Environmental Management

, Volume 59, Issue 1, pp 129–140 | Cite as

Accounting for the Impact of Management Scenarios on Typha Domingensis (Cattail) in an Everglades Wetland

  • Gareth Lagerwall
  • Gregory Kiker
  • Rafael Muñoz-Carpena
  • Naiming Wang


The coupled regional simulation model, and the transport and reaction simulation engine were recently adapted to simulate ecology, specifically Typha domingensis (Cattail) dynamics in the Everglades. While Cattail is a native Everglades species, it has become invasive over the years due to an altered habitat over the last few decades, taking over historically Cladium jamaicense (Sawgrass) areas. Two models of different levels of algorithmic complexity were developed in previous studies, and are used here to determine the impact of various management decisions on the average Cattail density within Water Conservation Area 2A in the Everglades. A Global Uncertainty and Sensitivity Analysis was conducted to test the importance of these management scenarios, as well as the effectiveness of using zonal statistics. Management scenarios included high, medium and low initial water depths, soil phosphorus concentrations, initial Cattail and Sawgrass densities, as well as annually alternating water depths and soil phosphorus concentrations, and a steadily decreasing soil phosphorus concentration. Analysis suggests that zonal statistics are good indicators of regional trends, and that high soil phosphorus concentration is a pre-requisite for expansive Cattail growth. It is a complex task to manage Cattail expansion in this region, requiring the close management and monitoring of water depth and soil phosphorus concentration, and possibly other factors not considered in the model complexities. However, this modeling framework with user-definable complexities and management scenarios, can be considered a useful tool in analyzing many more alternatives, which could be used to aid management decisions in the future.


Typha domingensis (Cattail) Regional simulation model Transport and reaction simulation engine Management scenarios Trend analysis Global uncertainty and sensitivity analysis 



Regional Simulation Model


coupled RSM TARSE model applied towards Ecology


Transport and Reaction Simulation Engine


South Florida Water Management District


South Florida Water Management Model


Water Conservation Area 2A


Hydrologic Simulation Engine


Global Uncertainty and Sensitivity Analysis


Comprehensive Everglades Restoration Plan


United States Army Corps of Engineers


Sequential Indicator Simulation


Delta Mean


Cattail Growth Factor


Sawgrass Growth Factor


Depth Management scenario


Phosphorus Management scenario



Financial support for this research was provided by the South Florida Water Management District and the U.S. Geological Survey—Water Resources Research Center at the University of Florida.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Submission Declaration

The work described herein has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), it is not under consideration for publication elsewhere, its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere including electronically in the same form, in English or in any other language, without the written consent of the copyright-holder.

Authors’ contributions

GL conducted the majority of the research, Global Uncertainty and Sensitivity Analysis, and writing of the paper. GK provided ecological modeling expertise, general guidance, paper writing, and review contributions. RMC provided invaluable guidance with the statistics, running the distributed model on the high performance computing cluster, and ensured that the general logic of the paper was maintained. NW provided RSM and WCA2A expertise, supplied raw vegetation maps, and provided critical review on model design. All authors read and approved the final manuscript.

Supplementary material

267_2016_769_MOESM1_ESM.pdf (983 kb)
Supplementary Information


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Gareth Lagerwall
    • 1
  • Gregory Kiker
    • 2
    • 3
  • Rafael Muñoz-Carpena
    • 4
  • Naiming Wang
    • 5
  1. 1.Room 202, Rabie Saunders BuildingUniversity of Kwa-Zulu NatalPietermaritzburgSouth Africa
  2. 2.Frazier Rogers HallUniversity of FloridaGainesvilleUSA
  3. 3.Honorary Associate Professor, School of Mathematics, Statistics and Computer ScienceUniversity of KwaZulu-NatalDurbanSouth Africa
  4. 4.Frazier Rogers HallUniversity of FloridaGainesvilleUSA
  5. 5.Hydrologic and Environmental Systems ModelingSouth Florida Water Management DistrictWest Palm BeachUSA

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