The Stream Biome Gradient Concept: factors controlling lotic systems across broad biogeographic scales



Citation: Dodds, W. K., Gido, K., Whiles, M. R., Daniels, M. D., & Grudzinski, B. P. (2015). The Stream Biome Gradient Concept: factors controlling lotic systems across broad biogeographic scales. Freshwater Science, 34(1), 1-19. doi:10.1086/679756
We propose the Stream Biome Gradient Concept as a way to predict macroscale biological patterns in streams. This concept is based on the hypothesis that many abiotic and biotic features of streams change predictably along climate (temperature and precipitation) gradients because of direct influences of climate on hydrology, geomorphology, and interactions mediated by terrestrial vegetation. The Stream Biome Gradient Concept generates testable hypotheses related to continental variation among streams worldwide and allows aquatic scientists to understand how results from one biome might apply to a less-studied biome. Some predicted factors change monotonically across the biome/climate gradients, whereas others have maxima or minima in the central portion of the gradient. For example, predictions across the gradient from drier deserts through grasslands to wetter forests include more permanent flow, less bare ground, lower erosion and sediment transport rates, decreased importance of autochthonous C inputs to food webs, and greater stream animal species richness. In contrast, effects of large ungulate grazers on streams are expected to be greater in grasslands than in forests or deserts, and fire is expected to have weaker effects in grassland streams than in desert and forest streams along biome gradients with changing precipitation and constant latitude or elevation. Understanding historic patterns among biomes can help describe the evolutionary template at relevant biogeographic scales, can be used to broaden other conceptual models of stream ecology, and could lead to better management and conservation across the broadest scales.


Stream, Biome, Lotic, Macro-Scale, Macrosystems, Biogeography