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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.