1. ¹Limnology/Department of Ecology and Evolution, Uppsala University, BMC, Uppsala, Sweden
2. ²Organic Pharmaceutical Chemistry/Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
3. ³Department of Ecology, University of Copenhagen, Fredriksberg C, Denmark

Correspondence: S Bertilsson, Limnology/Department of Ecology and Evolution, Uppsala University, BMC, Box 573, Uppsala SE-75123, Sweden. E-mail: stebe@ebc.uu.se

⁴These authors contributed equally to the work.

Received 12 April 2007; Revised 28 June 2007; Accepted 28 June 2007; Published online 2 August 2007.

Abstract

Influence of distribution and abundance of bacterial taxa on ecosystem function are poorly understood for natural microbial communities. We related 16S rRNA-based terminal restriction fragment length polymorphism to bacterial production and arginine uptake kinetics to test if functional features of bacterioplankton in four lakes could be predicted from community composition. Maximum arginine uptake rate (arginine V_max) ranged from 10% to 100% of bacterial production. Owing to high growth efficiencies on arginine (63–77%), the bacterial community could potentially saturate its carbon demand using this single organic substrate, for example, during sudden surges of free amino acids. However, due to low in situ concentrations of arginine in these lakes (<0.9 g l^-1), actual uptake rates at ambient concentrations rarely exceeded 10% of V_max. Bacterial production and arginine V_max could be predicted from a subset of bacterial ribotypes, tentatively affiliated with several bacterial divisions (Cyanobacteria, Actinobacteria, Bacteroidetes and Proteobacteria). Multivariate statistical analysis indicates that there were both highly important and less important ribotypes for the prediction of bacterial production and arginine V_max. These populations were either negatively or positively related to the respective functional feature, indicating contrasting ecological roles. Our study provides a statistically robust demonstration that, apart from environmental conditions, patterns in bacterial community composition can also be used to predict lake ecosystem function.