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Multi‐state succession in wetlands: a novel use of state and transition models
Author(s) -
Zweig C. L.,
Kitchens W. M.
Publication year - 2009
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/08-1392.1
Subject(s) - ecological succession , wetland , vegetation (pathology) , alternative stable state , ecosystem , environmental science , ecology , multivariate statistics , range (aeronautics) , peat , hydrology (agriculture) , environmental resource management , geography , geology , mathematics , biology , statistics , medicine , materials science , geotechnical engineering , pathology , composite material
The complexity of ecosystems and mechanisms of succession are often simplified by linear and mathematical models used to understand and predict system behavior. Such models often do not incorporate multivariate, nonlinear feedbacks in pattern and process that include multiple scales of organization inherent within real‐world systems. Wetlands are ecosystems with unique, nonlinear patterns of succession due to the regular, but often inconstant, presence of water on the landscape. We develop a general, nonspatial state and transition (S and T) succession conceptual model for wetlands and apply the general framework by creating annotated succession/management models and hypotheses for use in impact analysis on a portion of an imperiled wetland. The S and T models for our study area, Water Conservation Area 3A South (WCA3), Florida, USA, included hydrologic and peat depth values from multivariate analyses and classification and regression trees. We used the freeware Vegetation Dynamics Development Tool as an exploratory application to evaluate our S and T models with different management actions (equal chance [a control condition], deeper conditions, dry conditions, and increased hydrologic range) for three communities: slough, sawgrass ( Cladium jamaicense ), and wet prairie. Deeper conditions and increased hydrologic range behaved similarly, with the transition of community states to deeper states, particularly for sawgrass and slough. Hydrology is the primary mechanism for multi‐state transitions within our study period, and we show both an immediate and lagged effect on vegetation, depending on community state. We consider these S and T succession models as a fraction of the framework for the Everglades. They are hypotheses for use in adaptive management, represent the community response to hydrology, and illustrate which aspects of hydrologic variability are important to community structure. We intend for these models to act as a foundation for further restoration management and experimentation which will refine transition and threshold concepts.