Search for: All records

Microbial community dynamics on sinking particles control the amount of carbon that reaches the deep ocean and the length of time that carbon is stored, with potentially profound impacts on Earth’s climate. A mechanistic understanding of the controls on sinking particle distributions has been hindered by limited depth- and time-resolved sampling and methods that cannot distinguish individual particles. Here, we analyze microbial communities on nearly 400 individual sinking particles in conjunction with more conventional composite particle samples to determine how particle colonization and community assembly might control carbon sequestration in the deep ocean. We observed community succession with corresponding changes in microbial metabolic potential on the larger sinking particles transporting a significant fraction of carbon to the deep sea. Microbial community richness decreased as particles aged and sank; however, richness increased with particle size and the attenuation of carbon export. This suggests that the theory of island biogeography applies to sinking marine particles. Changes in POC flux attenuation with time and microbial community composition with depth were reproduced in a mechanistic ecosystem model that reflected a range of POC labilities and microbial growth rates. Our results highlight microbial community dynamics and processes on individual sinking particles, the isolation of which is necessary to improve mechanistic models of ocean carbon uptake.

 

The Antarctic marine environment is a dynamic ecosystem where microorganisms play an important role in key biogeochemical cycles. Despite the role that microbes play in this ecosystem, little is known about the genetic and metabolic diversity of Antarctic marine microbes. In this study we leveraged DNA samples collected by the Palmer Long Term Ecological Research (LTER) project to sequence shotgun metagenomes of 48 key samples collected across the marine ecosystem of the western Antarctic Peninsula (wAP). We developed an in silico metagenomics pipeline (iMAGine) for processing metagenomic data and constructing metagenome-assembled genomes (MAGs), identifying a diverse genomic repertoire related to the carbon, sulfur, and nitrogen cycles. A novel analytical approach based on gene coverage was used to understand the differences in microbial community functions across depth and region. Our results showed that microbial community functions were partitioned based on depth. Bacterial members harbored diverse genes for carbohydrate transformation, indicating the availability of processes to convert complex carbons into simpler bioavailable forms. We generated 137 dereplicated MAGs giving us a new perspective on the role of prokaryotes in the coastal wAP. In particular, the presence of mixotrophic prokaryotes capable of autotrophic and heterotrophic lifestyles indicated a metabolically flexible community, which we hypothesize enables survival under rapidly changing conditions. Overall, the study identified key microbial community functions and created a valuable sequence library collection for future Antarctic genomics research. 

Abstract Over the last half of the 20 th century, the western Antarctic Peninsula has been one of the most rapidly warming regions on Earth, leading to substantial reductions in regional sea ice coverage. These changes are modulated by atmospheric forcing, including the Amundsen Sea Low (ASL) pressure system. We utilized a novel 25-year (1993–2017) time series to model the effects of environmental variability on larvae of a keystone species, the Antarctic Silverfish ( Pleuragramma antarctica ). Antarctic Silverfish use sea ice as spawning habitat and are important prey for penguins and other predators. We show that warmer sea surface temperature and decreased sea ice are associated with reduced larval abundance. Variability in the ASL modulates both sea surface temperature and sea ice; a strong ASL is associated with reduced larvae. These findings support a narrow sea ice and temperature tolerance for adult and larval fish. Further regional warming predicted to occur during the 21st century could displace populations of Antarctic Silverfish, altering this pelagic ecosystem. 

Ocean ecosystem models predict that warming and increased surface ocean stratification will trigger a series of ecosystem events, reducing the biological export of particulate carbon to the ocean interior. We present a nearly three-decade time series from the open ocean that documents a biological response to ocean warming and nutrient reductions wherein particulate carbon export is maintained, counter to expectations. Carbon export is maintained through a combination of phytoplankton community change to favor cyanobacteria with high cellular carbon-to-phosphorus ratios and enhanced shallow phosphorus recycling leading to increased nutrient use efficiency. These results suggest that surface ocean ecosystems may be more responsive and adapt more rapidly to changes in the hydrographic system than is currently envisioned in earth ecosystem models, with positive consequences for ocean carbon uptake.

 

Abstract. Heterotrophic marine bacteria utilize organic carbon for growth and biomass synthesis. Thus, their physiological variability is key to the balancebetween the production and consumption of organic matter and ultimately particle export in the ocean. Here we investigate a potential link betweenbacterial traits and ecosystem functions in the rapidly warming West Antarctic Peninsula (WAP) region based on a bacteria-oriented ecosystemmodel. Using a data assimilation scheme, we utilize the observations of bacterial groups with different physiological traits to constrain thegroup-specific bacterial ecosystem functions in the model. We then examine the association of the modeled bacterial and other key ecosystemfunctions with eight recurrent modes representative of different bacterial taxonomic traits. Both taxonomic and physiological traits reflect thevariability in bacterial carbon demand, net primary production, and particle sinking flux. Numerical experiments under perturbed climate conditionsdemonstrate a potential shift from low nucleic acid bacteria to high nucleic acid bacteria-dominated communities in the coastal WAP. Our studysuggests that bacterial diversity via different taxonomic and physiological traits can guide the modeling of the polar marine ecosystem functionsunder climate change. 

A quantitative understanding of the mesopelagic zooplankton food web is key to development of accurate carbon budgets and geochemical models in marine systems. Here we use compound specific nitrogen stable isotope analysis of amino acids to quantify the trophic structure of the microzooplankton and mesozooplankton community during summer in the subarctic northeast Pacific Ocean during the EXport Processes in the Ocean from Remote Sensing (EXPORTS) field campaign. Source amino acid values in particles and zooplankton provide strong evidence that basal resources for the mesopelagic zooplankton food web were primarily small (), suspended or slow‐sinking particles, but that surface organic matter delivered by vertically migrating zooplankton may have also been important. Comparisons of values of source and trophic amino acids provide estimates of food web length, which decrease significantly with depth and suggest that protistan microzooplankton are key components of the food web from the surface to at least 500. These results emphasize the importance of small particles as a source of carbon and nitrogen to mesopelagic communities in this region, support observations of an inverse relationship between zooplankton vertical migration and small particles as sources of carbon to deep‐sea food webs in low productivity environments, and document the role of heterotrophic protists as key trophic intermediaries in the mesopelagic zone at this location.

 

Abstract. The West Antarctic Peninsula (WAP) is a rapidly warming region, withsubstantial ecological and biogeochemical responses to the observed changeand variability for the past decades, revealed by multi-decadal observationsfrom the Palmer Antarctica Long-Term Ecological Research (LTER) program. Thewealth of these long-term observations provides an important resource forecosystem modeling, but there has been a lack of focus on the developmentof numerical models that simulate time-evolving plankton dynamics over theaustral growth season along the coastal WAP. Here, we introduce aone-dimensional variational data assimilation planktonic ecosystem model (i.e., theWAP-1D-VAR v1.0 model) equipped with a modelparameter optimization scheme. We first demonstrate the modified and newlyadded model schemes to the pre-existing food web and biogeochemicalcomponents of the other ecosystem models that WAP-1D-VAR model was adaptedfrom, including diagnostic sea-ice forcing and trophic interactions specificto the WAP region. We then present the results from model experiments wherewe assimilate 11 different data types from an example Palmer LTER growthseason (October 2002–March 2003) directly related to corresponding modelstate variables and flows between these variables. The iterative dataassimilation procedure reduces the misfits between observationsand model results by 58 %, compared to before optimization, via an optimized set of12 parameters out of a total of 72 free parameters. The optimized model resultscapture key WAP ecological features, such as blooms during seasonal sea-iceretreat, the lack of macronutrient limitation, and modeled variables andflows comparable to other studies in the WAP region, as well as severalimportant ecosystem metrics. One exception is that the model slightlyunderestimates particle export flux, for which we discuss potentialunderlying reasons. The data assimilation scheme of the WAP-1D-VAR modelenables the available observational data to constrain previously poorlyunderstood processes, including the partitioning of primary production bydifferent phytoplankton groups, the optimal chlorophyll-to-carbon ratio ofthe WAP phytoplankton community, and the partitioning of dissolved organiccarbon pools with different lability. The WAP-1D-VAR model can besuccessfully employed to link the snapshots collected by the available datasets together to explain and understand the observed dynamics along thecoastal WAP.