Use of pyrolysis molecular beam mass spectrometry (py-MBMS) to characterize forest soil carbon: method and preliminary results.

The components of soil organic matter (SOM) and their degradation dynamics in forest soils are difficult to study and thus poorly understood, due to time-consuming sample collection, preparation, and difficulty of analyzing and identifying major components. As a result, changes in soil organic matter chemical composition as a function of age, forest type, or disturbance have not been examined. We applied pyrolysis molecular beam mass spectrometry (py-MBMS), which provides rapid characterization of SOM of whole soil samples. to the Tionesta soil samples described by Hoover, C.M., Magrini, K.A., Evans, R.J., 2002. Soil carbon content and character in an old growth forest in northwestern Pennsylvania: a case study introducing molecular beam mass spectrometry (PY-MBMS). Environmental Pollution 116 (Supp. 1), S269-S278. Our goals in this work were to: (1) develop and demonstrate an advanced, rapid analytical method for characterizing SOM components in whole soils, and (2) provide data-based models to predict soil carbon content and residence time from py-MBMS analysis. Using py-MBMS and pattern recognition techniques we were able to statistically distinguish among four Tionesta sites and show an increase in pyrolysis products of more highly decomposed plant materials at increasing sample depth. For example, all four sites showed increasing amounts of older carbon (phenolic and aromatic species) at deeper depths and higher amounts of more recent carbon (carbohydrates and lignin products) at shallower depths. These results indicate that this type of analysis could be used to rapidly characterize SOM for the purpose of developing a model, which could be used in monitoring the effect of forest management practices on carbon uptake and storage.

Identification of QTLs influencing wood property traits in loblolly pine ( Pinus taeda L.). II. Chemical wood properties.

Chemical wood property traits were analyzed for the presence of quantitative trait loci (QTLs) in a three-generation outbred pedigree of loblolly pine ( Pinus taeda L.). These traits were assayed using pyrolysis molecular beam mass spectrometry and include mass spectrum peak intensities associated with carbohydrates, alpha-cellulose and hemicellulose sugars, and lignin. Models for projection to latent structures (PLS) were used to also estimate the chemical composition of cell walls (i.e., alpha-cellulose, galactan and lignin) from mass spectrum data using multivariate regression. Both earlywood and latewood fractions from the fifth annual ring were analyzed for each trait. An interval mapping approach designed for an outbred pedigree was used to estimate the number of QTLs, the magnitude of QTL effects, and their genomic position. Eight unique QTLs influencing cell wall chemistry were detected from multiple peak intensities and/or PLS estimates using the one- and two-QTL models. Significant differences in chemical contents were observed among the populations from North Carolina vs Oklahoma, and results from QTLxenvironment analyses suggest that QTLs interact with environmental location. QTLs should be verified in larger experiments and in different genetic and environmental backgrounds. QTL mapping will help towards eventually identifying genes having a major effect on chemical wood properties.