Limnology and Oceanography: Methods最新文献

Marine dissolved organic carbon (DOC) is one of the largest reservoirs of fixed carbon on Earth, and its cycling contributes to ocean productivity and carbon storage. Despite its central role, efforts to characterize DOC reactivity and cycling in aquatic systems have been hampered by low recovery during isolation. The most widely applied recovery methods, solid-phase extraction and ultrafiltration, independently capture less than half of seawater DOC. Here we investigate ceramic nanofiltration as a novel method to isolate DOC from surface waters across the land-to-ocean continuum. A bench-scale prototype system employing a 200 Da pore size ceramic nanomembrane consistently retained > 82% of organic probe molecules (181–376 Da) and > 88% of bulk DOC from diverse surface waters. Salt permeation of the nanomembrane was variable (34–70%) across all surface waters, but highest in seawater (63–70%). Coastal surface seawater was size fractionated using a set of ceramic nanomembranes with pore sizes ranging from 200 to 2000 Da. Radiocarbon analysis of the size fractions revealed that an intermediate size class (i.e., 200–450 Da) is notably older than both smaller and larger size classes and bulk DOC, thereby challenging the size-reactivity continuum paradigm within low molecular weight coastal DOC (i.e., < 2000 Da). Together, these results suggest that ceramic nanofiltration may have the potential to effectively isolate DOC and remove salts, thus enabling new experimental insights into the cycling of DOC. If scaled, this technology could be applied to greatly expand our understanding of the role of DOC as a key intermediate in the ocean carbon cycle.

We evaluated the effect of in situ acidification of common estuarine macroinvertebrates from the Elbe estuary on stable isotope ratios, as the non-removal of non-dietary carbon can significantly influence aquatic food web analyses. A 10% HCl solution was used to remove inorganic carbon from crustaceans, which potentially biases the true ratio of assimilated dietary carbon. We detected significant differences in the δ¹³C values of all investigated crustaceans except for the mysid shrimp Mesopodopsis slabberi after acid treatment. On the contrary, acidification impacts on δ¹⁵N were only observed in Gammarus spp. samples. A carbonate proxy was additionally computed to evaluate the necessity of acidification because high values indicate high inorganic carbon in the tissue that may alter true δ¹³C values. Our results indicate that the necessity of acid treatment of common estuarine macroinvertebrates before stable isotope analysis depends on the species-specific carbonate content. Acid treatment is therefore not required for all species when analyzing aquatic food webs.

Characterizing the vertical structure of phytoplankton biomass is key to understanding the light, nutrient, and mixing dynamics driving lake ecosystems. In situ fluorometry is widely used in limnology to obtain chlorophyll a (Chl a) measurements as proxies for phytoplankton biomass. Unfortunately, daytime fluorometry signals are biased by non-photochemical quenching, limiting the value of these measurements. Phytoplankton utilize this quenching process to dissipate excess light energy as heat, which contaminates daytime fluorometry measurements with reductions in measured Chl a. Despite the ubiquitous impacts of non-photochemical quenching on fluorometer measurements, there is no universal correction method for inland waters. We propose a novel model for correcting non-photochemical quenching impacts in lake systems as a simple exponential function of available light in the water column. This model was developed from data collected from two lakes representing the endmembers in terms of lake productivity and clarity, thus producing a model with possible application to other systems. The study sites are ultraoligotrophic Lake Tahoe, CA-NV, and hypereutrophic Clear Lake, CA. Our proposed non-photochemical quenching correction model demonstrates good performance (R² = 0.74) when tested on an independent dataset from Lake George, NY. We applied the model to vertical data profiles from Lake Tahoe and Clear Lake to more accurately evaluate the vertical distribution of Chl a in these lakes. The results of this research have wide-reaching benefits by enabling more accurate interpretation and application of Chl a fluorescence measurements in lakes with a range of conditions.

Total alkalinity (TA) plays an important role in buffering seawater and determining how much anthropogenic carbon dioxide the oceans can absorb and mitigate the rise in atmospheric concentrations. Total alkalinity varies with location, depth, and time making it an important variable needed to quantify and monitor ocean acidification, and potentially for ocean alkalinity enhancement interventions. Currently, best practices are to use expensive high-quality borosilicate glass bottles for collecting and storing these samples. However, unlike other carbon system variables, TA is not affected by gas exchange meaning plastic bottles may be suitable for TA sample storage. Plastic bottles are lighter, cheaper, and less prone to breakage making them easier to handle and ship. Here, we test the suitability of high-density polyethylene (HDPE) for collection and long-term storage of TA samples. In two sets of experiments, it was determined that HDPE is not suitable for long-term storage of TA samples as there were large changes in TA over time and precision of duplicate samples was very poor. We hypothesize that HDPE plastic is slightly porous leading to leaching of alkalinity either into or out of the bottle over time impacting the value of the sample. Use of HDPE bottles for TA samples is not recommended for long term sample storage.

An ever-increasing number of Biogeochemical (BGC) Argo floats equipped with radiometric sensors have been deployed across the World Ocean. To date, more than 50,000 vertical profiles from 0 to at least 250 dbar of photosynthetically available radiation and downwelling irradiance at 3, narrow wavelengths have been acquired. For scientific use of radiometric data, corrections for temperature effects and sensor drift are necessary. However, these adjustments are only partially provided in delayed mode, almost a year after acquisition and distribution. This makes automatic, real-time quality control (RT-QC) data processing of BGC-Argo radiometry critically important. Nevertheless, only a range test has been applied to real-time radiometric profiles, so far. By leveraging the full dataset of multispectral radiometric measurements from various BGC-Argo platform types, we have developed a robust RT-QC protocol for processing radiometric data and profiles, aimed at identifying potential sensor malfunctions, particularly those related to temperature effects. Data quality flags are attributed to each data point by considering the expected shape of the radiometric profile associated with the solar elevation during data acquisition. For both daytime and nighttime profiles, the new protocols automatically unveil data potentially dominated by temperature effects. The proposed methodology remains resilient to sensor drift and unstable sea conditions, and it also holds promise for adaptation to data from cutting-edge hyper-spectral sensors mounted on BGC-Argo floats.

The accurate predictions on the red tide outbreaks in coastal regions can reduce their negative impacts on the marine environment and human life. Currently, the red tide prediction is generally accomplished by monitoring some related key factors, which are difficult to obtain on large spatial scales. Combining a transformer encoder with a graph convolution network (GCN), this study proposed an integrated model for red tide prediction that makes comprehensive use of the time-series hyperspectral data obtained through remote sensing methods. The topological graphs are constructed based on the multi-band spectral indices in the interconnected observation points, which are further analyzed using a GCN to obtain the topological features. After that, the temporal features of such topological graphs are extracted based on a transformer encoder, which are used for red tide prediction. The results show that the proposed model achieves reasonable predictions using the input period of 3 d before the date of red tide outbreaks, and the accuracy can reach about 92% with the input period of 5 d. The ablation experiments indicate that both the topological features obtained by the GCN and the temporal features obtained by the transformer encoder play significant roles in the prediction task of red tide outbreaks. The proposed model achieves the red tide prediction in interconnected coastal environments through the fusion of spectral-, topological-, and temporal features, and is expected to provide early alarms on red tide outbreaks for maritime and oceanic agencies.

Sedimentary archives can provide valuable insights into the study of anthropogenic impacts on marine and limnic ecosystems over centennial and millennial timescales, potentially extending the temporal breadth of observation-based biomonitoring. Sedimentary archives allow for the tracking of biodiversity changes over long time periods, potentially including periods before human-induced changes. However, evaluations of biodiversity reconstructions using sedimentary approaches through comparisons with existing observation-based biomonitoring data are limited. Here we compared sedimentary ancient DNA metabarcoding and several biomarkers with >50 years of phytoplankton biomonitoring data from the Baltic Sea. Our findings indicated that both sedimentary ancient DNA metabarcoding and biomarkers reveal historical trends in phytoplankton communities. Sedimentary ancient DNA data was strongly correlated with biomonitoring data, while biomarkers showed weaker correlations, particularly for dinoflagellates. In addition, the sedimentary ancient DNA data indicated the past prevalence of ecological communities with no present-day analogs, highlighting the challenges of using modern observational data to infer historical biodiversity trends. The study underscores the importance of validating sedimentary approaches against observation-based data and calls for further research to improve the taxonomic resolution of metabarcoding and the specificity of biomarkers. These advancements could significantly enhance our ability to reconstruct historical biodiversity trends and inform future conservation strategies.

Temporal and spatial variability in temperature are key habitat features that will determine individual, population, and community-level responses to global climate warming. Lakes and ponds exhibit thermal heterogeneity in the form of diel and seasonal fluctuations as well as vertical stratification; however, experimental studies of warming in these ecosystems have largely focused on elevated mean temperatures within thermally homogeneous settings. Thus, new tools are needed to incorporate temperature variability into aquatic mesocosm experiments. We present a design for a mesocosm array to simulate lentic environments with different magnitudes of spatial and temporal temperature variability. Each mesocosm consists of a 77-L plastic container heated by two independent band heaters, where water temperature is regulated via a programmable logic controller that receives feedback from thermocouples. We find that the controller is capable of producing high temperatures (> 35°C) and substantial thermal stratification, with low variability between replicate mesocosms. We generated a vertical temperature gradient up to 12.4°C across 54 cm of water depth and diel fluctuations up to 12.2°C in the surface layer (top 14 cm). We additionally demonstrate the utility of the mesocosm array for other common applications, including temperature ramps and real-time transformations of ambient temperature time series. The control system's ability to simultaneously regulate temporal and spatial thermal variability, while being cost-effective and requiring relatively little technical knowledge to assemble, demonstrates the utility of the array for ecological experiments that seek to investigate the impacts of climate warming on thermally variable aquatic ecosystems.

Dissolved organic matter (DOM) is a major carbon reservoir and exhibits high chemo-diversity and similarity. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) enables analysis of DOM due to its ultrahigh resolution at various field strengths. Capturing distinguishing features of DOM is especially challenging for lower resolution instruments. Here, we aim to refine resolution settings for various types of DOM. With a low-field 7 Tesla (T) FT-ICR MS, two strategies for tuning resolution were compared with free induction decay (FID) of 1–4 s: the initial mass to charge (m/z) ratio (A) and data size (B). Peak number rises then falls with data size; 16 M leads to loss of low-mass compounds (< 220 m/z). In further, the comparability of intensity-weighted average parameters was evaluated, revealing that m/z, carbon number, H/C, O/C, aromatic index, and double bond equivalent have a coefficient of variation (CV) of < 3%; in contrast, the average number of heteroatoms—P (45%), N (21%), and S (22%)—shows considerable CV (%) with resolution, varying across samples. Furthermore, the minimum required value of resolution varies across samples, ranging from > 300,000 to > 500,000: it increases from riverine water to porewater, and then to seawater DOM, typically exhibiting abundant CHO, CHOS, and CHOP, respectively. For a 7T FT-ICR MS, we propose tailored FID strategies: a 2-s medium FID (resolution > 300,000) for regular DOM, a shorter FID (~ 1 s) for small metabolites with low initial m/z (~ 50–100), and a longer FID (resolution > 500,000) for heteroatom-enriched DOM.

Turbidity, quantified in turbidity units (nephelometric or formazin), is a common and valid measure of water quality related to transparency. A transparency tube (TT) is an economical tool developed to estimate water clarity as an alternative to the Secchi disk, but it is also frequently used to estimate turbidity. Although the relationship between TT measures and turbidity is well characterized for freshwater river and lake systems, this relationship has not been tested for estuarine waters. The objective of the current study was to empirically determine the TT–turbidity relationship for estuarine waters in coastal South Carolina (SC) and compare these results with the traditional freshwater system conversions. We obtained 107 measurements of TT depth, turbidity, total suspended solids, colored dissolved organic matter absorbance, Secchi depth, and chlorophyll a at 22 estuarine locations in SC over a 1-year period. Linear regressions provide conversion equations that can be applied to SC estuarine waters. The TT–turbidity relationship for estuaries was compared with freshwater systems. Our results suggest that the slope of the relationship differs between systems (−1.11 vs. −1.41), resulting in different turbidity estimates for TT measurements for estuarine vs. inland waters. We propose a combined conversion table incorporating estuarine and freshwater (riverine and lacustrine) systems. A TT–turbidity conversion for coastal SC and similar estuarine waters significantly benefits current water quality programs and citizen science groups by producing more accurate turbidity estimates for screening and routine monitoring efforts.