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Additional file 1: Figure S1. Gas production of bioreactors. Figure S2. Biomass production of bioreactors and correlation analysis. Figure S3. Microbial community composition profiles of bioreactors. Figure S4. Alpha diversity metrics of bioreactor communities. Figure S5. Predictive performance of three machine learning algorithms using HRT bioindicators. Figure S6. Predictive performance of three machine learning algorithms using non-HRT bioindicators for considering community assembly caused by time. Figure S7. Prediction results of C6 and C8 productivities using non-HRT bioindicators for considering community assembly caused by time. Figure S8. Prediction results of C6 and C8 productivities for all samples in the four HRT phases using HRT bioindicators. Figure S9. Prediction results of C6 and C8 productivities for all samples in the four HRT phases using non-HRT bioindicators for considering community assembly caused by time. Figure S10. Random forest feature importance of A-HRT bioindicators and B-HRT bioindicators used to predict C6 and C8 productivities. Figure S11. Random forest feature importance of the non-HRT bioindicators used to predict C6 and C8 productivities. Figure S12. Metabolic pathways involved in converting lactate and xylan to n-caproate and n-caprylate. Figure S13. Correlation network of environmental factors, process performance and microbial community. Figure S14. Prediction results of C6 and C8 productivities for all samples in the four HRT phases using the four ASVs of HRT bioindicators irrespective of time. Figure S15. Reducing HRT increases abundances of HRT bioindicators driving the catabolism of xylan and lactate to n-caproate and n-caprylate. Figure S16. Alpha rarefaction curves. Figure S17. Workflow of the random forest classification analysis. Figure S18. Workflow of a two-step random forest regression analysis. Table S1. Mean carboxylate yields (i.e., C mole product to substrate ratios) at HRTs of 8 days and 2 days (stable production period). Table S2. Explained variances of the training set in the regression-based prediction of process parameters using A-HRT bioindicators and B-HRT bioindicators. Table S3. Explained variances of the training set in the regression-based prediction of process parameters using non-HRT bioindicators for considering community assembly caused by time. Table S4. Growth medium used for the reactor operation. Table S5. Daily feeding of bioreactors A and B during the four HRT phases.

Additional file 1. Additional information containing details about: S1 the reactor set-up, S2 the feed composition, S3 the degree of substrate degradation, S4 the gas production and composition, S5 miscellaneous reactor parameters, S6 the gas chromatography detection and calibration limits, S7 the concentrations of non-target carboxylates, S8 the gating strategy, S9 the flow cytometric controls, S10 the microbial community dynamics, S11 the correlation analysis, S12 the flow cytometric cell sorting and S13 the sequencing protocols and details of sequence analysis.

Additional file 1. Details on Methods and Results. Composition of mineral medium, details on experimental design, detailed process performance data of all experiments, detailed results of microbial community analysis, detailed ADM1 simulation results for all experiments.