Litter Decomposition and Scaling Theory

Litter decomposition is probably one of the best researched ecosystem processes. It is central to the recycling of plant nutrients within systems and is the energy channel through which much of the soil food web is sustained. The dominant conceptual model of litter decomposition posits that the primary controls on the rate of decomposition are climate, litter quality and decomposer organisms. These controls are hypothesized to operate hierarchically in space, with climate and litter quality co-dominant at regional to global scales; whereas decomposers operate only as an additional local control whose effect is negligible at broader scales. Consequently, decomposers have been omitted as controls from biogeochemical models. Yet evidence that microbial decomposers regulate decomposition rates at regional- to global-scales, independent of climate variables such as temperature and moisture, is generally lacking. One possibility for this lack of evidence is suggested by scaling theory, where the influence of mechanisms that act locally can be obscured in emergent, broad-scale patterns.

Pattern and scale has been described as the central issue in ecology, where the inherent challenge to prediction and understanding lies in the elucidation of mechanisms, which commonly operate at different scales to those on which the patterns are observed. We investigate how such scale mismatches in observation versus mechanism influence our understanding of controls on ecosystem processes, using litter decomposition as a representative process. We do this because litter decomposition is controlled by variables operating at finer scales than those at which the variables are typically measured and evaluated. In particular, the hierarchical model of litter decomposition is conceptually grounded in local (i.e. microsite) dynamics, but has been developed and substantiated with data collected at coarser scales of resolution (typically site-level). We are carrying out a series of field experiments to quantify the effect sizes of different controls on decomposition rates when observed at the same fine spatial grains at which they operate; and how this new understanding affects forecasting of broad-scale decomposition patterns.

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