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Abstract Microbial ecological functions are an emergent property of community composition. For some ecological functions, this link is strong enough that community composition can be used to estimate the quantity of an ecological function. Here, we apply random forest regression models to compare the predictive performance of community composition and environmental data for bacterial production (BP). Using data from two independent long-term ecological research sites—Palmer LTER in Antarctica and Station SPOT in California—we found that community composition was a strong predictor of BP. The top performing model achieved an R2 of 0.84 and RMSE of 20.2 pmol L−1 hr−1 on independent validation data, outperforming a model based solely on environmental data (R2 = 0.32, RMSE = 51.4 pmol L−1 hr−1). We then operationalized our top performing model, estimating BP for 346 Antarctic samples from 2015 to 2020 for which only community composition data were available. Our predictions resolved spatial trends in BP with significance in the Antarctic (P value = 1 × 10−4) and highlighted important taxa for BP across ocean basins. Our results demonstrate a strong link between microbial community composition and microbial ecosystem function and begin to leverage long-term datasets to construct models of BP based on microbial community composition. 

Marine heterotrophicBacteria(or referred to as bacteria) play an important role in the ocean carbon cycle by utilizing, respiring, and remineralizing organic matter exported from the surface to deep ocean. Here, we investigate the responses of bacteria to climate change using a three-dimensional coupled ocean biogeochemical model with explicit bacterial dynamics as part of the Coupled Model Intercomparison Project Phase 6. First, we assess the credibility of the century-scale projections (2015–2099) of bacterial carbon stock and rates in the upper 100 m layer using skill scores and compilations of the measurements for the contemporary period (1988–2011). Second, we demonstrate that across different climate scenarios, the simulated bacterial biomass trends (2076–2099) are sensitive to the regional trends in temperature and organic carbon stocks. Bacterial carbon biomass declines by 5–10% globally, while it increases by 3–5% in the Southern Ocean where semi-labile dissolved organic carbon (DOC) stocks are relatively low and particle-attached bacteria dominate. While a full analysis of drivers underpinning the simulated changes in all bacterial stock and rates is not possible due to data constraints, we investigate the mechanisms of the changes in DOC uptake rates of free-living bacteria using the first-order Taylor decomposition. The results demonstrate that the increase in semi-labile DOC stocks drives the increase in DOC uptake rates in the Southern Ocean, while the increase in temperature drives the increase in DOC uptake rates in the northern high and low latitudes. Our study provides a systematic analysis of bacteria at global scale and a critical step toward a better understanding of how bacteria affect the functioning of the biological carbon pump and partitioning of organic carbon pools between surface and deep layers. 

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 We examined microbial succession along a glacier forefront in the Antarctic Peninsula representing ∼30 years of deglaciation to contrast bacterial and eukaryotic successional dynamics and abiotic drivers of community assembly using sequencing and soil properties. Microbial communities changed most rapidly early along the chronosequence, and co-occurrence network analysis showed the most complex topology at the earliest stage. Initial microbial communities were dominated by microorganisms derived from the glacial environment, whereas later stages hosted a mixed community of taxa associated with soils. Eukaryotes became increasingly dominated by Cercozoa, particularly Vampyrellidae, indicating a previously unappreciated role for cercozoan predators during early stages of primary succession. Chlorophytes and Charophytes (rather than cyanobacteria) were the dominant primary producers and there was a spatio-temporal sequence in which major groups became abundant succeeding from simple ice Chlorophytes to Ochrophytes and Bryophytes. Time since deglaciation and pH were the main abiotic drivers structuring both bacterial and eukaryotic communities. Determinism was the dominant assembly mechanism for Bacteria, while the balance between stochastic/deterministic processes in eukaryotes varied along the distance from the glacier front. This study provides new insights into the unexpected dynamic changes and interactions across multiple trophic groups during primary succession in a rapidly changing polar ecosystem. 

abstract The marine coastal region makes up just 10% of the total area of the global ocean but contributes nearly 20% of its total primary production and over 80% of fisheries landings. Unicellular phytoplankton dominate primary production. Climate variability has had impacts on various marine ecosystems, but most sites are just approaching the age at which ecological responses to longer term, unidirectional climate trends might be distinguished. All five marine pelagic sites in the US Long Term Ecological Research (LTER) network are experiencing warming trends in surface air temperature. The marine physical system is responding at all sites with increasing mixed layer temperatures and decreasing depth and with declining sea ice cover at the two polar sites. Their ecological responses are more varied. Some sites show multiple population or ecosystem changes, whereas, at others, changes have not been detected, either because more time is needed or because they are not being measured. 

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. 

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.