Influent Disturbance Drives Microbial Assembly Pattern and Co-occurrence Network, Linking to the Operating Performance in Full-Scale Leachate Anoxic/Aerobic Process

The stability and activity of microbial communities directly diagnose the health of leachate biological treatment processes, and unveiling the ecological drivers of microbial assembly could identify the critical factors resulting from the influent disturbances and improve operational performance. Hereby, we conducted a meta-analysis of microbial diversity, ecological mechanisms based on a full-scale working leachate treatment plant (LTP) around one year, and co-occurrence for shaping their communities to screen the critical microbial responses to the variations of influent loadings in practical operation. A significant difference was observed in the treatment process under the low and high-loading periods ( p < 0.001) with 0.71 ± 0.09 and 0.95 ± 0.09 mg COD Cr /mg MLSS, respectively, with 60.6%, 95.4%, and 64.1% of COD Cr, NH 4 + -N, and TN removal under the low-loading period. The microbial diversity was 6.75 and 5.68 under the low- and high-loading periods in terms of the Shannon index, which was the most limiting factor influencing the operation performance ( r = 0.618). The deterministic processes had a dominant role in the microbial assembly during the high-loading period, and they had little effect on the system performance. Low loadings led to over 20% of microorganism species from five bins dominating from homogeneous selection (HoS, deterministic process) to ecological drift (DR, stochastic processes), as the 2456 observed OTUs were divided into 94 phylogenetic bins, which increased microbial stability with a large average clustering coefficient of 0.192 and 15 connectors based on a complex network structure analysis. COD Cr loadings rather than nitrogen loadings were critical to affecting the diversity ( r = −0.771), leading to the pollutant removal rates decreasing by 11.4–14.3%. norank_f_Saprospiraceae could be the indicator microorganism for excessive organic loadings, and on-site monitoring of microbial ecology evolution should be developed to provide clues about the operational performance of the leachate treatment process in advance.