxes using the new technology and analyses of the presented LECS.