Decomposition of organic matter is a fundamental ecosystem process that is mediated by the activities of microbes and detritivores that respond to variation in litter quality and environmental factors. Temperature, nutrient supply and the chemistry of leaf litter are three factors with strong influence over decomposition rates. Yet, we still have little understanding of how nutrient regimes interact with litter quality to affect the temperature sensitivity of decomposition in streams and rivers. This is a critical gap, given that water temperature, nutrient regimes and riparian vegetation are altered by human activities. This project applies a metabolic theory framework to test whether the temperature sensitivity of leaf-litter and cotton strip decomposition by microbes and detritivores varies across lotic systems of different nutrient status, as quantified by nitrogen and phosphorus concentrations. We use breakdown rates from global syntheses of litter and cotton strip decomposition assays (MASSLOSS and CELLDEX projects) that span gradients in nutrient supply and substrate lability to test several hypotheses. Previous studies have observed that decomposition mediated by detritivores has a stronger temperature sensitivity than decomposition mediated by microbes. Mild to moderate nutrient fertilization stimulates decomposition rates. We predict that the average rates of decomposition will differ between systems categorized as oligotrophic, mesotrophic and eutrophic, but not affect the activation energy of decomposition mediated by microbes or detritivores. However, we expect the effect on nutrients on average decomposition rate will be more pronounced for processing mediated by detritivores relative to microbes, given that microbes can sequester water column nutrients. Nutrient-poor, carbon-rich organic substrates are associated with a greater temperature sensitivity relative to nutrient-rich and structurally less complex substrates. We thus predict that eutrophication will cause the temperature sensitivity of nutrient-poor substrates to weaken, but have little effect on the temperature sensitivity of nutrient-rich substrates. Finally, we will use linear mixed effect regression to model the individual and interacting effects of temperature, nutrients and substrate chemistry on decomposition to more robustly quantify temperature sensitivity. Results from this study will improve predictions of how shifts in thermal regimes will affect organic-matter processing across systems with varying nutrient supply and detrital quality.