An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis

Abstract The biosphere is filled with complex living patterns and important questions about biodiversity and community and ecosystem ecology are concerned with structure and function of multispecies systems that are responsible for those patterns. Cluster analysis identifies discrete groups within multivariate data and is an effective method of coping with these complexities, but often suffers from subjective identification of groups. The bootstrap testing method greatly improves objective significance determination for cluster analysis. The BOOTCLUS program makes cluster analysis that reliably identifies real patterns within a data set more accessible and easier to use than previously available programs. A variety of analysis options and rapid re-analysis provide a means to quickly evaluate several aspects of a data set. Interpretation is influenced by sampling design and a priori designation of samples into replicate groups, and ultimately relies on the researcher’s knowledge of the organisms and their environment. However, the BOOTCLUS program provides reliable, objectively determined groupings of multivariate data.

[1]  A. Longhurst,et al.  Recurrent Group Analysis of Species Assemblages of Demersal Fish in the Gulf of Guinea , 1968 .

[2]  M. Hill,et al.  Data analysis in community and landscape ecology , 1987 .

[3]  David F West,et al.  Breeding structure of three snow pool Aedes mosquito species in northern Colorado , 1998, Heredity.

[4]  Valério D. Pillar,et al.  HOW SHARP ARE CLASSIFICATIONS , 1999 .

[5]  Brian Everitt,et al.  Cluster analysis , 1974 .

[6]  P. Uchil,et al.  Phylogenetic analysis of Japanese encephalitis virus: envelope gene based analysis reveals a fifth genotype, geographic clustering, and multiple introductions of the virus into the Indian subcontinent. , 2001, The American journal of tropical medicine and hygiene.

[7]  Michael B. Richman,et al.  On the Application of Cluster Analysis to Growing Season Precipitation Data in North America East of the Rockies , 1995 .

[8]  Derek Ellis,et al.  Re-analysis of species associational data using bootstrap significance tests , 1991 .

[9]  F. P. Ojeda,et al.  Guild structure of carnivorous intertidal fishes of the Chilean coast: implications of ontogenetic dietary shifts , 1998, Oecologia.

[10]  Anil K. Jain,et al.  Bootstrap technique in cluster analysis , 1987, Pattern Recognit..

[11]  Marina Montresor,et al.  TOWARD AN ASSESSMENT ON THE TAXONOMY OF DINOFLAGELLATES THAT PRODUCE CALCAREOUS CYSTS (CALCIODINELLOIDEAE, DINOPHYCEAE): A MORPHOLOGICAL AND MOLECULAR APPROACH , 1999 .

[12]  P. Sopp.  Cluster analysis. , 1996, Veterinary immunology and immunopathology.

[13]  G. Soete.  OVWTRE: A program for optimal variable weighting for ultrametric and additive tree fitting , 1988 .

[14]  E. C. Pielou,et al.  The Interpretation of Ecological Data: A Primer on Classification and Ordination , 1985 .

[15]  C. Lindegaard,et al.  Reconstruction of trophic state in Danish lakes using subfossil chydorid (Cladocera) assemblages , 1998 .

[16]  M K Kerr,et al.  Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[17]  James E. McKenna,et al.  Structure and dynamics of the fishery harvest in Broward County, Florida, during 1989 , 1997 .

[18]  N. Poff,et al.  A hydrogeography of unregulated streams in the United States and an examination of scale‐dependence in some hydrological descriptors , 1996 .

[19]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[20]  J. W. Johnston,et al.  Similarity indices I: what do they measure. , 1976 .

[21]  Pan Qifeng,et al.  Old World sources of the first New World human inhabitants: A comparative craniofacial view , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[22]  J. Sepkoski,et al.  Distribution of Freshwater Mussels: Coastal Rivers as Biogeographic Islands , 1974 .

[23]  H. Gleason,et al.  The individualistic concept of the plant association , 1939 .

[24]  James E. McKenna.  Biological structure and dynamics of littoral fish assemblages in the Eastern Finger Lakes , 2001 .

[25]  C. Rutter,et al.  Bootstrap estimation of diagnostic accuracy with patient-clustered data. , 2000, Academic radiology.

[26]  R. Fisher,et al.  The Relation Between the Number of Species and the Number of Individuals in a Random Sample of an Animal Population , 1943 .

[27]  Brian J. Rothschild,et al.  Stock Assessment: Quantitative Methods and Applications for Small Scale Fisheries , 1995 .

[28]  G. W. Milligan,et al.  An examination of procedures for determining the number of clusters in a data set , 1985 .

[29]  N. S. Urquhart,et al.  Patterns in the Balance of Nature , 1966 .

[30]  Larry T. Looper,et al.  Neural Networks: A Primer , 1991 .

[31]  C. R. Lovell,et al.  Host-specific ecotype diversity of rhizoplane diazotrophs of the perennial glasswort Salicornia virginica and selected salt marsh grasses , 2001 .

[32]  J. R. Vidal,et al.  Genetic relationships among grapevine varieties grown in different French and Spanish regions based on RAPD markers , 1999, Euphytica.

[33]  P. Rincón,et al.  Application of a cluster‐bootstrapping method for identifying the dietary patterns of fish populations , 1992 .

[34]  J. E. McKenna,et al.  Influence of physical disturbance on the structure of coral reef fish assemblages in the Dry Tortugas , 1997 .

[35]  Frederic E. Clements,et al.  Nature and Structure of the Climax , 1936 .

[36]  G. N. Lance,et al.  A general theory of classificatory sorting strategies: II. Clustering systems , 1967, Comput. J..

[37]  Hugh G. Gauch,et al.  Multivariate analysis in community ecology , 1984 .

[38]  Peter H. A. Sneath,et al.  Numerical Taxonomy: The Principles and Practice of Numerical Classification , 1973 .

[39]  Charles Ashbacher.  Microsoft Visual Basic 6.0 Pro , 1999 .

[40]  Donald F. Boesch,et al.  Application of numerical classification in ecological investigations of water pollution , 1977 .

[41]  G. N. Lance,et al.  A General Theory of Classificatory Sorting Strategies: 1. Hierarchical Systems , 1967, Comput. J..

[42]  E. Fager,et al.  Determination and Analysis of Recurrent Groups , 1957, Ecology.

[43]  A. Nemec,et al.  Using the Bootstrap to Assess Statistical Significance in the Cluster Analysis of Species Abundance Data , 1988 .

[44]  V. J. Rayward-Smith,et al.  Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition , 1999 .