Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, Escherichia coli. Our system, based on cutting-edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 82–88%, over the 12–18% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell-intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, E. coli, and still exhibit patterns such as classical senescence, non-senescence, or negative senescence. We end by discussing whether similar levels of non-genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive.

#### Leslie matrix strain AB1157

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain AB1157. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesAB1157.csv

#### Leslie matrix strain BW25113

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain BW25113. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesBW25113.csv

#### Leslie matrix strain IAI1

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain IAI1. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesIAI1.csv

#### Leslie matrix strain MG1655

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain MG1655. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesMG1655.csv

#### Leslie matrix strain MG1655Inlag

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain MG1655Inlag. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesMG1655Inlag.csv

#### Leslie matrix MG1655LM

This csv file contains data of a age structured, Leslie matrix population projection model for E. coli strain MG1655LM. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesMG1655LM.csv

#### Leslie matrix strain W3110

This csv file contains data of a age structured Leslie matrix population projection model for E. coli strain W3110. The data has been collected using a microfluidic device, called the mother machine. The discrete time steps in the Leslie matrix is one hour (note the initial data has been collected at 4 min time intervals). Age goes from birth (second column) to the last column of the matrix. Fertility rates (number of division per hour) are in the top row (first row after the header row). Survival rates are in the sub-diagonal. Final age with open age class.

lesW3110.csv

#### R code for analyzing the Leslie matrix data

This is the R code that has been used for computing the different demographic parameters of Table 2 in the article: population growth rate lambda, generation time T, cohort generation time T_c, Mean lifespan, SD lifespan, coefficient of variation (CV) in lifespan, Mean lifetime reproductive success (LRS), SD LRS, CV LRS.

LeslieAnalysis.R