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Abstract The hydrological effects of climate change are documented in many regions; however, climate-driven impacts to the source and transport of river nutrients remain poorly understood. Understanding the factors controlling nutrient dynamics across river systems is critical to preserve ecosystem function yet challenging given the complexity of landscape and climate interactions. Here, we harness a large regional dataset of nitrate (NO₃^–) yield, concentration, and isotopic composition (δ¹⁵N and δ¹⁸O) to evaluate the strength of hydroclimate and landscape variables in controlling the seasonal source and transport of NO₃^–. We show that hydroclimate strongly influenced the seasonality of river NO₃^–, producing distinct, source-dependent NO₃^–regimes across rivers from two mountain ranges. Riverine responses to hydroclimate were also constrained by watershed-scale topographic features, demonstrating that while regional climate strongly influences the timing of river NO₃^–transport, watershed topography plays a distinct role in mediating the sensitivity of river NO₃^–dynamics to future change. 

Large river systems, particularly those shared by developing nations in the tropics, exemplify the interconnected and thorny challenges of achieving sustainability with respect to food, energy, and water ( 1 ). Numerous countries in South America, Africa, and Asia have committed to hydropower as a means to supply affordable energy with net-zero emissions by 2050 ( 2 ). The placement, size, and number of dams within each river basin network have enormous consequences for not only the ability to produce electricity ( 3 ) but also how they affect people whose livelihoods depend on the local river systems ( 4 ). On page 753 of this issue, Flecker et al. ( 5 ) present a way to assess a rich set of environmental parameters for an optimization analysis to efficiently sort through an enormous number of possible combinations for dam placements and help find the combination(s) that can achieve energy production targets while minimizing environmental costs in the Amazon basin. 

Williams et al . claim that the data used in Sabo et al . were improperly scaled to account for fishing effort, thereby invalidating the analysis. Here, we reanalyze the data rescaled per Williams et al . and following the methods in Sabo et al . Our original conclusions are robust to rescaling, thereby invalidating the assertion that our original analysis is invalid.