Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10144354 | Ecological Engineering | 2018 | 15 Pages |
Abstract
Tools that provide decision makers with an understanding of ecosystem response to changes in streamflow attributes are necessary to balance human and ecosystem water needs. Flow response curves provide one such approach for informing management based on modeled relationships between environmental control (e.g., flood magnitude) and response (e.g., plant recruitment) variables, although unidirectional relationships may fail to capture the complex interactions between ecological and physical processes in riparian ecosystems. We take advantage of the linkage between plant functional traits important for (a) determining a plant's response to environmental conditions and (b) for predicting its impact on the flow of water and transport of sediment, to build a predictive model of riparian ecosystem dynamics. By using plant functional groups (i.e., guilds), our model accounts for process linkages among streamflow properties, physical processes, and plant community response. The model relies on a series of flow response curves built and tested with data collected along semiarid, canyon-bound rivers in Colorado. We built 2D hydrodynamic models and updated them with a flexible vegetation module to represent plant-hydraulic interactions for three study reaches. Plant guild distributions are well described by the model while predictions of the occurrence and direction of topographic change are less deterministic. Our work is among the first to develop response curves for both physical and ecological processes in the same framework. The shape of the resulting curves indicate that the functioning of riparian ecosystems is driven by nonlinear relationships and that clear, identifiable thresholds exist. As such, changes to the flow regime will have a differential impact on physical and ecological processes, depending on the nature of the shift. We discuss the strength and limitations of our model and make suggestions about its applicability to river management.
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Authors
Rebecca M. Diehl, Andrew C. Wilcox, David M. Merritt, Dustin W. Perkins, Julian A. Scott,