Using the biomass-ratio and idiosyncratic hypotheses to predict mixed-species litter decomposition

A test is made of the acceptability of the biomass-ratio hypothesis (BMRH), operationalized as community-weighted means (CWMs), and of a new hypothesis (idiosyncratic annulment), for predicting the decomposition of multispecies litter mixtures. Specifically, (1) does the BMRH based on monoculture decomposition rates introduce systematic over- or underestimation of rates in mixtures? and (2) does the degree of variability of these rates decrease with increasing species richness (SR) beyond that expected from purely mathematical causes? Decomposition rates (mg g(1) d(1)) of litter from six tree species in microcosms were measured under controlled conditions during 18 weeks of incubation, alone and in all possible combinations of two, three, five and six species. Observed mixture decomposition rates were compared with those predicted by the BMRH using CWMs calculated from the monoculture rates, and the variability of the differences were compared with the SR of the mixture. Both positive and negative deviations from expectation occurred at all levels of SR. The average differences between observed rates of mixtures and those predicted were approximately zero. Although variability in the prediction errors was independent of the SR, this variability between different mixtures having the same number of species decreased with increasing SR such that mixtures with the most species converged on the predicted values. This decrease in variance was not due to idiosyncratic annulment of higher order interactions between species. The BMRH described the average response of litter mixtures. The decrease in variance and the convergence to the predicted values based on CWMs was not due to the oidiosyncratic annulment' of species interactions but was a mathematical consequence of CWMs being sums of random variables. Since convergence occurs with increasing SR and since SR increases with increasing spatial scale, the spatial scale will be a determinant in the prediction of ecosystem processes, such as litter decomposition rates.