[Anderson, M.J. & Wilis T.J. (2003). Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecology, 84, 511–525. DOI: 10.1890/0012-9658(2003)084[0511:CAOPCA]2.0.CO;2.]Search in Google Scholar
[APHA, (1992). Standard methods for the examination of water and waste water. American Washington: Public Health Association.]Search in Google Scholar
[Bandalos, D.L. & Boehm-Kaufman M.R. (2009). Four common misconceptions in exploratory factor analysis. In C.E. Lance & R.J. Vandenberg (Eds.), Statistical and methodological myths and urban legends (pp. 61–87). New York: Routledge Publisher.]Search in Google Scholar
[Barrett, P.T. & Kline P. (1981). The observation to variable ratio in factor analysis. Personality Study and Group Behaviour, 1, 23−33.]Search in Google Scholar
[Bray, J.R. & Curtis J.T. (1957). An ordination of the upland forest communities of Southern Wisconsin. Ecol. Monogr., 27, 325–349. DOI: 10.2307/1942268.10.2307/1942268]Search in Google Scholar
[Bryant, F.B. & Yarnold P.R. (1995). Principal components analysis and exploratory and confirmatory factor analysis. In L.G. Grimm & R.R. Yarnold (Eds.), Reading and understanding multivariate statistics (pp. 99−136). Washington: American Psycholgical Association.]Search in Google Scholar
[Burd, B.J.A., Nemec, A. & Brinkhurst R.O. (1990). The development and application of analytical methods in benthic marine faunal studies. Adv. Mar. Biol., 26, 169−247. DOI: 10.1016/S0065-2881(08)60201-1.10.1016/S0065-2881(08)60201-1]Search in Google Scholar
[Cadima, J. & Jolliffe I.T. (1995). Loadings and correlations in the interpretation of principal components. Journal of Applied Statistics, 22, 203−214. DOI: 10.1080/757584614.10.1080/757584614]Search in Google Scholar
[Cattell, R.B. (1966). The Scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276. DOI: 10.1207/s15327906mbr0102_10.10.1207/s15327906mbr0102_1026828106]Search in Google Scholar
[Cattell, R.B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York: Plenum Press.10.1007/978-1-4684-2262-7]Search in Google Scholar
[Chateau, F. & Lebart L. (1996). Assessing sample variability in the visualization techniques related to principal component analysis: Bootstrap and alternative simulation methods. In A. Prats (Ed.), Proceedings of COMPSTAT 2006. Heidelberg: Physica Verlag.]Search in Google Scholar
[Chatfield, C. & Collins A.J. (1980). Introduction to multivariate analysis. London, New York: Chapman & Hall.10.1007/978-1-4899-3184-9]Search in Google Scholar
[Comrey, A.L. & Lee H.B. (1992). A first course in factor analysis. London: Taylor and Francis.]Search in Google Scholar
[de Winter, J.C.F., Dodou, D. & Wieringa P.A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44, 147−181. DOI: 10.1080/00273170902794206.10.1080/0027317090279420626754265]Search in Google Scholar
[Dengler, J., Lobel, S. & Dolnik C. (2009). Species constancy depends on plot size a problem for vegetation classification and how it can be solved. J. Veg. Sci., 20, 754−766. DOI: 10.1111/j.1654-1103.2009.01073.x.10.1111/j.1654-1103.2009.01073.x]Search in Google Scholar
[Diaconis, P. & Efron B. (1983). Computer-intensive methods in statistics. Sci. Am., 248, 116−130. doi:10.1038/scientificamerican0583-11610.1038/scientificamerican0583-116]Search in Google Scholar
[Dochtermann, N.A. & Jenkins S.H. (2011). Multivariate methods and small sample sizes. Ethology, 117, 95−101. DOI: 10.1111/j.1439-0310.2010.01846.x.10.1111/j.1439-0310.2010.01846.x]Search in Google Scholar
[Fasham, M.J.R. (1977). The comparison of nonmetric multidimensional scaling, principal component analysis and reciprocal averaging for the ordination of simulated coenocline and coenoplanes. Ecology, 58, 551−561. DOI: 10.2307/193900410.2307/1939004]Search in Google Scholar
[Forcino, F.L. (2012). Multivariate assessment of the required sample size for community paleoecological research. Palaeogeo. Palaeoclimatol. Palaeoecol., 315−316, 134−141. DOI: 10.1016/j.palaeo.2011.11.019.10.1016/j.palaeo.2011.11.019]Search in Google Scholar
[Gamito, S. & Raffaelli D. (1992). The sensitivity of several ordination methods to sample replication in benthic surveys. J. Exp. Mar. Biol. Ecol., 164, 221−232. DOI: 10.1016/0022-0981(92)90176-B.10.1016/0022-0981(92)90176-B]Search in Google Scholar
[Gauch, H.G. & Whittaker R.H. (1972). Comparison of ordination techniques. Ecology, 53, 868–875. DOI: 10.2307/1934302.10.2307/1934302]Search in Google Scholar
[Gauch, H.G., Whittaker R.H. & Wentworth T.R. (1977). A comparative study of reciprocal averaging and other ordination techniques. J. Ecol., 65, 157–174. DOI: 10.2307/2259071.10.2307/2259071]Search in Google Scholar
[Gauch, H.G., Whittaker R.H. & Singer S.B. (1981). A comparative study of nonmetric ordinations. J. Ecol., 69, 135–152. DOI: 10.2307/225982110.2307/2259821]Search in Google Scholar
[Gehlhausen, S.M., Schwartz, M.W. & Augspurger C.K. (2000). Vegetation and microclimatic edge effects in two mixed mesophytic forest fragments. Plant Ecol., 147, 21−35. DOI: 10.1023/A:1009846507652.10.1023/A:1009846507652]Search in Google Scholar
[Goff, F.G. & Mitchell R. (1975). A comparison of species ordination results from plot and stand data. Vegetatio, 31, 15−22. DOI: 10.1007/BF00127871.10.1007/BF00127871]Search in Google Scholar
[Goodall, D.W. (1953). Objective methods for the classification of vegetation. III. An essay in the use of factor analysis. Aust. J. Bot., 1, 39−63. DOI: 10.1071/BT9530039.10.1071/BT9530039]Search in Google Scholar
[Gorsuch, R.L. (1983). Factor analysis. Hillsdale NJ: Lawrence Erlbaum Associates.]Search in Google Scholar
[Hatcher, L. (1994). A step-by-step approach to using the SAS system for factor analysis and structural equation modeling. Cary: SAS Institute.]Search in Google Scholar
[Hill, M.O. (1973). Reciprocal averaging: an eigenvector method of ordination. J. Ecol., 61, 237−249. DOI: 10.2307/2258931.10.2307/2258931]Search in Google Scholar
[Hill, M.O. & Gauch H.G. (1980). Detrended correspondence analysis: an improved technique. Vegetatio, 42, 47−58. DOI: 10.1007/BF00048870.10.1007/BF00048870]Search in Google Scholar
[Hirosawa, Y., Marsh, S.E. & Kliman D.H. (1996). Application of standardized principal component analysis to land-cover characterization using multi temporal AVHRR data. Remote Sens. Environ., 58, 267−281. DOI: 10.1016/S0034-4257(96)00068-5.10.1016/S0034-4257(96)00068-5]Search in Google Scholar
[Hirst, C.N. & Jackson D.A. (2007). Reconstructing community relationships: the impact of sampling error, ordination approach and gradient length. Divers. Distrib., 13, 361–371. DOI: 10.1111/j.1472-4642.2007.00307.x.10.1111/j.1472-4642.2007.00307.x]Search in Google Scholar
[Hutcheson, G. & Sofroniou N. (1999). The multivariate social scientist: Introductory statistics using generalized linear models. London: Sage Publication.10.4135/9780857028075]Search in Google Scholar
[Jackson, D.A. (1993). Stopping rules in principal components analysis: A comparison of heuristical and statistical approaches. Ecology, 74, 2204−2214. DOI: 10.2307/1939574.10.2307/1939574]Search in Google Scholar
[Jackson, J.A. (1991). A user’s guide to principal component analysis. New York: Wiley Inter Science.10.1002/0471725331]Search in Google Scholar
[James, F.C. & McCulloch C.E. (1990). Multivariate analysis in ecology and systematics: panacea or Pandoras box. Annu. Rev. Ecol. Evol. Syst., 21, 129−166. DOI: 10.1146/annurev.es.21.110190.001021.10.1146/annurev.es.21.110190.001021]Search in Google Scholar
[Joliffe, I. (2002). Principal component analysis. New York: Springer-Verlag.]Search in Google Scholar
[Kendall, M. (1980). Multivariate analysis. London: Charles Griffin.]Search in Google Scholar
[Kline, P. (1979). Psychometrics and psychology. London: Academic Press.]Search in Google Scholar
[Knox, R.G. & Peet R.K. (1989). Bootstrapped ordination: a method for estimating sampling effects in indirect gradient analysis. Vegetatio, 80, 153−165. DOI: 10.1007/BF00048039.10.1007/BF00048039]Search in Google Scholar
[Lawley, D.N. & Maxwell A.E. (1971). Factor analysis as a statistical method. New York: Macmillan.]Search in Google Scholar
[Legendre, P. & Birks H.J.B. (2012). Clustering and partitioning. In H.J.B. Birks, A.F. Lotter, S. Juggins & J.P. Smol (Eds.), Tracking environmental change using lake sediments Vol. 5: Data handling and numerical techniques (pp. 167−200). Dordrecht: Springer. DOI: 10.1007/978-94-007-2745-8_7.10.1007/978-94-007-2745-8_7]Search in Google Scholar
[MacCallum, R.C., Widaman, K.F., Zhang, S. & Hong S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84−99. DOI: 10.1037/1082-989X.4.1.84.10.1037/1082-989X.4.1.84]Search in Google Scholar
[MacCallum, R.C., Widaman, K.F., Preacher, K.J. & Hong S. (2001). Sample size in factor analysis: The role of model error. Multivariate Behavioral Research, 36, 611–637. DOI: 10.1207/S15327906MBR3604_06.10.1207/S15327906MBR3604_0626822184]Search in Google Scholar
[Manjarres-Martinez, L.M., Gutiérrez-Estrada, J.C., Hernando, J.J.A. & Soriguer M.C. (2012). The performance of three ordination methods applied to demersal fish data sets: stability and interpretability. Fish. Manag. Ecol., 19, 200−213. DOI: 10.1111/j.1365-2400.2011.00817.x.10.1111/j.1365-2400.2011.00817.x]Search in Google Scholar
[Manly, B.F.J. (1998). Randomization, bootstrap and Monte Carlo methods in biology. London: Chapman & Hall.]Search in Google Scholar
[Minchin, P.R. (1987). An evaluation of the relative robustness of techniques for ecological ordination. Vegetatio, 69, 89−107. DOI: 10.1007/BF00038690.10.1007/BF00038690]Search in Google Scholar
[Mundfrom, D.J., Shaw, D.G. & Ke T.L. (2005). Minimum sample size recommendations for conducting factor analyses. International Journal of Testing, 5, 159−168. DOI: 10.1207/s15327574ijt0502_4.10.1207/s15327574ijt0502_4]Search in Google Scholar
[Okland, R.H., Eilersten, O. & Okland T. (1990). On the relationship between sample size and beta diversity in boreal coniferous forests. Vegetatio, 87, 187−190. DOI: 10.1007/BF00042954.10.1007/BF00042954]Search in Google Scholar
[Orloci, L. (1966). Geometric models in ecology 1. The theory and application of some ordination methods. J. Ecol., 54, 193−215. DOI: 10.2307/2257667.10.2307/2257667]Search in Google Scholar
[Orloci, L. (1978). Multivariate analysis in vegetation research. The Hague: Junk.]Search in Google Scholar
[Osborne, J.W. & Costello A.B. (2004). Sample size and subject to item ratio in principal components analysis. Practical Assessment Research & Evaluation, 9, 15−23.]Search in Google Scholar
[Otypkova, Z. & Chytry M. (2006). Effects of plot size on the ordination of vegetation samples. J. Veg. Sci., 17, 465−472. DOI: 10.1111/j.1654-1103.2006.tb02467.x.10.1111/j.1654-1103.2006.tb02467.x]Search in Google Scholar
[Peres-Neto, P.R., Jackson, D.A. & Somers K.M. (2003). Giving meaningful interpretation to ordination axes: assessing loading significance in principal component analysis. Ecology, 84, 2347–2363. http://www.jstor.org/stable/345014010.1890/00-0634]Search in Google Scholar
[Peres-Neto, P.R., Jackson, D.A. & Somers K.M. (2005). How many principal components? Stopping rules for determining the number of non-trivial axes revisited. Computational Statistics and Data Analysis, 49, 974−997. DOI: 10.1016/j.csda.2004.06.015.10.1016/j.csda.2004.06.015]Search in Google Scholar
[Pillar, V. de P. (1999). The bootstrapped ordination re-examined. J. Veg. Sci., 10, 895−902. DOI: 10.2307/3237314.10.2307/3237314]Search in Google Scholar
[Preacher, K.J. & MacCallum R.C. (2002). Exploratory factor analysis in behavioral genetics research: Factor recovery with small sample sizes. Behav. Genet., 32, 153−161. DOI: 10.1023/A:1015210025234.10.1023/A:1015210025234]Search in Google Scholar
[Rao, C.R. (1964). The use and interrelation of principal component analysis in applied research. Sankhya (Ser. A), 26, 329−358. http://www.jstor.org/stable/25049339]Search in Google Scholar
[Richman, M.B. (1988). A cautionary note concerning a commonly applied eigen analysis procedure. Tellus B, 40, 50−58. DOI: 10.1111/j.1600-0889.1988.tb00212.x.10.1111/j.1600-0889.1988.tb00212.x]Search in Google Scholar
[Shaukat, S.S. (1985). Approaches to the analysis of ruderal weed vegetation. PhD. thesis, University of Western Ontario, London, Canada.]Search in Google Scholar
[Shaukat, S.S. & Uddin M. (1989a). A comparison of principal component and factor analysis as an ordination model with reference to desert ecosystem. Coenoses, 4, 15−28. http://www.jstor.org/stable/43461254]Search in Google Scholar
[Shaukat, S.S. & Uddin M. (1989b). An application of canonical and principal component analysis to the study of desert environment. Abstracta Botanica (Budapest), 13, 17−45. http://www.jstor.org/stable/43519176]Search in Google Scholar
[Shaukat, S.S. & Siddiqui I.A. (2005). Essentials of Mathematical Ecology: Computer Programs in BASIC, FORTRAN and C++. Karachi: Farquan Publishers.]Search in Google Scholar
[Shaukat, S.S., Sheikh I.H. & Siddiqui I.A. (2005). An application of correspondence analysis, Detrended correspondence analysis and Canonical correspondence analysis to the vegetation and environment of calcareous hills around Karachi. Int. J. Biol. Biotechnol., 2, 617−627.]Search in Google Scholar
[Stauffer, D. F., Garton E.O. & Steinhorst R.K. (1985). A comparison of principal component from real and random data. Ecology, 66, 1693−1698. DOI: 10.2307/2937364.10.2307/2937364]Search in Google Scholar
[Swan, J.M.A. & Dix R.L. (1966). The phytosociological structure of upland forest at Candle Lake, Saskatchewan. J. Ecol., 54, 13−40. DOI: 10.2307/2257657.10.2307/2257657]Search in Google Scholar
[Ter Braak, C.J.F. (1986). Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology, 67, 1167−1179. DOI: 10.2307/1938672.10.2307/1938672]Search in Google Scholar
[Velicer, W.F. & Fava J.L. (1998). The effects of variable and subject sampling on factor pattern recovery. Psychological Methods, 3, 231−251. DOI: 10.1037/1082-989X.3.2.231.10.1037/1082-989X.3.2.231]Search in Google Scholar
[Walker, S.C. & Jackson D.A. (2011). Random-effects ordination: describing and predicting multivariate correlations and co-occurrences. Ecol. Monogr., 81, 635–663. http://www.jstor.org/stable/2320847810.1890/11-0886.1]Search in Google Scholar
[Whittaker, R.J. (1987). An application of detrended correspondence analysis and nonmetric multidimensional scaling to the identification and analysis of environmental factor complexes and vegetation structures. J. Ecol., 75, 363−376. DOI: 10.2307/2260424.10.2307/2260424]Search in Google Scholar
[Wikum, D.A. & Wali M.K. (1974). Analysis of a North Dakota gallery forest: Vegetation in relation to topographic and soil gradients. Ecol. Monogr., 44, 441–464. DOI: 10.2307/1942449.10.2307/1942449]Search in Google Scholar