Scott D. Tiegs

The decomposition of organic matter is a fundamental ecosystem‐level process that governs nutrient cycling, fuels ecosystems, and impacts our global climate. Despite the central importance of this process for ecosystems across the planet, little is known about how the capacity of ecosystems to decompose organic matter—that is, their decomposition potential—varies across time and space. Closing this gap is needed to provide baseline information on the dynamics of ecosystems, for tracking anthropogenic impacts, and for development of practical and efficient sampling procedures. For nine consecutive years during the months of July–August, we deployed an identical organic‐matter decomposition assay in the same 26 temperate deciduous‐forest streams (234 stream‐years total) to evaluate the interannual and among‐stream variation in the decomposition of organic matter. Decomposition rates (as k values) ranged widely across all stream‐years (mean = 0.026, SD = 0.018, range = 0.0020–0.094). Interestingly, among‐stream variation, expressed on a per‐stream basis, was more than three times greater than interannual variation (expressed on a per year basis), explaining 75% and 22% of the overall variation in our dataset, respectively. Removing the effects of temperature by adjusting decomposition rates for degree days did not substantially impact this pattern (stream: 80% of variation, year: 17% of variation). Surprisingly, despite large differences in temperature among streams, temperature explained little variation in decomposition rates, pointing to the importance of other factors. When compared to the decomposition rates from stream sites across the planet, the rates presented here spanned 27.3% of this range, highlighting the diversity of decomposition rates that can be found in a relatively compact geographic area. From the perspective of using organic‐matter decomposition as a bioassessment tool, this variation could limit the sensitivity of decomposition‐based assays to human impacts, although study designs could be utilized to ameliorate this problem (e.g., those that stratify by geology). The results and dataset presented here are a needed step toward a more complete understanding of how ecosystem processes vary across time and space.