- The effects of initial leaf litter chemistry of 16 common coniferous and deciduous hardwoods and shrubs on their annual decomposition patterns were studied on the H.J. Andrews Experimental Forest (Oregon). Leaf litters were characterized by their chemical qualities, which included measurement of elemental fractions (C, N, P, K, Ca, Mg), proximate fractions (non-polar, polar, acid-soluble extractives, acid-soluble lignin and acid-insoluble "Klason lignin"), and colorimetric characters (total phenolics, reactive polyphenolics, water-soluble carbohydrates, water-soluble condensed tannins, and water and acid-insoluble condensed tannins). These analytical methods improve upon traditional proximate analysis (Ryan et al. 1990) used to characterize leaf litters, through measurement of reactive and residual phenolic fractions and acid-soluble lignin. This paper discusses the procedures that are involved in improving proximate analysis and the link between leaf chemistry and one year
decomposition rates. Significant differences were found in leaf litter qualities and in
decomposition rates (expressed as decay) among species. The annual decay (k) for the leaf litter ranged from 0.27 to 1.02. The decay values for all species combined had highly significant (p [less than or equal to] 0.0001) correlations with 29 out of the 36 initial chemistry variables tested. The three highest correlations were with acid-insoluble
condensed tannins (r= 0.83 p [less than or equal to] 0.0001 n=339), the lignocellulose index (r= -0.81 p[less than or equal to] 0.0001, n=339) and acid-insoluble residue or 'Klason lignin" (r= -0.80 p [less than or equal to] 0.0001, n=339). A multiple regression model with all 16 species suggested that annual decomposition was best related to acid-insoluble condensed tannins, Klason lignin, water-insoluble condensed tannins, Ca and total phenolic:N ( R²=0.84, p [less than or equal] 0.0001, n= 339). Correlation and multiple linear regression models with each species' decay rate revealed that no one single initial chemical predictor could best explain the decomposition rates for each of the 16 species and that there were a wide range of chemical predictors related to the patterns of decomposition for each species.