Linking metrics of landscape pattern to hydrological process in a lotic wetland
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Strong reciprocal interactions exist between landscape patterns and ecological processes. In wetlands, hydrology is the dominant abiotic driver of ecological processes and both controls, and is controlled, by vegetation presence and patterning. We focus on binary patterning in the Everglades ridge-slough landscape, where longitudinally connected flow, principally in sloughs, is integral to landscape function. Patterning controls discharge competence in this low-gradient peatland, with important feedbacks on hydroperiod and thus peat accretion and patch transitions.
To quantitatively predict pattern effects on hydrologic connectivity and thus hydroperiod.
We evaluated three pattern metrics that vary in their hydrologic specificity. (1) Landscape discharge competence considers elongation and patch-type density that capture geostatistical landscape features. (2) Directional connectivity index (DCI) extracts both flow path and direction based on graph theory. (3) Least flow cost (LFC) is based on a global spatial distance algorithm strongly analogous to landscape water routing, where ridges have higher flow cost than sloughs because of their elevation and vegetation structure. Metrics were evaluated in comparison to hydroperiod estimated using a numerically intensive hydrologic model for synthetic landscapes. Fitted relationships between metrics and hydroperiod for synthetic landscapes were extrapolated to contemporary and historical maps to explore hydroperiod trends in space and time.
Both LFC and DCI were excellent predictors of hydroperiod and useful for diagnosing how the modern landscape has reorganized in response to modified hydrology.
Metric simplicity and performance indicates potential to provide hydrologically explicit, computationally simple, and spatially independent predictions of landscape hydrology, and thus effectively measure of restoration performance.
KeywordsSpatial metrics Connectivity Hydrology Hydroperiod Ridge and slough Wetland Everglades
We would like to thank Likai Zhu for his assistance in Python programming and R scripting. Danielle Watts, Jim Heffernan, Joseph Delesantro, Stephen Casey and Jim Jawitz have all been invaluable resources for discussing the ideas presented in this work. We also acknowledge the constructive inputs from two anonymous reviewers whose suggestions greatly improved the paper.
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