Predicting river light regimes and associated patterns in primary productivity

Abstract:

Light is a first order control on patterns of stream gross primary productivity (GPP) and evidence suggests that longitudinal patterns of light at the stream surface and GPP exist; however, the lack of widespread observations of lighting conditions experienced by stream autotrophs constrains our ability understand how light influences stream GPP. Incoming incident light above terrestrial canopies is influenced by both riparian and in-stream processes that reduce light available for stream autotrophs. Here, we build a biophysical model that considers these processes in series to estimate stream light environments. We used this model to predict GPP as a function of light and to assess the relative importance of factors mediating stream light regimes, and ultimately stream GPP. We applied our model across 120 U.S. rivers with varying site characteristics that have near-continuous estimates of GPP. Our estimates of GPP based only on light and simple assumptions were able to capture important seasonal patterns of GPP and broad-scale variation across sites. Our modeling approach allowed us to quantify the relative importance of processes mediating light availability on GPP and we found a point along the network continuum where the primary limitation on light availability shifts from riparian vegetation to in-stream changes in water depth and clarity. Accounting for each of these processes in succession improved our ability to make first approximations of daily rates of GPP based solely on light availability. Accurate estimates of stream light regimes facilitate baseline estimates of stream productivity and should enhance our ability to understand spatiotemporal patterns of GPP at network to continental scales.