title: Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.
abstract: Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA) historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal) hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1) this mechanism can produce spontaneous divergence of local elevation; 2) divergent and homogenous states can exhibit global bi-stability; and 3) feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.
authors.affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina, USA. james.heffernan@duke.edu
authors.forename: James B
authors.initials: JB
authors.lastname: Heffernan
authors.forename: Danielle L
authors.initials: DL
authors.lastname: Watts
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Cohen
mesh_terms: D000465:Algorithms; D003247:Conservation of Natural Resources; D017753:Ecosystem; D004784:Environmental Monitoring; D005431:Florida; D008962:Models, Theoretical; D014872:Water Movements; D053833:Wetlands