Biochar drives humus formation during composting by regulating the specialized metabolic features of microbiome

Biochars have attracted tremendous attention due to their effects on soil improvement; they enhance carbon storage, soil fertility and quality, and contaminant (organic and heavy metal) immobilization and transformation. These effects could be achieved by modifying soil microbial habitats and (or) directly influencing microbial metabolisms, which together induce changes in microbial activity and microbial community structures. This review links microbial responses, including microbial activity, community structures and soil enzyme activities, with changes in soil properties caused by biochars. In particular, we summarized possible mechanisms that are involved in the effects that biochar-microbe interactions have on soil carbon sequestration and pollution remediation. Special attention has been paid to biochar effects on the formation and protection of soil aggregates, biochar adsorption of contaminants, biochar-mediated transformation of soil contaminants by microorganisms, and biochar-facilitated electron transfer between microbial cells and contaminants and soil organic matter. Certain reactive organic compounds and heavy metals in biochar may induce toxicity to soil microorganisms. Adsorption and hydrolysis of signaling molecules by biochar interrupts microbial interspecific communications, potentially altering soil microbial community structures. Further research is urged to verify the proposed mechanisms involved in biochar-microbiota interactions for soil remediation and improvement.

Statistical Analysis of Mixed-Ploidy Populations (StAMPP) is a freely available R package for calculation of population structure and differentiation based on single nucleotide polymorphism (SNP) genotype data from populations of any ploidy level, and/or mixed-ploidy levels. StAMPP provides an advance on previous similar software packages, due to an ability to calculate pairwise FST values along with confidence intervals, Nei's genetic distance and genomic relationship matrixes from data sets of mixed-ploidy level. The software code is designed to efficiently handle analysis of large genotypic data sets that are typically generated by high-throughput genotyping platforms. Population differentiation studies using StAMPP are broadly applicable to studies of molecular ecology and conservation genetics, as well as animal and plant breeding.