Understanding global ecological patterns and processes, from biogeochemical to biogeographical, requires broad‐scale macrosystems context for comparing and contrasting ecosystems. Climate gradients (precipitation and temperature) and other continental‐scale patterns shape freshwater environments due to their influences on terrestrial environments and their direct and indirect effects on the abiotic and biotic characteristics of lakes, streams, and wetlands. We combined literature review, analyses of open access data, and logical argument to assess abiotic and biotic characters of freshwater systems across gradients of latitude and elevation that drive precipitation, temperature, and other variability. We explored the predictive value of analyzing patterns in freshwater ecosystems at the global macrosystems scale. We found many patterns based on climate, particularly those dependent upon hydrologic characteristics and linked to characteristics of terrestrial biomes. For example, continental waters of dry areas will generally be widely dispersed and have higher probability of drying and network disconnection, greater temperatures, greater inorganic turbidity, greater salinity, and lower riparian canopy cover relative to areas with high precipitation. These factors will influence local community composition and ecosystem rates. Enough studies are now available at the continental or global scale to start to characterize patterns under a coherent conceptual framework, though considerable gaps exist in the tropics and less developed regions. We present illustrative global‐scale trends of abiotic, biotic, and anthropogenic impacts in freshwater ecosystems across gradients of precipitation and temperature to further understanding of broad‐scale trends and to aid prediction in the face of global change. We view freshwater systems as occurring across arrays of multiple gradients (including latitude, altitude, and precipitation) rather than areas with specific boundaries. While terrestrial biomes capture some variability along these gradients that influence freshwaters, other features such as, slope, geology, and historical glaciation also influence freshwaters. Our conceptual framework is not so much a single hypothesis as a way to logically characterize patterns in freshwaters at scales relevant to (1) evolutionary processes that give rise to freshwater biodiversity, (2) regulatory units that influence freshwater ecosystems, and (3) the current scope of anthropogenic impacts on freshwaters and the vital ecosystem services they provide.

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1. In streams, hydrology is a predominant driver of ecological structure and function.Providing adequate flows to support aquatic life, or environmental flows, is therefore a top management priority in stream systems.2. Flow regime classification is a widely accepted approach for establishing environmental flow guidelines. However, it is surprisingly difficult to quantify relationships between hydrology and ecology (flow-ecology relationships) while describing how these relationships vary across classified flow regimes. Developing such relationships is complicated by several sources of spatial bias, such as autocorrelation due to spatial design, flow regime classification and other environmental or ecological sources of spatial bias.3. We used mixed moving-average spatial stream network models to develop flowecology relationships across classified flow regimes and to assess spatial patterns of these relationships. We compared relationships between fish traits and lifehistory strategies with hydrologic metrics across flow regimes and assessed whether spatial autocorrelation influenced these relationships. Trait-hydrology relationships varied between flow regimes and across all streamscombined. Some relationships between traits and hydrologic metrics fit predictions based on life-history theory, while others exhibited unexpected relationships with hydrology. Spatial factors described a large proportion of variability in fish traits and different patterns of spatial autocorrelation were observed in different flow regimes. Synthesis and applications.Further work is needed to understand why flow-ecology relationships vary across classified flow regimes and why these relationships may not fit predictions based on life-history theories. Managers determining environmental flow standards need to be aware that different hydrologic metrics are often important drivers of fish trait diversity in different flow regimes. Flow-ecology relationships may therefore be confounded by spatial structure inherent in flow regime classification and much existing biological data. Complex patterns of spatial bias should be considered when managing stream systems within an environmental flows framework. K E Y W O R D Senvironmental flows, fish, hydrology, life-history strategies, spatial autocorrelation, spatial stream network models, streams, traits

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