5 years ago

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template [Ecology]

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template [Ecology]
Xiaoli Dong, Albert Ruhi, Nancy B. Grimm

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

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