Broad‐scale climate patterns combined with local flow and turbidity disturbances structure the seasonality of gross primary production in an aridland river

Both local and global climate phenomena shape the hydrologic regimes of watersheds. For aridland rivers in the southwestern United States, peak flows occur during two distinct periods: spring snowmelt and summer monsoons. Although discharge ( Q ) is a primary driver of variation in the production and consumption of instream organic matter, or stream metabolism, few connection have been made regarding how climate impacts ecosystem processes through changes in flow and related disturbances. We considered how variation in disturbance variables, specifically Q and associated changes in turbidity, affected gross primary production during spring snowmelt and summer monsoons in the Rio Grande. Nine years of continuous environmental data ( Q , turbidity, light) and climate indices (i.e., El Niño‐Southern Oscillation and Monsoon Index) were used to explain the variation in gross primary production estimates. We found that relationships were sensitive to the timescale of disturbance: at the seasonal scale, high snowmelt Q decreased spring mean gross primary production, while at the daily scale, high turbidity, and to a lesser extent Q , reduced gross primary production during summer. Also, mean Q and turbidity disturbances were uncoupled in spring and inversely related in summer. We conclude that long‐term datasets are essential to uncover emergent relationships between broad‐scale climate patterns and ecosystem processes and are necessary to better understand how hydroclimatic variability drives ecosystem processes at varying time scales in rivers across Earth.