Aquatic microbial primary producers exist in genetically diverse populations, but are often studied as single lineages, so that interpreting single lineage studies relies critically on understanding how microbial growth differs with social milieu. The properties of lineages grown alone often fail to predict the growth of these same lineages in the presence of conspecifics, and this discrepancy points towards an opportunity to improve our understanding of how multilineage assemblages of a species are shaped. We demonstrate that different lineages of a marine picoplankter modulate their lineage growth rate in response to the presence of non-self conspecifics, even when resource competition is effectively absent. This explains why growth rates of lineages in isolation do not reliably predict their growth rates in mixed culture, or the lineage composition of assemblages. The diversity of growth strategies observed are thus consistent with lineage-specific energy-allocation that depends on social milieu. Since lineage growth is only one of many traits determining fitness in natural assemblages, we propose that in all but the poorest quality environments where allocating maximum energy to growth is the only viable strategy, we should expect intraspecific variation in growth strategies, with more strategies possible in ameliorated environments, such as high CO₂ for many marine picoplankton. 

For detailed methods, please refer to the methods section in the manuscript. 

This submission includes the following files:

R Files:

“2020927_Collins_Schaum_ProcB_plotting_andstats_figure02_03_upper_panels.R” R code to create panels A,B,C in Figures 02 and 03 in the main manuscript. It also fits a non linear mixed model to the data. 

“2020927_Collins_Schaum_ProcB_plotting_andstats_figure02_03_lower.R” R code to create panels D,E,F in Figures 02 and 03 in the main manuscript. It also fits a linear mixed model to the data. 

"20200925_regressiontomean_OK_to_submit.R": This file tests whether we can get the observed pattern solely due to regression to a mean  and makes SI Figure 02 (plus several others that were not displayed due to file size). 

" 20200927_Collins_Schaum_ProcB_SIgraphs_03to08_code.R" makes SI Figures 3 through to 8. 

Data Files:

"carballoc400_1000ppm.csv" This looks into whether after accounting for 'losses' through respiration, 'excess' carbon goes into growth, or whether we assume that it must go elsewhere (or whether it seems that in order to maintain growth rates, samples must be obtaining C from elsewhere).  Here, ecotype indicates the focal lineage, biorep the biological replicate number, PS.avg are average photosynthesis rates per biological replicate (i.e. the technical replicates are pooled) in µg C per µgC per hour,  mue.avg are the average growth rates as µ day^-1 (again, pooled for technical replicates), mue.se is the standard error to go with with mue.avg, surplus_percent_PS shows the % of surplus PS, ppm is the selection pCO2,  react_to indicates whether samples were grown in co-culture, spiked media or against a GFP strain, muecomp.avg is the average change in growth rate upon encountering another lineage, spike, or the GFP strain and muecomp.se is the standard error thereof. This data set is mainly used to make graphs within the SI

“MonoCoStrategies_SI_Figure_03_data.csv” Data to make SI Figure 03. Column headers as above.

“MonoCoStrategies_SI_Figure_04_data.csv” Data to make SI Figure 04. Column headers as above. 

"20190418_foldchangedataCO2_GFP.csv" GFP Data (at elevated pCO2) to be used with "20190418_stats_and_curve_fitting.R" . Mono indicates the growth-rate of the lineage in monoculture, GFP is the fold-change difference in growth upon encountering the GFP lineage, Foc_lin indicates the focal lineage, biorep is for the level of biological replication, tech rep is for the level of technical replication, 'unique sample' is for plotting purposes only as it assigns a unique identifier within each focal lineage/biorep/techrep combination. against is to show whether the focal lineage was grown in co-culture, spiked media or against the GFP strain and is only useful when several 'foldchangedataCO2" files are being merged. 

"20190418_foldchangedataCO2_cocu.csv" direct co-culture data at elevated pCO2 to be used with "20190418_stats_and_curve_fitting.R". Column names are as above. 

"20190418_foldchangedataCO2_spiked.csv" spiked cultures data at elevated pCO2 to be used with "20190418_stats_and_curve_fitting.R". Column names are as above. 

"20190418_foldchangedata_cocu.csv" direct co-culture data at ambient pCO2 to be used with "20190418_stats_and_curve_fitting.R". Column names are as above. 

"20190418_foldchangedata_spiked.csv" spiked cultures data at ambient pCO2 to be used with "20190418_stats_and_curve_fitting.R". Column names are as above. 

"20190418_foldchangedata_GFP.csv" GFP cultures data at ambient pCO2 to be used with "20190418_stats_and_curve_fitting.R". Column names are as above.