Patterns, Processes And Models Of Microbial Recovery In A Chronosequence Following Reforestation Of Reclaimed Mine Soils
Soil microbial communities mediate important ecological processes and play essential roles in biogeochemical cycling. Ecosystem disturbances such as surface mining significantly alter soil microbial communities, which could lead to changes or impairment of ecosystem functions. Reforestation procedures were designed to accelerate the reestablishment of plant community and the recovery of the forest ecosystem after reclamation. However, the microbial recovery during reforestation has not been well studied even though this information is essential for evaluating ecosystem restoration success. In addition, the similar starting conditions of mining sites of different ages facilitate a chronosequence approach for studying decades-long microbial community change, which could help generalize theories about ecosystem succession. In this study, the recovery of microbial communities in a chronosequence of reclaimed mine sites spanning 30 years post reforestation along with unmined reference sites was analyzed using next-generation sequencing to characterize soil-microbial abundance, richness, taxonomic composition, interaction patterns and functional genes.
Generally, microbial succession followed a trajectory along the chronosequence age, with communities becoming more similar to reference sites with increasing age. However, two major branches of soil microbiota, bacteria and fungi, showed some contrasting dynamics during ecosystem recovery, which are likely related to the difference in their growth rates, tolerance to environmental change and relationships with plants. For example, bacterial communities displayed more intra-annual variability and more complex co-occurrence networks than did fungi. A transition from copiotrophs to oligotrophs during succession, suggested by taxonomic composition shifts, indicated that the nutrient availability is one important factor driving microbial succession.
This theory was also supported by metagenomic analysis of the functional genes. For example, the increased abundance of genes involved in virulence, defense and stress response along ages indicated increased competition between microorganisms, which is likely related to a decrease of available nutrients. Metagenomic analysis also revealed that lower relative abundances of methanotrophs and methane monooxygenase at previously-mined sites compared with unmined sites, which supports previous observations that ecological function of methane sink provided by many forest soils has not recovered after 30 years.
Because of the difficulty identifying in situ functional mechanisms that link soil microorganisms with environmental change, modeling can be a valuable tool to infer those relationships of microbial communities. However, the extremely high richness of soil microbial communities can result in extremely complicated models that are difficult to interpret. Furthermore, uncertainty about the coherence of ecological function at high microbial taxonomic levels, grouping operational taxonomic units (OTUs) based on phylogenetic linkages can mask trends and relationships of some important OTUs. To investigate other ways to simplify soil microbiome data for modeling, I used co-occurrence patterns of bacterial OTUs to construct functional groups. The resulting groups performed better at characterizing age-related microbial community dynamics and predicted community structures and environmental factors with lower error.