Data from: Evolutionary rescue in populations of Pseudomonas fluorescens across an antibiotic gradient

Environmental change represents a major threat to species persistence. When change is rapid, a population's only means of persisting may be to evolve resistance. Understanding such 'evolutionary rescues' is important for conservation in the face of global change, but also in the agricultural and medical sciences, where the objective is rather population control or eradication. Theory predicts that evolutionary rescue is fostered by large populations and genetic variation, but this has yet to be tested. We replicated hundreds of populations of the bacterium Pseudomonas fluorescens SBW25 submitted to a range of doses of the antibiotic streptomycin. Consistent with theory, population size, and initial genetic diversity influenced population persistence and the evolution of antibiotic resistance. Although all treated populations suffered initial declines, those experiencing the smallest decreases were most likely to be evolutionarily rescued. Our results contribute to our understanding of how evolution may or may not save populations and species from extinction.Rams_exp1_1experiment 1: data set for survival analysis. column 1: population type {clonal, diversified}; column 2: antibiotic dose; column 3: population survival {alive, dead}Rams_exp1_2Data set for time series analysis of population size in experiment 1, during the first 22h. column 1: population type {clonal, diversified}; column 2: antibiotic dose; column 3: population replicate; column 4: time {hours}; column 5: log10(population size+1); column 6: future population rescue {alive, dead}Rams_exp1_3data for final population size (t=53h) in experiment 1 (rescued populations). Column 1: population type {clonal, diversified}; column 2: antibiotic dose; column 3: log10(population size+1).Rams_exp2_1data set for analysis of population rescue at end of experiment 2 (t=86hours). Column 1: population type {0.2ml, 1.5ml volume}; column 2: population rescue {alive, dead}; column 3: antibiotic dose.Rams_exp2_2data set for time series analysis of population size during experiment 2. Column 1: population type {0.2ml, 1.5ml volume}; column 2: population rescue {alive, dead after 86h}; column 3: antibiotic dose; column 4: population identity; column 5: time {hours}; column 6: log10(population size+1)RAms_exp2_3data set for analysis of correlation between change in log population size (t48 minus t24) and frequency of antibiotic-resistant type in the population. Column 1: antibiotic dose; column 2: change in population size; column 3: frequency of resistant type.Rams_exp2_4data file for analysis of final (t=86h) population size in rescued (1.5ml volume) populations and frequency of antibiotic resistant types in these populations. Column 1: antibiotic dose; column 2: frequency of resistant type; column 3: log10(population size+1)