Limnology and Oceanography Letters最新文献

Zooplankton-microbial interactions play crucial roles in epipelagic ecosystem functions. The distinct west-to-east gradients and complex circulation patterns in the Mediterranean Sea, combined with the ubiquity of pelagic copepods, provide an ideal model to study the ecological processes driving host-associated microbial spatial distribution. Here, we characterized and compared the copepod-associated microbial metacommunities (CAMC) with those from seawater microbial metacommunities (SMC). Copepod-associated microbial metacommunities displayed spatial dissimilarity between the western and eastern basins, while SMC exhibited similar microbial compositions. The within-basin similarity observed in CAMC was associated with connectivity by the surface currents. Ecological drift explained most of CAMC variability, likely as a response to the restricted co-dispersal of the hosts with their microbes, which presented low prevalence and abundance. Seawater microbial metacommunities displayed higher homogenizing dispersal, with widely distributed generalist taxa. We conclude that CAMC better reflect cross-basin gradients and connectivity patterns than SMC, suggesting that CAMC may serve as a useful proxy for studying microbial biogeography.

While there is a diversity of approaches for modeling phytoplankton blooms, their accuracy in predicting the onset and manifestation of a bloom is still lagging behind what is needed to support effective management. We outline a framework that integrates trait theory and ecosystem modeling to improve bloom prediction. This framework builds on the concept that the phenology of blooms is determined by the dynamic interaction between the environment and traits within the phytoplankton community. Phytoplankton groups exhibit a collection of traits that govern the interplay of processes that ultimately control the phases of bloom initiation, maintenance, and collapse. An example of process-trait mapping is used to demonstrate a more consistent approach to bloom model parameterization that allows better alignment with models and laboratory- and ecosystem-scale datasets. Further approaches linking statistical-mechanistic models to trait parameter databases are discussed as a way to help optimize models to better simulate bloom phenology and allow them to support a wider range of management needs.

The deep Southern Adriatic is a Mediterranean region highly sensitive to climate change, influenced by dense water cascading from the northern Adriatic and heat/salt transport from the Eastern Mediterranean. Historical (since 1957) and modern (permanent and opportunistic temperature and salinity sampling, Argo floats, fixed moorings) measurements reveal a substantial change since the mid-2000s in thermohaline properties. Historically marked by steady increases in temperature, salinity, and density, with substantial saw-tooth decadal variability, the near-bottom Southern Adriatic has experienced unprecedented warming (0.8°C) and salinization (0.2) over the past decade, accelerating in time and reversing density trends. The inflow of much more saline waters reduced stratification and altered dense water properties at its source in the northern Adriatic. This at least fivefold acceleration of the high-emission regional climate projections may have substantial effects on the Adriatic biogeochemistry and living organisms, changing sea level trends and more.

Phytoplankton blooms in the Southern Ocean (SO) are seasonally limited by light and micronutrients. As such, regional variations in iron supply from mixed-layer winter entrainment are expected to impact the extent of seasonal iron limitation. Here, we determined seasonal iron limitation in the Atlantic SO by conducting iron addition incubation experiments during winter, prior to the maximum mixed-layer deepening, and in spring, prior to the peak of the summer bloom. Both the polar and subantarctic zones displayed evidence of iron limitation in spring, based on increased photosynthetic efficiency, with evidence of the subantarctic zone being limited in winter. In contrast, there was no evidence of limitation in either season in the sub-tropical and Antarctic zones. The large degree of zonal variability in the timing of iron supply resulting from winter entrainment impacts the seasonal characteristics of iron limitation, phytoplankton physiology and the potential for growth.

Coastal waters exhibit the highest and most dynamic dissolved CH₄ concentrations in marine environments, but significant knowledge gaps on the distribution and emissions, particularly in the Southern Ocean, still exist. We quantified dissolved CH₄ concentrations and sea–air fluxes in the coastal waters of Maxwell Bay, King George Island, Antarctica, in December 2023. Surface waters showed exceptionally high CH₄ supersaturations (213–2342%), associated with lower salinity and higher turbidity, which were attributed primarily to meltwater discharge from a retreating tidewater glacier. Our findings suggest that glacial melt may significantly increase CH₄ emissions from Antarctic coastal waters, highlighting the need for further research to understand CH₄ dynamics and improve emission estimates in the context of accelerating climate-driven glacial melt.

Global carbon sequestration by macroalgae is hypothesized to rival rates in other blue carbon ecosystems. However, quantifying macroalgal carbon sequestration is challenging as it is hypothesized to occur outside macroalgal ecosystems, with 73% of sequestration occurring when dissolved organic carbon (DOC) is exported to deep ocean waters. In part due to the complexity of tracking carbon from coastal ecosystems to deep waters, large uncertainties remain about the rate of macroalgal carbon sequestration and its fate in the ocean. We present a synthesis of literature on macroalgal carbon cycling and place it in the context of the marine carbon cycle with a focus on DOC. Synthesis and critiquing of current estimates, including through a case study, indicates that uncertainty around all macroalgal carbon cycle terms remains high. To reduce uncertainty, we recommend developing and comparing estimates made via independent methods including by modeling, remote sensing, and using geochemical tracers.

The ocean microbe-metabolite network involves thousands of individual metabolites that encompass a breadth of chemical diversity and biological functions. These microbial metabolites mediate biogeochemical cycles, facilitate ecological relationships, and impact ecosystem health. While analytical advancements have begun to illuminate such roles, a challenge in navigating the deluge of marine metabolomics information is to identify a subset of metabolites that have the greatest ecosystem impact. Here, we present an ecological framework to distill knowledge of fundamental metabolites that underpin marine ecosystems. We borrow terms from macroecology that describe important species, namely “dominant,” “keystone,” and “indicator” species, and apply these designations to metabolites within the ocean microbial metabolome. These selected metabolites may shape marine community structure, function, and health and provide focal points for enhanced study of microbe-metabolite networks. Applying ecological concepts to marine metabolites provides a path to leverage metabolomics data to better describe and predict marine microbial ecosystems.

Concentrations of total dissolved inorganic carbon (DIC) in freshwater ecosystems are controlled by terrestrial inputs and a myriad of in situ processes, such as aquatic metabolism. Dissolved CO₂ is one of the components of DIC, and its dynamics are also regulated by chemical equilibrium with the DIC pool, so-called carbonate buffering. Although its importance is generally recognized, carbonate buffering is still not consistently accounted for in freshwater studies. Here, we review key concepts in freshwater carbonate buffering, perform simulation experiments, and provide a case study of an alkaline river to illustrate calculations of DIC from CO₂. These analyses demonstrate that carbonate buffering can alter common interpretations of CO₂ data, including carbon–oxygen coupling through production and respiration. As direct measurements of dissolved CO₂ are increasingly common, accounting for CO₂ equilibria with DIC is critical to understanding its role in carbon cycling within most freshwater systems.

Storm deposition is critical for burying estuarine sedimentary organic carbon (OC), yet how this process responds to artificial island construction remains unclear. We examined this issue by comparing lithology, elemental and organic geochemistry, and ²¹⁰Pb and ¹³⁷Cs profiles of two sediment cores retrieved 1 yr apart near the newly constructed Zhoushan Green Petrochemical Base (ZGPB) in Hangzhou Bay, China. We identified a post-construction storm deposit of unprecedented thickness, likely formed by high-turbidity flows linked to a storm-triggered submarine landslide near ZGPB. The associated substantial OC burial during storm's waning phase was far outweighed by OC loss due to severe erosion during its waxing phase. This net OC loss was further exacerbated by enhanced remineralization within the thick deposit. These findings underscore the necessity for holistic planning of artificial islands, as their construction may amplify coastal vulnerability to emerging geohazards and undermine estuarine carbon storage capacity.