Hydrological and biogeochemical controls on watershed dissolved organic matter transport: pulse-shunt concept.

Hydrological precipitation and snowmelt events trigger large "pulse" releases of terrestrial dissolved organic matter (DOM) into drainage networks due to an increase in DOM concentration with discharge. Thus, low-frequency large events, which are predicted to increase with climate change, are responsible for a significant percentage of annual terrestrial DOM input to drainage networks. These same events are accompanied by marked and rapid increases in headwater stream velocity; thus they also "shunt" a large proportion of the pulsed DOM to downstream, higher-order rivers and aquatic ecosystems geographically removed from the DOM source of origin. Here we merge these ideas into the "pulse-shunt concept" (PSC) to explain and quantify how infrequent, yet major hydrologic events may drive the timing, flux, geographical dispersion, and regional metabolism of terrestrial DOM. The PSC also helps reconcile long-standing discrepancies in C cycling theory and provides a robust framework for better quantifying its highly dynamic role in the global C cycle. The PSC adds a critical temporal dimension to linear organic matter removal dynamics postulated by the river continuum concept. It also can be represented mathematically through a model that is based on stream scaling approaches suitable for quantifying the important role of streams and rivers in the global C cycle. Initial hypotheses generated by the PSC include: (1) Infrequent large storms and snowmelt events account for a large and underappreciated percentage of the terrestrial DOM flux to drainage networks at annual and decadal time scales and therefore event statistics are equally important to total discharge when determining terrestrial fluxes. (2) Episodic hydrologic events result in DOM bypassing headwater streams and being metabolized in large rivers and exported to coastal systems. We propose that the PSC provides a framework for watershed biogeochemical modeling and predictions and discuss implications to ecological processes.