Temperate streams are among the most well studied ecosystems in the world, yet there remains much uncertainty regarding the processes that regulate food web structure. Here we explore the relative contribution of internal food web factors (e.g. functional group composition) and external watershed factors on inter-stream variation in individual size spectra slopes (λ). Size spectra analysis is an ataxic approach that describes the decrease in abundance with increasing body size of individuals within a community (N∼M λ). The slope of the relationship, represented by λ, describes food web size structure and trophic efficiency. The size spectra approach has been used to examine aquatic food web responses to commercial fisheries, climate change, invasive species, and nutrient pollution among other environmental perturbations. We used Bayesian hierarchical generalized mixed models to estimate λ for benthic macroinvertebrate, fish, and combined food webs while simultaneously testing a variety of internal food web and external watershed variables that were hypothesized to influence inter-site variation in λ. The mean λ for combined and invertebrate food webs (mean = -2.04 and -2.02 respectively, range -2.58 to -1.51) aligned well with theoretic predictions (-2.0). In contrast, the mean fish slope was shallower and more variable among sites (mean = -1.85, range = -2.71 to -1.33). Interestingly, the only factor that influenced the fish-only and combined size spectra was watershed drainage area, which showed a positive relationship, suggesting that larger watersheds likely have a larger diversity and stability of energy sources. Meanwhile, invertebrate size spectra was similarly influenced by drainage area, but the percent agricultural lands and variance in watershed slope both also demonstrated a positive effect (increased efficiency), while the proportion of omnivore and predator biomass within the invertebrate assemblage had negative relationships (decreasing efficiency). Size spectra analyses simplify food web processes allowing for greater insight into factors structuring food webs.