Search

Biochar greatly influences the soil bacterial community and nutrient transformations, while our knowledge of the responses of fungal lifestyles to biochar is still in its infancy. Here, we used experimental pre-treatments (acetone extraction) of nutrient-rich biochars to identify which major biochar properties influence fungi the most: the easily mineralizable C, fused aromatic backbone, or the inorganic nutrients of biochars. Our objective was to investigate how different biochar fractions (easily mineralizable C, fused aromatic C, nutrients) structure the fungal taxonomic and functional communities. The easily mineralizable C of biochars induced greater short-term changes in fungal community composition compared to the fused aromatic C. The easily mineralizable C significantly decreased the relative abundance of Basidiomycota by avg. 10.6%, while it had no effects on Ascomycota and Zygomycota. Co-occurrence network indicated that saprophytic fungi were self-assembled in the easily mineralizable C-sufficient environment, whereas they were the connectors to interact with other groups when lower amounts of energy in form of mineralizable C were present. Thus, the easily mineralizable C in biochar as a microbial C source probably promoted saprotroph growth, caused them to self-assemble and to enhance their competitive capacity, leading to overall diversity decrease and relative decline of fungal pathogens. The inorganic nutrients had no effects on fungal diversity and saprotroph abundance, while they decreased the relative abundance of Zygomycota. Our study highlighted the important roles of both mineralizable C and inorganic nutrients in modification of the fungal community, and demonstrated that biochar probably favors the growth of saprotrophs over soil-borne fungal pathogens.

This study underpins quantitative relationships that account for the combined effects that starting biomass and peak pyrolysis temperature have on physico-chemical properties of biochar. Meta-data was assembled from published data of diverse biochar samples (n=102) to (i) obtain networks of intercorrelated properties and (ii) derive models that predict biochar properties. Assembled correlation networks provide a qualitative overview of the combinations of biochar properties likely to occur in a sample. Generalized Linear Models are constructed to account for situations of varying complexity, including: dependence of biochar properties on single or multiple predictor variables, where dependence on multiple variables can have additive and/or interactive effects; non-linear relation between the response and predictors; and non-Gaussian data distributions. The web-tool Biochar Engineering implements the derived models to maximize their utility and distribution. Provided examples illustrate the practical use of the networks, models and web-tool to engineer biochars with prescribed properties desirable for hypothetical scenarios.

Natural organic matter (NOM) is a highly active component of soils and sediments, and plays all important role in global C cycling. However, NOM has defied molecular-level structural characterization, owing to variations along the decomposition continuum and its existcnce as highly functionalized polyelectrolytes. We conducted a conrprehensivc systematic overview of spectral signatures and peak positions of major organic molecules that occur as part of NOM using near-edge x-ray absorption fine structure (NEXAFS) spectroscopy. The spectra of carbohydrates and amino sugars show resonances between 289.10 and 289.59 eV, attributed to 1s-3p/[[sigma].sup.*] transitions of O-alkyl (C-OH) moieties. They also exhibited distinct peaks between 288.42 and 288.74 eV, representing C 1s-[[pi].sup.*.sub.C=O] transition from COOH functionalities. Amino acids produced a strong signal around 288.70 eV which can be identified as a C [[pi].sup.*.sub.C=O] transition of carboxyl/carbonyl (COOH/ COO-) structures. Spectral features near 285.29 eV were ascribed to C [[pi].sup.*.sub.C=C] transition of ring structure of aromatic amino acids, while spectra between 287.14 and 287.86 eV were attributed to C [[pi].sup.*.sub.C-H] and C 1s-[[sigma].sup.*.sub.C-H/]3p Rydberg-like excitations from CH and C[H.sub.2] groups. Phenols and benzoquinone produced strong resonances between 285.08 and 285.37 eV, attributed to the [[pi].sup.*] orbital of C (C 1s-[[pi].sup.*.sub.C=C]) atoms connected to either C or H (C-H) in the aromatic ring. The next higher excitation common to both phenols and quinone appeared between 286.05 and 286.35 eV, and could be associated with C 1s[[pi].sup.*.sub.C=C] transitioxrs of aromatic C bonded to O atom in phenols, and to C 1s-[[pi].sup.*.sub.C=O] transitions from aromatic C connected to O atom (C-OH) in phenols or to a C=O in p-benzoquinone and some phenols with carbonyl structures, respectively. Nucleobases exhibited complex spectral features with pronounced resonances between 286.02 and 286.84 eV and between 288.01 and 288.70 eV. Molecular markers for black C (benzenecarboxylic acid and biphenyl-4,4'-dicarboxylic acid) exhibit sharp absorption bands between 285.01 and at 285.43 eV, possibly from C 1s-[[pi].sup.*.sub.C=C] transition characteristic of C-H sites or unsaturated C (C=C) on aromatic ring structures. These aromatic carboxylic acids also exhibit broad peaks between 288.35 and 288.48 eV, reflecting C [[pi].sup.*.sub.C=O] transition of carboxyl functional groups bonded to unsaturated C. This investigation provides a more comprehensive NEXAFS spectral library of biogeochemically relevant organic C compounds. The spectra of these reference organic compounds reveal distinct spectral features and peak positions at the C K-edge that arc characteristic of the molecular orbitals bonding C atoms. Detailed structural information can be derived from these distinctive spectral features that could be used to build robust peak assignment criteria to exploit the chemical sensitivity of NEXAFS spectroscopy for in situ molecular-level spatial investigation and fingerprinting of complex organic C compounds in environmental samples. Abbreviations: EDX, energy dispersive x-ray; NEXAFS, near-edge x-ray absorption fine structure spectroscopy; NOM, natural organic matter; SEM, scanning electron microscopy; STXM, scanning transmission x-ray microscopy; TEM transmission electron microscope: XPS, x-ray photoelectron spectroscopy. doi: 10.2136/sssaj2008.0228