Skip to main content
Log in

Determining an appropriate minimum mapping unit in vegetation mapping for ecosystem restoration: a case study from the Everglades, USA

  • Research Article
  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

This paper documents the analyses that were conducted with regards to investigating an appropriate Minimum Mapping Unit (MMU) to be used to capture the potential changes in vegetation patterns for a 10,924 square km restoration project being conducted in south Florida, USA. Spatial landscape and class metrics that were shown to change predictably with increasing grain size were adopted from previous studies and applied to a multi-scale analysis. Specifically, this study examines the effects of changing grain size on landscape metrics, utilizing empirical data from a real landscape encompassing 234,913 ha of south Florida’s Everglades. The objective was to identify critical thresholds within landscape metrics, which can be used to provide insight in determining an appropriate MMU for vegetation mapping. Results from this study demonstrate that vegetation heterogeneity will exhibit dissimilar patterns when investigating the loss of information within landscape and class metrics, as grain size is increased. These results also support previous findings that suggest that landscape metric “scalograms” (the response curves of landscape metrics to changing grain size), are more likely to be successful for linking landscape pattern to ecological processes as both pattern and process in ecological systems often operate on multiple scales. This study also incorporates an economic cost for various grain dependant vegetation mapping scales. A final selection of the 50 × 50 m grain size for mapping vegetation was based on this study’s investigation of the “scalograms”, the costs, and a composite best professional judgment of seasoned scientists having extensive experience within these ecosystems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Benson BJ, MacKenzie MD (1995) Effects of sensor spatial resolution on landscape structure parameters. Landscape Ecol 10(2):113–120

    Article  Google Scholar 

  • Costanza R, Maxwell T (1994) Resolution and predictability: an approach to the scaling problem. Landscape Ecol 9(1):47–57

    Article  Google Scholar 

  • Cullinan VI, Thomas JM (1992) A comparison of quantitative methods for examining landscape pattern and scale. Landscape Ecol 7(3):211–227

    Article  Google Scholar 

  • Ferriter A, Doren B, Winston R, Thayer D, Miller B, Thomas B, Barrett M, Pernas T, Hardin S, Lane J, Kobza M, Schmitz D, Bodle M, Toth L, Rodgers L, Pratt P, Snow S, Goodyear C (2008) Chapter 9: the status of non-indigenous species in the South Florida environment. In: 2008 South Florida Environmental Report. South Florida Water Management District, West Palm Beach, p 57

    Google Scholar 

  • Forman RTT (1995) Land mosaics: the ecology of landscapes and regions. Cambridge University Press, Cambridge

    Google Scholar 

  • Haines-Young R, Chopping M (1996) Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Prog Phys Geogr 20:418–445

    Article  Google Scholar 

  • Hay GJ, Marceau DJ, Dube P, Bouchard A (2001) A multiscale framework for landscape analysis: object-specific analysis and upscaling. Landscape Ecol 16:471–490

    Article  Google Scholar 

  • Jones DT, Madden M, Snyder J, Rutchey K (1999) A vegetation classification system for Southern Florida’s national parks and preserves. South Florida natural resources center technical report, Everglades national park, national park service. U.S. Department of the Interior, Homestead

    Google Scholar 

  • McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. General technical report PNW-GTR-351, USDA, forest service. Pacific Northwest Research Station, Portland

    Google Scholar 

  • Obeysekera J, Rutchey K (1997) Selection of scale for Everglades landscape models. Landscape Ecol 12(1):7–18

    Article  Google Scholar 

  • Openshaw S (1984) The modifiable areal unit problem. Geo Books, Norwich

    Google Scholar 

  • Qi Y, Wu J (1996) Effects of changing spatial resolution on the results of landscape pattern analysis using spatial autocorrelation indices. Landscape Ecol 11(1):39–49

    Article  Google Scholar 

  • RECOVER (2004a) Restoration coordination and verification (RECOVER) program management plan. South Florida Water Management District, West Palm Beach, Florida, and United States Army Corps of Engineers. Jacksonville District, Jacksonville

    Google Scholar 

  • RECOVER (2004b) CERP monitoring and assessment plan: part 1 monitoring and supporting research: restoration coordination and verification (RECOVER). United States Army Corps of Engineers, Jacksonville District, Jacksonville, Florida. South Florida Water Management District, West Palm Beach

    Google Scholar 

  • Rutchey K, Vilchek L, Love M (2005) Development of a vegetation map for water conservation area 3. Technical publication ERA #421. South Florida Water Management District, West Palm Beach

    Google Scholar 

  • Rutchey K, Schall TN, Doren RF, Atkinson A, Ross MS, Jones DT, Madden M, Vilchek L, Bradley KA, Snyder JR, Burch JN, Pernas T, Witcher B, Pyne M, White R, Smith TJIII, Sadle J, Smith CS, Patterson ME, Gann GD (2006) Vegetation classification for South Florida natural areas. United States Geological Survey, Open-File Report 2006-1240, Saint Petersburg

    Google Scholar 

  • Rutchey K, Schall TN, Sklar FH (2008) Development of vegetation maps for assessing Everglades restoration progress. Wetlands 28(3):806–816

    Article  Google Scholar 

  • Saura S (2002) Effects of minimum mapping unit on land cover data spatial configuration and composition. Int J Remote Sens 23(22):4853–4880

    Article  Google Scholar 

  • Sklar FH, van der Valk AG (eds) (2002) Tree island of the Everglades. Kluwer Academic Publishers, Boston

    Google Scholar 

  • Snedecor GW, Cochran WG (1978) Statistical methods, 6th edn. Iowa State University, Ames, p 593

    Google Scholar 

  • Stohlgren TJ, Chong GW, Kalkhan MA, Schell LD (1997) Multiscale sampling of plant diversity: effects of minimum mapping unit size. Ecol Appl 7(3):1064–1074

    Article  Google Scholar 

  • Turner MG, O’Neill RV, Gardner RH, Milne BT (1989) Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecol 3:153–162

    Article  Google Scholar 

  • U.S. Congress (2000) Sect. 601 of the Water Resources Development Act of 2000 (Public Law 106-541). Washington, DC

  • Wu J (2004) Effects of changing scale on landscape pattern analysis: scaling relations. Landscape Ecol 19:125–138

    Article  Google Scholar 

  • Wu J, Hobbs R (2002) Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landscape Ecol 17:355–365

    Article  Google Scholar 

  • Wu J, Li H (2006) Chapter 1: concepts of scale and scaling. In: Wu J, Jones KB, Li H, Loucks OL (eds) Scaling and uncertainty analysis in ecology. Springer, Dordrecht, pp 3–15

    Chapter  Google Scholar 

  • Wu Y, Sklar FH, Rutchey K (1997) Analysis and simulations of fragmentation patterns in the everglades. Ecol Appl 7(1):228–276

    Article  Google Scholar 

  • Wu J, Shen W, Sun W, Tueller PT (2002) Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecol 17:761–782

    Article  Google Scholar 

  • Wu J, Jones KB, Li H, Loucks OL (2006a) Chapter 18: scaling with known uncertainty: a synthesis. In: Wu J, Jones KB, Li H, Loucks OL (eds) Scaling and uncertainty analysis in ecology. Springer, Dordrecht, pp 329–346

    Chapter  Google Scholar 

  • Wu Y, Wang N, Rutchey K (2006b) An analysis of spatial complexity of ridge and slough patterns in the Everglades ecosystem. Ecol Complex 3:183–192

    Article  Google Scholar 

  • Xiangyun X, Gertner G, Wang G, Anderson B (2005) Optimal sampling scheme for estimation landscape mapping of vegetation cover. Landscape Ecol 20:375–387

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ken Rutchey.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rutchey, K., Godin, J. Determining an appropriate minimum mapping unit in vegetation mapping for ecosystem restoration: a case study from the Everglades, USA. Landscape Ecol 24, 1351–1362 (2009). https://doi.org/10.1007/s10980-009-9387-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10980-009-9387-z

Keywords

Navigation