Classification of Natural and Semi-natural Vegetation

Vegetation Ecology: Second Edition

Volumn , Issue , 2013, Pages 28-70

  Peet, Robert K ^a   Roberts, David W ^b  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b MONTANA STATE UNIVERSITY   (United States)

Author keywords

Braun Blanquet; Fidelity; Hierarchical agglomerative clustering; Hierarchical divisive clustering; Non hierarchical partitioning; Standardization; Table sorting; Taxa; US National Vegetation Classification; Vegetation classification

Indexed keywords

EID: 84886514536     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781118452592.ch2     Document Type: Chapter

References (132)

1. Aho, K., Roberts, D.W. & Weaver, T. (2008) Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods. Journal of Vegetation Science 19, 549-562.
2. Allen, R.B. (1992) RECCE: an inventory method for describing New Zealand's vegetation cover. Forestry Research Institute Bulletin 176. FRI, Christchurch, New Zealand.
3. Anderson, M., Bourgeron, P., Bryer, M.T. et al. (1998) International Classification of Ecological Communities: Terrestrial Vegetation of the United States. Volume II. The National Vegetation Classification System: List of Types. The Nature Conservancy, Arlington, VA.
4. Austin, M.P. & Heyligers, P.C. (1989) Vegetation survey design for conservation: Gradsect sampling of forests in Northeastern New South Wales. Biological Conservation 50, 13-32.
5. Austin, M.P. & Heyligers, P.C. (1992) New approaches to vegetation survey design: Gradsect sampling. In: Nature Conservation: Cost Effective Biological Surveys and Data Analysis, (eds C.R. Margules & M.P. Austin), pp. 31-37. CSIRO, Melbourne, VIC.
6. Austin, M.P. & Smith, T.M. (1989) A new model for the continuum concept. Vegetatio 83, 35-47.
7. Bailey, R.G. (1976) Ecoregions of the United States (map). U.S. Forest Service, Intermountain Region, Ogden, UT.
8. Beals, E.W. (1984) Bray-Curtis ordination: an effective strategy for analysis of multivariate ecological data. Advances in Ecological Research 14, 1-55.
9. Bechtold, W.A. & Patterson, P.L. (2004) The enhanced Forest Inventory and Analysis Program-national sampling design and estimation procedures. General Technical Report SRS-80. U.S. Department of Agriculture Forest Service, Southern Research Station, Asheville, NC.
10. Becking, R.W. (1957) The Zürich-Montpellier school of phytosociology. Botanical Reviews 23, 411-488.
11. Berendsohn, W.G., Döring, M., Geoffroy, M. et al. (2003) The Berlin Model: a concept-based taxonomic information model. In: MoReTax-Handling Factual Information Linked to Taxonomic Concepts in Biology [Schriftenreihe für Vegetationskunde 39] (ed. W.G. Berendsohn), pp. 15-42. Federal Agency for Nature Conservation, Bonn, DE.
12. Braun-Blanquet, J. (1928) Pflanzensoziologie: Gründzuge der Vegetationskunde. Springer-Verlag, Berlin.
13. Braun-Blanquet, J. (1964) Pflanzensoziologie. 3rd ed. Springer-Verlag, Berlin.
14. Bray, J.R. & Curtis, J.T. (1957) An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs 27, 326-349.
15. Breiman, L. (2001) Random forests. Machine Learning 45, 532.
16. Breiman, L., Friedman, J., Olshen, R.A. & Stone, C.J. (1984) Classification and Regression Trees. Wadsworth & Brooks, Monterey, CA.
17. Brogden, H.E. (1949) A new coefficient: application to biserial correlation and to estimation of selective efficiency. Psychometrica 14, 169-182.
18. Bruelheide, H. (2000) A new measure of fidelity and its application to defining species groups. Journal of Vegetation Science 11, 167-178.
19. Bruelheide, H. & Chytrý, M. (2000) Towards unification of national vegetation classifications: A comparison of two methods for analysis of large data sets. Journal of Vegetation Science 11, 295-306.
20. Bruelheide, H. & Flintrop, T. (1994) Arranging phytosociological tables by species-relevégroups. Journal of Vegetation Science 5, 311-316.
21. Ĉerná, L. & Chytrý, M. (2005) Supervised classification of plant communities with artificial neural networks. Journal of Vegetation Science 16, 407-414.
22. Chytrý, M. & Otýpková Z. (2003) Plot sizes used for phytosociological sampling of European vegetation. Journal of Vegetation Science 14, 563-570.
23. Chytrý, M., Tichý, M., Holt, J. & Botta-Dukát, Z. (2002) Determination of diagnostic species with statistical fidelity measures. Journal of Vegetation Science 13, 79-90.
24. Cowardin, L.M., Carter, V., Golet, F.C. & LaRoe, E.T. (1979) Classification of the Wetlands and Deepwater Habitats of the United States. U.S. Fish and Wildlife Service, Washington, DC.
25. Curtis, J.T. (1959) Vegetation of Wisconsin. University of Wisconsin Press, Madison, WI.
26. De Cáceres, M., Font, X. & Oliva, F. (2008) Assessing species diagnostic value in large data sets: a comparison between phi coefficient and Ochiai index. Journal of Vegetation Science 19, 779-788.
27. De Cáceres, M., Font, X., Vicente, P. & Oliva, F. (2009) Numerical reproduction of traditional classifications and automated vegetation identification. Journal of Vegetation Science 20, 620-628.
28. De Cáceres, M., Font, X. & Oliva, F. (2010a) The management of vegetation classifications with fuzzy clustering. Journal of Vegetation Science 21, 1138-1151.
29. De Cáceres, M., Legendre, P. & Moretti, M. (2010b) Improving indicator species analysis by combining groups of sites. Oikos 119, 1674-1684.
30. De Cáceres, M. & Wiser, S. (2012) Towards consistency in vegetation classification. Journal of Vegetation Science 23, 387-393.
31. Dengler, J. (2009) A flexible multi-scale approach for standardised recording of plant species richness patterns. Ecological Indicators 9, 1169-1178.
32. Dengler, J., Chytrý, M. & Ewald, J. (2008) Phytosociology. In: Encyclopedia of Ecology (eds S.E. J ø rgensen & B.D. Fath), pp. 2767-2779. Elsevier, Oxford.
33. Dengler, J., Löbel, S. & Dolnik, C. (2009) Species constancy depends on plot size-a problem for vegetation classification and how it can be solved. Journal of Vegetation Science 20, 754-766.
34. Dengler, J., Jansen, F., Glöckler, F. et al. (2011) The Global Index of Vegetation-Plot Databases: a new resource for vegetation science. Journal of Vegetation Science 22, 582-597.
35. Domin, K. (1928) The relations of the Tatra mountain vegetation to the edaphic factors of the habitat: a synecological study. Acta Botanica Bohemica 6/7, 133-164.
36. Dufrêne, M. & Legendre, P. (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecological Monographs 67, 345-366.
37. Ellenberg, H. (1956) Grundlagen der Vegetationsgliederung. 1. Teil: Aufgaben und Methoden der Vegetationskunde. Ulmer, Stuttgart.
38. Equihua, M. (1990) Fuzzy clustering of ecological data. Journal of Ecology 78, 519-534.
39. Ewald, J. (2003) A critique for phytosociology. Journal of Vegetation Science 14, 291-296.
40. Faith. D.P., Minchin, P.R. & Belbin, L. (1987) Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.
41. Feoli, E. & Orlóci, L. (1979) Analysis of concentration and detection of underlying factors in structured tables. Vegetatio 40, 49-54.
42. Franz, N.M., Peet, R.K. & Weakley, A.S. (2008) On the use of taxonomic concepts in support of biodiversity research and taxonomy. Symposium Proceedings, In: The New Taxonomy (ed. Q.D. Wheeler). Systematics Association Special Volume 74, 63-86. Taylor & Francis, Boca Raton, FL.
43. Fridley, J.D., Peet, R.K. Wentworth, T.R. & White, P.S. (2005) Connecting fine-and broad-scale patterns of species diversity: species-area relationships of Southeastern U.S. flora. Ecology 86, 1172-1177.
44. Gégout, J.-C. & Coudun, C. (2012) The right relevéin the right vegetation unit: a new typicality index to reproduce expert judgment with an automatic classification programme. Journal of Vegetation Science 23, 24-32.
45. Gillison, A.N. & Brewer, K.R.W. (1985) The use of gradient directed transects or gradsects in natural resource survey. Journal of Environmental Management 20, 103-117.
46. Gleason, H.A. (1926) The individualistic concept of the plant association. Bulletin of the Torrey Botanical Club 53, 7-26.
47. Gleason, H.A. (1939) The individualistic concept of the plant association. American Midland Naturalist 21, 92-110.
48. Goodall, D.W. (1953) Objective methods for the classification of vegetation. II. Fidelity and indicator value. Australian Journal of Botany 1, 434-456.
49. Goodall, D.W. (1973) Sample similarity and species correlation. In: Ordination and Classification of Communities [Handbook of Vegetation Science V] (ed. R.H. Whittaker), pp. 105-156. Dr. W. Junk, The Hague.
50. Goodman L. & Kruskal, W. (1954) Measures of association for cross-validations. Journal of the American Statistical Association 49, 732-764.
51. Gopal, S. & Woodcock, C. (1994) Theory and methods for accuracy assessment of thematic maps using fuzzy sets. Photogrammetric Engineering and Remote Sensing 60, 181-188.
52. Gray, A.N., Brandeis, T.J., Shaw, J.D. & McWilliams, W.H. (2012) Forest inventory vegetation database of the United States of America. Biodiversity and Ecology 4 (in press).
53. Grossman, D.H., Faber-Langendoen, D., Weakley, A.S. et al. (1998) International Classification of Ecological communities: Terrestrial Vegetation of the United States. Volume I. The National Vegetation Classification System: Development, Status, and Applications. The Nature Conservancy, Arlington, VA.
54. Hartigan, J.A & Wong, M.A. (1979) Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal Statistical Society, Series C (Applied Statistics) 28, 100-108.
55. Hennekens, S.M. & Schaminée, J.H.J. (2001) TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science 12, 589-591.
56. Hill, M.O. (1979) TWINSPAN-A FORTRAN Program for Arranging Multivariate Data in an Or-dered Two-way Table by Classification of the Individuals and Attributes. Cornell University, Ithaca, NY.
57. Hubálek, Z. (1982) Coefficients of association and similarity, based on binary (presence-absence) data: an evaluation. Biological Reviews of the Cambridge Philosophical Society 57, 669-689.
58. Hubert, L.J. & Levin, J.R. (1976) A general framework for assessing categorical clustering in free recall. Psychology Bulletin 83, 1072-1080.
59. Jansen, F. & Dengler, J. (2010) Plant names in vegetation databases-a neglected source of bias. Journal of Vegetation Science 21, 1179-1186.
60. Jennings, M.D., Faber-Langendoen, D., Loucks, O.L., Peet, R.K. & Roberts, D. (2009) Characterizing Associations and Alliances of the U.S. National Vegetation Classification. Ecological Monographs 79, 173-199.
61. Jones, M.B., Schildhauer, M.P., Reichman, O.J. & Bowers, S. (2006) The new bioinformatics: integrating ecological data from the gene to the biosphere. Annual Review of Ecology, Evolution and Systematics 37, 519-544.
62. Juhász-Nagy, P. (1964) Some theoretical models of cenological fidelity I. Acta Botanica Debrecina 3, 33-43.
63. Kaufman, L. & Rousseeuw, P.J. (1990) Finding Groups in Data. John Wiley and Sons, New York, NY.
64. Kent, M. (2012) Vegetation Description and Data Analysis: A Practical Approach. 2nd ed. Wiley-Blackwell, Oxford, UK.
65. Knollová, I., Chytrý, M., Tichý, L. & Hájek, O. (2005) Stratified resampling of phytosociological databases: some strategies for obtaining more representative data sets for classification studies. Journal of Vegetation Science 16, 479-486.
66. Krajina, V.J. (1933) Die Pflanzengesellschaften des Mlynica-Tales in den Vysoke Tatry (Hohe Tatra). Mit besonderer Berücksichtigung derökologischen Verhältnisse. Beihefte zum Botanischen Centralblatt 50, 774-957; 51, 1-224.
67. Lambert, J.M. & Dale, M.B. (1964) The use of statistics in phytosociology. Advances in Ecological Research 2, 59-99.
68. Lance, G.N. & Williams, W.T. (1967) A general theory of classificatory sorting strategies. I. Hierarchical systems. Computer Journal 9, 373-380.
69. Legendre, P. & Gallagher, E.D. (2001) Ecologically meaningful transformations for ordination of species data. Oecologia 129, 271-280.
70. Legendre, P. & Legendre, L. (1998) Numerical ecology, 2nd ed. Developments in Environmental Modelling 20. Elsevier, Amsterdam.
71. Lengyel, A., Chytrý, M. & Tichý, L. (2011) Heterogeneity-constrained random resampling of phytosociological databases. Journal of Vegetation Science 22, 175-183.
72. Lepš, J. & Šmilauer, P. (2003) Multivariate Analysis of Ecological Data Using CANOCO. Cambridge University Press, Cambridge.
73. Ludwig, J.A. & Reynolds, J.F. (1988) Statistical Ecology: A Primer on Methods and Computing. John Wiley and Sons, New York, NY.
74. McCune, B. (1994) Improving community analysis with the Beals smoothing function. Ecoscience 1, 82-86.
75. McCune, B. & Grace, J.B. (2002) Analysis of Ecological Communities. MjM Software Design, Gleneden Beach, OR.
76. Michalcová, D., Lvončík, S., Chytrý, M. & Hájek, O. (2011) Bias in vegetation databases? A comparison of stratified-random and preferential sampling. Journal of Vegetation Science 22, 281-291.
77. Mucina, L. (1997) Classification of vegetation: past, present and future. Journal of Vegetation Science 8, 751-760.
78. Mucina, L., Rodwell, J.S., Schaminée, J.H.J. & Dierschke, H. (1993) European vegetation survey: Current state of some national programs. Journal of Vegetation Science 4, 429-438.
79. Mucina, L., Schaminée, J.H.J & Rodwell, J.S. (2000) Common data standards for recording relevés in field survey for vegetation classification. Journal of Vegetation Science 11, 769-772.
80. Mueller-Dombois, D. & Ellenberg, H. (1974) Aims and Methods of Vegetation Ecology. John Wiley & Sons, Ltd, New York, NY.
81. Nekola, J.C. & White, P.S. (1999) The distance decay of similarity in biogeography and ecology. Journal of Biogeography 26, 867-878.
82. Noest, V., van der Maarel, E. & van der Meulen, F. (1989) Optimum transformation of plant species cover-abundance values. Vegetatio 83, 167-178.
83. Orlóci, L. (1967) An agglomerative method for classification of plant communities. Journal of Ecology 55, 193-206.
84. Orlóci, L. (1978) Multivariate Analysis in Vegetation Research, 2nd edn. Dr. W. Junk, The Hague.
85. Peet, R.K., Lee, M.T., Jennings, M.D. & Faber-Langendoen, D. (2012) VegBank: a permanent, open-access archive for vegetation plot data. Biodiversity and Ecology 4 (in press).
86. Peet, R.K., Wentworth, T.R. & White, P.S. (1998) The North Carolina Vegetation Survey protocol: a flexible, multipurpose method for recording vegetation composition and structure. Castanea 63, 262-274.
87. Pfister, R.D. & Arno, S.F. (1980) Classifying forest habitat types based on potential climax vegetation. Forest Science 26, 52-70.
88. Pfister, R.D., Kovalchik, B.L., Arno, S.F. & Presby, R.C. (1977) Forest Habitat Types of Montana. USDA Forest Service General Technical Report INT-34.
89. Podani, J. (1990) Comparison of fuzzy classifications. Coenoses 5, 17-21.
90. Podani, J. (2000) Simulation of random dendrograms and comparison tests: some comments. Journal of Classification 17, 123-142.
91. Podani, J. (2005) Multivariate exploratory analysis of ordinal data in ecology: pitfalls, problems and solutions. Journal of Vegetation Science 16, 497-510.
92. Podani, J. & Csányi, B. (2010) Detecting indicator species: some extensions of the IndVal measure. Ecological Indicators 10, 1119-1124.
93. Podani, J. & Feoli, E. (1991) A general strategy for the simultaneous classification of variables and objects in ecological data tables. Journal of Vegetation Science 2, 435-444.
94. Radford, A.E., Ahles, H.E. & Bell, C.R. (1968) Manual of the Vascular Flora of the Carolinas. University of North Carolina Press, Chapel Hill, NC.
95. Roberts, D.W. (2010) OPTPART: Optimal partitioning of similarity relations. R package version 2.0-1, http://CRAN.R-project.org/package=optpart (accessed 25 May 2012).
96. Rodríguez, J.P., Rodríguez-Clark, K.M., Baille, J.E.M. et al. (2011) Establishing IUCN redlist criteria for threatened ecosystems. Conservation Biology 25, 21-29.
97. Rodwell, J.S. (2006) National Vegetation Classification: User's Handbook. Joint Nature Conservation Committee, Peterborough.
98. Rodwell, J.S., Pignatti, S., Mucina, L. & Schaminée, J.H.J. (1995) European Vegetation Survey: update on progress. Journal of Vegetation Science 6, 759-762.
99. Rodwell, J.S., Schaminée, J.H.J., Mucina, L., Pignatti, S., Dring, J. & Moss, D. (2002) The Diversity of European Vegetation. An Overview of Phytosociological Alliances and Their Relationships to EUNIS Habitats. National Centre for Agriculture, Nature Management and Fisheries, Wageningen.
100. Roleček, J., Chytrý, M., Háyek, M., Lvončik, S. & Tichý, L. (2007) Sampling in large-scale vegetation studies: Do not sacrifice ecological thinking to statistical puritanism. Folia Geobotanica 42, 199-208.
101. Roleček, J., Tichý, L., Zleney, D. & Chytrý, M. (2009) Modified TWINSPAN classification in which the hierarchy respects cluster heterogeneity. Journal of Vegetation Science 20, 596-602.
102. Rousseeuw, P.J. (1987) Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computation and Applied Mathematics 20, 53-65.
103. Schaminée, J.H.J., Hennekens, S.M., Chytrý, M. & Rodwell, J.S. (2009) Vegetation-plot data and databases in Europe: an overview. Preslia 81, 173-185.
104. Schaminée, J.H.J., Hennekens, S.M. & Ozinga, W.A. (2007) Use of the ecological information system SynBioSys for the analysis of large datasets. Journal of Vegetation Science 18, 463-470.
105. Shimwell, D.W. (1971) Description and Classification of Vegetation. Sidgwick and Jackson, London.
106. Smartt, P.F.M., Meacock, S.E. & Lambert, J.M. (1976) Investigations into the proper ties of quantitative vegetational data. II. Further data type comparisons. Journal of Ecology 64, 41-78.
107. Sokal, R.R. & Rohlf, F.J. (1995) Biometry. The principles and Practice of Statistics in Biological Research, 3rd edN. Freeman, New York, NY.
108. Sokal, R.R. & Sneath, P.H.A. (1963) Principles of Numerical Taxonomy. Freeman, San Francisco and London.
109. Stohlgren, T.J., Falkner, M.B. & Schell, L.D. (1995) A modified-Whittaker nested vegetation sampling method. Vegetatio 117, 113-121.
110. Szafer, W. & Pawlowski, B. (1927) Die Pflanzenassoziationen des Tatra-Gebirges. A. Bemerkungenüber die angewandte Arbeitsmethodik. Bulletin International de l'Académie Polonaise des Sciences et Lettres B3 Suppl. 2, 1-12.
111. TDWG (2005) Taxonomic Concept Transfer Schema. Biodiversity Information Standards. http://www.tdwg.org/standards/117/(accessed 5 July 2012).
112. Tichý, L. & Chytrý, M. (2006) Statistical determination of diagnostic species for site groups of unequal size. Journal of Vegetation Science 17, 809-818.
113. Tichý, L., Chytrý, M., Hájek, M., Talbot, S.S. & Botta-Dukát, Z. (2010) OptimClass: using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities. Journal of Vegetation Science 21, 287-299.
114. Tsiripidis, I., Bergmeier, E., Fotiadis, G. & Dimopoulos, P. (2009) A new algorithm for the determination of differential taxa. Journal of Vegetation Science 20, 233-240.
115. USFGDC (United States Federal Geographic Data Committee) (2008) National Vegetation Classification Standard, Version 2 FGDC-STD-005-2008. Vegetation Subcommittee, Federal Geographic Data Committee, FGDC Secretariat, US Geological Survey, Reston, VA.
116. van der Maarel, E. (1979) Transformation of cover-abundance values in phytosociology and its effects on community similarity. Vegetatio 39, 97-144.
117. van der Maarel, E. (2007) Transformation of cover-abundance values for appropriate numerical treatment: Alternatives to the proposals by Podani. Journal of Vegetation Science 18, 767-770.
118. van Tongeren, O., Gremmen, N. & Hennekens, S. (2008) Assignment of relevés by supervised clustering of plant communities using a new composite index. Journal of Vegetation Science 19, 525-536.
119. Vision, T.J. (2010) Open data and the social contract of scientific publishing. BioScience 60, 330-331.
120. Waterton, C. (2002) From field to fantasy: classifying nature, constructing Europe. Social Studies of Science 32, 177-204.
121. Weber, H.E., Moravec, J. & Theurillat, J.-P. (2000) International Code of Phytosociological Nomenclature. 3rd edn. Journal of Vegetation Science 11, 739-768.
122. Wesche, K. & von Wehrden, H. (2011) Surveying southern Mongolia: application of multivariate classification methods in drylands with low diversity and long floristic gradients. Journal of Vegetation Science 14, 561-570.
123. Westhoff, V. & van der Maarel, E. (1973) The Braun-Blanquet approach. In: Ordination and Classification of Communities [Handbook of Vegetation Science V] (ed. R.H. Whittaker), pp. 617-726. Junk, The Hague.
124. Whittaker, R.H. (1960) Vegetation of the Siskiyou Mountains, Oregon and California. Ecological Monographs 30, 279-338.
125. Whittaker, R.H. (1962) Classification of natural communities. Botanical Review 28, 1-239.
126. Whittaker, R.H. (ed.) (1973) Ordination and Classification of Communities. [Handbook of Vegetation Science-Part V.]. Junk, The Hague.
127. Whittaker, R.H., Niering, W.A. & Crisp, M.D. (1979) Structure, pattern, and diversity of a mallee community in New South Wales. Vegetatio 39, 65-76.
128. Wildi, O. (2010) Data analysis in vegetation ecology. Wiley-Blackwell, Oxford, UK.
129. Williams, W.T., Lambert, J.M & Lance, G.N. (1966) Multivariate methods in plant ecology. V. Similarity analyses and information-analysis. Journal of Ecology 54, 427-445.
130. Willner, W., Tichý, L. & Chýtrý, M. (2009) Effects of different fidelity measures and contexts on the determination of diagnostic species. Journal of Vegetation Science 20, 10-137.
131. Wilson, J.B. (2012) Species presence/absence sometimes represents a plant community as well as species abundances do, or better. Journal of Vegetation Science 23 (DOI: 10.1111/j.1654-1103.2012.01430.x).
132. Wiser, S., Spencer, N., De Cáceres, M., Kleikamp, M., Boyle, B. & Peet, R.K. (2011) Veg-X-an exchange standard for plot-based vegetation data. Journal of Vegetation Science 22, 598-609.