Landscape Ecology

, Volume 27, Issue 1, pp 109–119

Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: a model study

  • Jiang Jiang
  • Donald L. DeAngelis
  • Thomas J. SmithIII
  • Su Yean Teh
  • Hock-Lye Koh
Research Article

Abstract

Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback.

Keywords

Individual-based model Positive feedback Environmental gradient Ecotone Vegetation aggregation Mangrove vegetation 

Supplementary material

10980_2011_9689_MOESM1_ESM.doc (154 kb)
Supplementary material 1 (DOC 154 kb)
10980_2011_9689_MOESM2_ESM.doc (180 kb)
Supplementary material 2 (DOC 180 kb)

References

  1. Anderson GH, Smith III TJ, Teague PD (2003) Variations in mangrove peat salinity from April 1997 to April 2003: a spatial analysis. Harney River Estuary, Everglades National Park, Annual Technical Presentations Meeting—SFWMD/USGS Cooperative Program. West Palm BeachGoogle Scholar
  2. Berger U, Hildenbrandt H (2000) A new approach to spatially explicit modelling of forest dynamics: spacing, ageing and neighbourhood competition of mangrove trees. Ecol Model 132(3):287–302CrossRefGoogle Scholar
  3. Berger U, Rivera-Monroy VH, Doyle TW, Dahdouh-Guebas F, Duke NC, Fontalvo-Herazo ML, Hildenbrandt H, Koedam N, Mehlig U, Piou C, Twilley RR (2008) Advances and limitations of individual-based models to analyze and predict dynamics of mangrove forests: a review. Aquat Bot 89(2):260–274Google Scholar
  4. Chen RG, Twilley RR (1998) A gap dynamic model of mangrove forest development along gradients of soil salinity and nutrient resources. J Ecol 86(1):37–51CrossRefGoogle Scholar
  5. Clements FE (1907) Plant physiology and ecology. Henry Holt, New YorkGoogle Scholar
  6. Clymo RS, Hayward PM (1982) The ecology of Sphagnum. In: Smith AJE (ed) Bryophyte ecology. Chapman and Hall, London, pp 229–289CrossRefGoogle Scholar
  7. Cutini M, Agostinelli E, Acosta TRA, Molina JA (2010) Coastal salt-marsh zonation in Tyrrhenian central Italy and its relationship with other Mediterranean wetlands. Plant Biosyst 144(1):1–11CrossRefGoogle Scholar
  8. Doyle TW, Girod GF (1997) The frequency and intensity of Atlantic hurricanes and their influence on the structure of South Florida Mangrove communities. In: Diaz HF, Pulwarty RS (eds) Hurricane, climate and socioeconomic impact. Springer Verlag, New York, pp 55–65Google Scholar
  9. Doyle TW, Girod GF, Brooks MA (2003) Modeling mangrove forest migration along the southwest coast of Florida under climate change. In: Ning ZH, Turner RE, Doyle TW, Abdollahi K (eds) Integrated assessment of the climate change impacts on the Gulf Coast Region. GRCCC and LSU Graphic Services, Baton Rouge, pp 211–221Google Scholar
  10. Eppinga M, Rietkerk M, Wassen M, De Ruiter P (2009) Linking habitat modification to catastrophic shifts and vegetation patterns in bogs. Plant Ecol 200(1):53–68CrossRefGoogle Scholar
  11. Grimm V, Revilla E, Berger U, Jeltsch F, Mooij WM, Railsback SF, Thulke H, Weiner J, Wiegand T, DeAngelis DL (2005) Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310(5750):987–991Google Scholar
  12. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman R, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198(1–2):115–126Google Scholar
  13. Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221(23):2760–2768CrossRefGoogle Scholar
  14. Larsen LG, Harvey JW, Crimaldi JP (2007) A delicate balance: ecohydrological feedbacks governing landscape morphology in a lotic peatland. Ecol Monogr 77:591–614CrossRefGoogle Scholar
  15. Lugo AE (1981) The inland mangroves of Inagua. J Nat Hist 15(5):845–852CrossRefGoogle Scholar
  16. Macchiato MF, Ragosta M, Cosmi C, Lo Porto A (1992) A method in multivariate statistics to analyze ecosystems starting from their species composition. Ecol Model 62(4):295–310CrossRefGoogle Scholar
  17. Manson FJ, Loneragan NR, Phinn SR (2003) Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs. Estuar Coast Shelf Sci 57(4):653–666CrossRefGoogle Scholar
  18. Martin PH, Fahey TJ, Sherman RE (2011) Vegetation zonation in a neotropical montane forest: environment, disturbance and ecotones. Biotropica: doi:10.1111/j.1744-7429.2010.00735.x
  19. Mutch RW (1970) Wildland fires and ecosystems—a hypothesis. Ecology 51(6):1046–1051CrossRefGoogle Scholar
  20. Oosting HJ (1955) The study of plant communities: an introduction to plant ecology. W. H. Freeman, San FranciscoGoogle Scholar
  21. Perry W (2004) Elements of South Florida’s comprehensive everglades restoration plan. Ecotoxicology 13(3):185–193PubMedCrossRefGoogle Scholar
  22. Pool DJ, Snedaker SC, Lugo AE (1977) Structure of mangrove forests in Florida, Puerto-Rico, Mexico, and Costa-Rica. Biotropica 9(3):195–212CrossRefGoogle Scholar
  23. Ross MS, O’Brien JJ, Flynn LJ (1992) Ecological site classification of Florida Keys terrestrial habitats. Biotropica 24(4):488–502CrossRefGoogle Scholar
  24. Semeniuk V (1983) Mangrove distribution in northwestern Australia in relationship to regional and local fresh-water seepage. Vegetatio 53(1):11–31CrossRefGoogle Scholar
  25. Shugart HH, Emanuel WR, West DC, DeAngelis DL (1980) Environmental gradients in a simulation model of a beech-yellow-poplar stand. Math Biosci 50(3–4):163–170CrossRefGoogle Scholar
  26. Siccama TG (1974) Vegetation, soil, and climate on the Green Mountains of Vermont. Ecol Monogr 44(3):325–349CrossRefGoogle Scholar
  27. Snyder JR, Herndon A, Robertson WBJ (1990) South Florida rockland. In: Myers RL, Ewel JJ (eds) Ecosystems of Florida. The University of Central Florida Press, Orlando, pp 230–279Google Scholar
  28. Sternberg LDL, Ishshalomgordon N, Ross M, Obrien J (1991) Water relations of coastal plant-communities near the ocean fresh-water boundary. Oecologia 88(3):305–310CrossRefGoogle Scholar
  29. Sternberg LDL, Teh SY, Ewe SML, Miralles-Wilhelm F, DeAngelis DL (2007) Competition between hardwood hammocks and mangroves. Ecosystems 10(4):648–660CrossRefGoogle Scholar
  30. Stoddart DR, Bryan GW, Gibbs PE (1973) Inland mangroves and water chemistry, Barbuda, West Indies. J Nat Hist 7(1):33–46CrossRefGoogle Scholar
  31. Swain ED, Wolfert MA, Bales JD, Goodwin CR (2003) Two-dimensional hydrodynamic simulation of surface-water flow and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS). U.S. Geological Survey Water-Resources Investigations Report 03-4287Google Scholar
  32. Teh SY, DeAngelis DL, Sternberg LDL, Miralles-Wilhelm FR, Smith TJ, Koh HL (2008) A simulation model for projecting changes in salinity concentrations and species dominance in the coastal margin habitats of the Everglades. Ecol Model 213(2):245–256CrossRefGoogle Scholar
  33. Transeau EN (1935) The prairie Peninsula. Ecology 16(3):423–437CrossRefGoogle Scholar
  34. van Breemen N (1995) How Sphagnum bogs down other plants. Trends Ecol Evol (Personal edition) 10(7):270–275Google Scholar
  35. Walker S, Wilson JB, Steel JB, Rapson GL, Smith B, King WM, Cottam YH (2003) Properties of ecotones: evidence from five ecotones objectively determined from a coastal vegetation gradient. J Veg Sci 14(4):579–590Google Scholar
  36. Wiegand T, Camarero JJ, Rüger N, Gutiérrez E (2006) Abrupt population changes in treeline ecotones along smooth gradients. J Ecol 94(4):880–892CrossRefGoogle Scholar
  37. Williams K, MacDonald M, LdSL Sternberg (2003) Interactions of storm, drought, and sea-level rise on coastal forest: a case study. J Coast Res 19(4):1116–1121Google Scholar
  38. Wilson AM (2005) Fresh and saline groundwater discharge to the ocean: a regional perspective. Water Resour Res 41(2):doi:0.1029/2004wr003399
  39. Wilson JB, Agnew DQ (1992) Positive-feedback switches in plant communities. Adv Ecol Res 23:263–336CrossRefGoogle Scholar
  40. Zeng Y, Malanson GP (2006) Endogenous fractal dynamics at alpine treeline ecotones. Geograph Anal 38(3):271–287CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. (outside the USA) 2011

Authors and Affiliations

  • Jiang Jiang
    • 1
  • Donald L. DeAngelis
    • 1
    • 2
  • Thomas J. SmithIII
    • 2
  • Su Yean Teh
    • 3
  • Hock-Lye Koh
    • 4
  1. 1.Department of BiologyUniversity of MiamiCoral GablesUSA
  2. 2.U. S. Geological SurveySoutheast Ecological Science CenterSt. PetersburgUSA
  3. 3.School of Mathematical SciencesUniversiti Sains MalaysiaMindenMalaysia
  4. 4.Disaster Research Nexus, School of Civil EngineeringUniversiti Sains MalaysiaNibong TebalMalaysia

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