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Microstructure observations and mixing parameterizations along an Atlantic transect in very weak turbulence
No full textMicrostructure measurements of shear and temperature can be used to calculate ocean turbulent dissipation rates and diffusivities. Here microstructure observations are taken along an transect in the North Atlantic, that includes observations of very weak deep ocean turbulence. In this paper we show the necessity of using the thermistor probes, instead of the more common shear probes, to calculate dissipation rates when they are smaller than W kg−1. Profiles of combined dissipation rates from the shear and thermistor probes are then compared to the finescale strain parameterization and Thorpe sorting method. Based on this comparison, recommendations and restrictions are suggested for applying both parameterizations in a weakly turbulent environment. The results indicate that temperature-based strain provides improved estimates of dissipation rates in the deep ocean where density gradients are small, while density-based strain provides better results otherwise. We find that Thorpe based estimates are very accurate when pre-existing knowledge of the turbulent kinetic energy dissipation rate ε is used. When this knowledge is not available, using climatological mean estimates of ε can allow for more detailed estimates of dissipation by applying the Thorpe resorting method. Finally, we employ the triple decomposition framework to get more insights in the relative roles of dianeutral and isoneutral mixing processes, and use this to calculate the dianeutral and isoneutral diffusivities. It turns out that the triple decomposition is generally not a good predictor of the isoneutral diffusivity. Overall, this paper has assessed the potential of direct observations and parameterizations of dissipation and showed that dissipation rates can be estimated quite well within a factor 5 between different methods, but it becomes difficult to achieve higher accuracy.</span
Contrasts in the marine inorganic carbon chemistry of the Benguela Upwelling System since the Last Glacial Maximum
No full textUpwelling regions are dynamic systems where relatively cold, nutrient-, and CO2-rich waters reach to the surface from the deep. CO2 sink or source properties of these regions are dependent not only on the dissolved inorganic carbon content of the upwelled waters, but also on the efficiency of the biological carbon pump which constrains the drawdown of atmospheric CO2 in the surface waters. The Benguela Upwelling System (BUS) is a major upwelling region with one of the most productive marine ecosystems today. However, contrasting signals reported on the variation in upwelling intensities based on, for instance, foraminiferal and radiolarian indices over the last glacial cycle indicate that a complete understanding of (local) changes is currently lacking. To reconstruct changes in the CO2 history of the northern Benguela upwelling region over the last 27 kyr, we used a box core (64PE450-BC6) and piston core (64PE450-PC8) from the Walvis Ridge. Here, we apply various temperature and pCO2 proxies, representing both surface (U and δ13C of alkenones) and subsurface (Mg Ca and δ11B in planktonic foraminiferal shells) processes. Reconstructed pCO2 records suggest enhanced storage of carbon at depth during the Last Glacial Maximum (LGM). The offset between δ13C of planktonic (high δ13C) and benthic foraminifera (low δ13C) suggests evidence of a more efficient biological carbon pump, potentially fueled by remote and local iron supply through eolian transport and dissolution in the shelf regions, effectively preventing release of the stored glacial CO2.</span
Benthic invertebrates in the Wadden Sea form a stable community characterized by facilitating relationships
No full textEntire tidal food webs rely on the presence and productivity of benthic invertebrates. These invertebrates recycle nutrients, decompose organic matter, and function as food for myriad species at higher trophic levels. The interactions between benthic invertebrate species also play an important role in shaping the ecological functioning of these ecosystems. Here, we used a deep-learning species distribution model to characterize the interspecific interactions occurring in an intertidal benthic invertebrate community while accounting for abiotic factors. The data include >30,000 samples collected between 2008 and 2020, over a spatial grid of more than 2400 km2 in the Wadden Sea. The benthic invertebrates in the Wadden Sea were shown to form a stable community where species engage in relatively few strong interactions in a larger network of weak interactions. This corroborates classical theory on stability–connectivity relations. We provide a stepping stone for species-specific analysis by showing that the numbers of interaction link to functional species traits. However, the biological interpretation of these links remains open. We conclude that rather than posing a catch-all solution for improving our understanding of benthic invertebrate communities, our approach provides a baseline interaction mapping tool and starting point for more targeted experiments to elucidate underlying mechanisms.</span
Degradation and habitat-dependent colonization of plastics in Caribbean coastal waters and sediments by bacterial communities
No full textThis study investigates microbial colonization of plastics in Caribbean coastal waters. We deployed five polymer types, on set with a mild UV-pretreatment and one set without UV-pretreatment, for 4.5 months in the water column and sediment at two locations, and analyzed the epiplastic biofilms with 16S rRNA gene sequencing. While a significant influence of location and habitat was apparent, we could not detect notable effects related to polymer type or UV-pretreatment on microbial community composition. Nevertheless, potential plastic and hydrocarbon degraders constituted up to 43 % of sequences from epiplastic biofilms, suggesting an affinity for plastic. Indeed, utilizing 13C-labeled PE and PP, we determined incorporation of plastic-derived carbon into microbial biomass. We measured isotopically labeled fatty acids in incubations with 13C labeled plastics in both water column and sediments, whether virgin or pre-weathered with UV light. The apparent biodegradation of plastic in benthic habitats challenges the perception of marine sediments as a final sink for polyolefins
Realising the potential of interoperable data products to improve the outlook for marine biodiversity: Lessons from the European marine observation and data network
No full textPolicies responding to increasing pressures on marine biodiversity require adequate data to support their implementation and to monitor their effectiveness. Marine biodiversity science has made significant progress generating and aggregating biodiversity data, however turning this into evidence-based knowledge useful to decision makers remains a significant challenge. ‘Data products’ provide processed data to address specific user needs, and are widely used in climate science, geosciences, and remote sensing, but the development of biodiversity data products is challenging due to the complexity of biological systems and of the data derived from surveys designed without explicit biodiversity policy or management guidance. A wide range of potential products of interest may include distributional data for thousands of individual taxa, requiring advanced statistical methods to model patterns in biodiversity using heterogeneous and sparse source data with biases in spatial, temporal, and taxonomic coverage. We illustrate these challenges using data products created within the Biology thematic lot of the European Marine Observation and Data Network (EMODnet), and we propose that the EMODnet Biology approach, which involves providing clear and open documentation of the product creation process with a strong emphasis on the computational tools needed to link source data to higher-level data products, can productively support decision making at the European scale. Furthermore, this approach provides part of the essential infrastructure required to maximise the financial benefits of FAIR data, and data products play a key role in empowering users to make maximum use of existing biodiversity data to help to understand and manage our seas
A macrozoobenthic data set of the Black Sea northwestern shelf
No full textBenthic ecological data are crucial to study and manage ecosystems. On the one hand, abiotic and species data provide complementary information to identify habitats. On the other hand, trait data, describing taxon characteristics, are required to predict anthropogenic impacts on marine ecosystems. Indeed, species traits are now widely used to understand natural selection in communities or to highlight ecosystem functions. While trait data are in growing demand, compiling them is challenging, time-consuming and there are no properly established procedures for major marine ecosystems. Here, we share a data set comprising macrozoobenthic occurrences for 215 taxa over the Black Sea northwestern shelf, between 1995 and 2017, and 27 traits documented for 127 taxa that related to life cycle and ecosystem function. In addition, we provide an abiotic data set of physical and chemical variables generated by a model or compiled from in-situ data. This data set aims to fill the functional knowledge gap in the Black Sea and offers research opportunities to future studies covering ecosystem functions, biodiversity conservation, and management
High‐Resolution Sensors Reveal Nitrate and Dissolved Silica Dynamics in an Arctic Fjord
No full textSubglacial weathering releases biologically important nutrients into meltwaters that have the potential to influence downstream ecosystems. There is a need to understand how accelerated glacial retreat could impact biogeochemical cycling in coastal regions in the near future. However, fjords—important gateways connecting the Greenland ice sheet and coastal oceans—are highly heterogeneous environments both in space and time. Here, we investigate temporal variability of nutrient dynamics in a glacier-fed fjord (Nuup Kangerlua, Greenland) using a high resolution record of nitrate + nitrite (∑NOx) and dissolved silica (DSi), coupled with temperature and salinity, using submersible in situ sensors. During a 3-month monitoring period (14th June to 13 September 2019), ∑NOx varied between 0.05 and 10.07 μM (±0.2 μM), whereas DSi varied between 0.35 and 14.98 μM (±0.5 μM). Both nutrients started low (following the spring bloom) and increased throughout the monitoring period. Several large peaks in both nutrients were observed, and these can largely be associated with meltwater runoff and upwelling events. Peaks in DSi were likely the direct result of glacial meltwater pulses, whereas elevated ∑NOx concentrations in the fjord system were likely the result of meltwater-induced upwelling of marine sources. However, we did not observe a case of simple conservative mixing, suggesting that other processes in the fjord system (e.g., differential biological uptake and remineralization) may decouple the relationship between the two nutrients. This data set was used to investigate the biogeochemical impact of changes in glacier meltwater input throughout the melt season.</span
Assisting recolonization of near‐shore seagrasses
No full textNatural recolonization of seagrasses may take decades after disturbances and is particularly challenging in near-shore environments, where sediment mobility inhibits seagrass establishment. We assisted recolonization in fifteen 4x10 m unvegetated experimental plots in a Mexican Caribbean near-shore fringe where the seagrasses had died due to massive inundations of holopelagic Sargassum species, and where a containment barrier was placed to avoid future inundations. The applied treatments were: artificial substrate (AS: 90 belowground, artificial, biodegradable, 15x15 cm-sized substrates, cut from a 0.91 x 0.45m Biodegradable EcoSystem Engineering sheet), transplant (TR: 90 cores, 4.5 cm diameter, with Halodule wrightii), and control (C: no manipulation), each with five replicates. After 6 months, 63% of H. wrightii transplants survived, presenting mean rhizome extension of 7.6 cm, and H. wrightii from natural surrounding patches started to colonize the plots. After approximately 8 months, AS and TR plots already showed higher light conditions and lower fluctuations in sediment levels than the controls. After 14 months, the AS and TR plots reached higher mean (± SE) density (respectively, 4024 ± 620 and 3484 ± 360 shoots/m2) and cover (60.3 ± 3.85 and 53.7 ± 2.84 %), compared to the control plots (2043 ± 381 shoots/m2, 35.3 ± 5.7 % cover). Higher density of H. wrightii likely favored the natural establishment of Thalassia testudinum seedlings, with an average of 2.07 (± 0.15) and 1.87 (± 0.18) seedlings in AS and TR plots, respectively, compared to 0.48 (± 0.23) in the controls. Both techniques accelerated seagrass recolonization, but artificial substrates required less effort and avoided harvesting of donor meadows.</span
Measurement error in remotely sensed fractional snow cover datasets: implications for ecological research
No full textSnow cover and snow melt patterns are important features of the Arctic environment, with wide-ranging repercussions for ecology. Datasets based on satellite imaging—often freely available—provide a powerful means for estimating snow cover. However, researchers should be aware of the possible error and bias in such datasets. Here, we quantify measurement error in commonly used data on snow cover, and demonstrate how biases have the potential to alter conclusions of ecological studies. We established 38 quadrats (80 m × 50 m) across a study site of Arctic tundra near Utqiaġvik, Alaska. At each quadrat, we estimated fractional snow cover (FSC) and the timing of snow melt using data from moderate resolution imaging spectroradiometer (MODIS), visible infrared imaging radiometer suite (VIIRS), and Sentinel-2 satellites. We compared satellite-based estimates with data from drone imagery to quantify measurement error and bias. We then evaluated whether the measurement error and bias alter conclusions about the relationship between the timing of snow melt and the breeding phenology of a population of pectoral sandpipers Calidris melanotos. We found that satellite datasets tended to overestimate FSC, leading to late estimates for snow melt dates. The Sentinel-2 dataset gave the most accurate results, followed by VIIRS, with MODIS giving the least accurate results. The degree of error varied substantially with the level of FSC, with biases reaching up to 60% for MODIS and VIIRS datasets at intermediate FSC values. Consequently, these datasets resulted in substantially different conclusions about how snow melt patterns were related to settlement and nesting dates of pectoral sandpipers. Our study indicates that measurement error in FSC can be large with substantial variation in the degree of error among satellite products. We show that these biases can impact conclusions of ecological studies. Therefore, ecologists should be conscious of the limitations of satellite-derived estimates of snow melt, and where possible should consult studies validating snow measurements in environments comparable to that of their study system.</span
Predicting massive floating macroalgal blooms in a regional sea
No full textIncreasingly frequent and severe floating macroalgal blooms present significant challenges to coastal and ocean environments. Here a short-term forecast system of floating macroalgal blooms was developed to predict the physical-biogeochemical environment and macroalgal ecodynamic processes in a regional ocean. Predictions of macroalgal ecodynamic processes are influenced by oceanic conditions (hydrodynamics, temperature, and nutrients), as well as atmospheric conditions (wind). The system\u27s effectiveness is demonstrated by successfully hindcasting the June 2021 green tide bloom event in the Yellow Sea and using real-time satellite data to make reliable and robust continuous short-term predictions for 2022 and 2023. The prediction accuracy of coverage reaches 87.5%, and the minimum transport error of the green tide center of mass is 6.09 nautical miles over an 7-day prediction duration. Supported by regional marine physics and biogeochemistry and macroalgal physiological characteristic datasets, this system may serve as a crucial cornerstone for similar floating macroalgal disaster prevention.</span