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

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Abstract

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.

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Abbreviations

RSM:

Regional Simulation Model

RTE:

coupled RSM TARSE model applied towards Ecology

TARSE:

Transport and Reaction Simulation Engine

SFWMD:

South Florida Water Management District

SFWMM:

South Florida Water Management Model

WCA2A:

Water Conservation Area 2A

HSE:

Hydrologic Simulation Engine

GUSA:

Global Uncertainty and Sensitivity Analysis

CERP:

Comprehensive Everglades Restoration Plan

USACE:

United States Army Corps of Engineers

SIS:

Sequential Indicator Simulation

DM:

Delta Mean

CATGF:

Cattail Growth Factor

SAWGF:

Sawgrass Growth Factor

DepthMgmt:

Depth Management scenario

PMgmt:

Phosphorus Management scenario

References

  • Ascough JC, Maier HR, Ravalico JK, Strudley MW (2008) Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecol Model 219:383–399

    Article  Google Scholar 

  • Brown MT, Cohen MJ, Bardi E, Ingwersen WW (2006) Species diversity in the Florida Everglades, USA: a systems approach to calculating biodiversity. Aqua Sci 68:254–277

    Article  Google Scholar 

  • Chen ZM, Xia XH, Tang HS, Li SC, Deng Y (2010) Emergy based ecological assessment of constructed wetland for municipal wastewater treatment: methodology and application to the Beijing wetland. J Environ Inform 15(2):62–73

    Google Scholar 

  • DeBusk WF, Reddy KR, Koch MS, Wang Y (1994) Spatial distribution of soil nutrients in a nothern-Everglades marsh: water conservation area 2A. Soil Soc Am 58:543–552

    Article  Google Scholar 

  • Fitz CH, Kiker GA, Kim JB (2011) Integrated ecological modeling and decision analysis within the Everglades landscape. Environ Sci Technol 41:517–547

  • Fitz CH, Trimble B (2006) Everglades Landscape Model (ELM). http://my.sfwmd.gov/portal/page/portal/xweb%20-%20release%202/elm. Accessed 29 July 2016

  • Glennon R (2002) Water follies – Groundwater pumping and the fate of America’s fresh waters. Island Press, Washington, DC

    Google Scholar 

  • Grace JB (1989) Effects of water depth on Typha Latifolia and Typha domingensis. Am J Botany: 762-768.

  • Gross LJ (1996) ATLSS home page. http://atlss.org/. Accessed 31 July 2010.

  • Grunwald S, Ozborne TZ, Reddy KR (2008) Temporal trajectories of phosphorus and pedo-patterns mapped in water conservation Area 2, Everglades, Florida, USA. Geoderma 146:1–13

    Article  CAS  Google Scholar 

  • Grunwald S, Reddy KR, Newman S, DeBusk WF (2004) Spatial variability, distribution and uncertainty assessment of soil phosphorus in a South Florida Wetland. Environmetrics 15:811–825

    Article  CAS  Google Scholar 

  • Gunderson LH, Holling CS & Peterson GD (2001) Surprises and sustainability: cycles of renewal in the everglades. In: Panarchy: understanding transformations in human and natural systems. Island Press, Washington DC, pp 315–332.

  • Jawitz JW, Muñoz-Carpena R, Muller S, Grace KA, James AI (2008) Development, testing, and sensitivity and uncertainty analyses of a transport and reaction simulation engine (TARSE) for spatially distributed modeling of phosphorus in south Florida Peat Marsh Wetlands. Scientific Investigations Report 2008-5029. Reston, VA: United States Geological Survey.

  • Keen RE, Spain JD (1992) Computer simulation in biology. Wiley-Liss, New York

    Google Scholar 

  • Krysanova V, Hattermann F, Wechsung F (2007) Implications of complexity and uncertainty for integrated modeling and impact assessment in river basins. Environ Model Software 22:701–709

    Article  Google Scholar 

  • Lagerwall GL, Kiker GA, Muñoz-Carpena R, Convertino M, James A, Wang N (2012) A spatially distributed, deterministic approach to modeling Typha domingensis (Cattail) in an Everglades wetland. Ecol Proc 1(2012):10

    Article  Google Scholar 

  • Lagerwall G, Kiker GA, Muñoz-Carpena R, Wang N (2014) Global uncertainty and sensitivity analysis of a spatially distributed ecological model. Ecol Model 275:22–30

    Article  Google Scholar 

  • Layzer JA (2006) Ecosystem-based solutions: restoring the Florida Everglades. In: The environmental case. 2nd ed. CQPress, Washington DC, pp 404–435.

  • Lieske DJ, Bender DJ (2009) Accounting for the Influence of Geographic Location and Spatial Autocorrelation in Environmental Models: A Comparative Analysis Using North American Songbirds. J Environ Inform 13(1):12–32

    Article  Google Scholar 

  • Lilburne L & Tarantola S (2009) Sensitivity analysis of spatial models. Int J Geogr Inform Sci 23:151–168.

  • Miao, S.L. & Sklar, F.H. (1998) Biomass and nutrient allocation of Sawgrass and Cattail along a nutrient gradient in the Florida Everglades. Wetlands Ecol Manage 5:245.

  • Messina JP, Evans TP, Manson SM, Shortridge AM, Deadman PJ, Verburg PH (2008) Complex systems models and the management of error and uncertainty. J Land Use Sci 3(1):11–25

    Article  Google Scholar 

  • Muller S, Muñoz-Carpena R, Kiker G (2011) Model relevance: Frameworks for exploring the complexity-sensitivity-uncertainty trilemma. Book Chapter (pp. 35–67). Climate: Global hange and Local Adaption. In: I Linkov, T. S. Bridges. Springer Dordrecht/Boston/London. Published in cooperation with NATO Scientific Affairs Division.

  • Newman S, Schutte J, Grace J, Rutchey K, Fontaine T, Reddy K, Pietrucha M (1998) Factors influencing Cattail Abundance in the Northern Everglades. Aqua Botany 60: 265–280.

  • Odum HT, Odum EC & Brown MT (2000) Wetlands management, In: Environment and society in Florida, CRC Press, Boca Raton, FL, p 197.

  • Rutchey K, Schall T, Sklar F (2008) Development of vegetation maps for assessing Everglades restoration progress. Wetlands 172(2):806–816

    Article  Google Scholar 

  • Saltelli A, Chan K, Scott EM (2004) Sensitivity analysis. John Wiley & Sons Ltd, Chichester, UK

    Google Scholar 

  • SFWMD (2008a) RSM water quality user manual (DRAFT). South Florida Water Management District, West Palm Beach, FL, User Manual (draft)

    Google Scholar 

  • SFWMD (2008c) WCA2A HSE Setup. Overview document. South Florida Water management District, West Palm Beach, FL

    Google Scholar 

  • Sobol IM (2001) Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. IMACS 55:271–280

    Google Scholar 

  • Tarboton KC, Irizarry-Ortiz MM, Loucks DP, Davis SM, Obeysekera JT (2004) Habitat suitability indices for evaluating water management alternatives. South Florida Water Management District, West Palm Beach, FL

    Google Scholar 

  • Urban NH, Davis SM, Aumen NG (1993) Fluctuations in Sawgrass and Cattail densities in Everglades water conservation area 2A under varying nutrient, hydrologic, and fire regimes. Aqua Botany 46:203–223

    Article  CAS  Google Scholar 

  • USACE, S.F.R.O. (2010a) CERP: The Plan in Depth—Part 1. [Online]. http://www.evergladesplan.org/about/rest_plan_pt_01.aspx. Accessed 3 August 2010.

  • USACE, S.F.R.O. (2010b) CERP: The Plan in Depth—Part 2. [Online]. http://www.evergladesplan.org/about/rest_plan_pt_02.aspx. Accessed 3 August 2010.

  • Willard DA, 2010. SOFIA - FS-146-96. [Online]. http://sofia.usgs.gov/publications/fs/146-96/. Accessed 3 August 2010.

  • Wu Y, Sklar FH, Rutchey K (1997) Analysis and simulation of fragmentation patterns in the Everglades. Ecol Appl 7(1):268–276

    Article  Google Scholar 

  • Zajac ZB (2010) Global sensitivity and uncertainty analysis of spatially distributed watershed models. PhD. Dissertation. University of Florida, Gainesville, FL

  • Zheng C, Yang W, Yang ZF (2011) Strategies for managing environmental flows based on the spatial distribution of water quality: a case study of Baiyangdian Lake, China. J Environ Inform 18(2):84–90

    Article  Google Scholar 

Download references

Acknowledgments

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.

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Authors and Affiliations

  1. Room 202, Rabie Saunders Building, University of Kwa-Zulu Natal, Pietermaritzburg, KZN, 3209, South Africa

    Gareth Lagerwall

  2. Frazier Rogers Hall, University of Florida, PO Box 110570, Gainesville, FL, 32611-0570, USA

    Gregory Kiker

  3. Honorary Associate Professor, School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, KZN, Durban, South Africa

    Gregory Kiker

  4. Frazier Rogers Hall, University of Florida, PO Box 110570, Gainesville, FL, 32611-0570, USA

    Rafael Muñoz-Carpena

  5. Hydrologic and Environmental Systems Modeling, South Florida Water Management District, 3301 Gun Club Rd, West Palm Beach, FL, 33406, USA

    Naiming Wang

Authors
  1. Gareth Lagerwall
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  2. Gregory Kiker
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  3. Rafael Muñoz-Carpena
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  4. Naiming Wang
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Correspondence to Gareth Lagerwall.

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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.

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Lagerwall, G., Kiker, G., Muñoz-Carpena, R. et al. Accounting for the Impact of Management Scenarios on Typha Domingensis (Cattail) in an Everglades Wetland. Environmental Management 59, 129–140 (2017). https://doi.org/10.1007/s00267-016-0769-0

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