Titlebook: Analyzing Ecological Data; Alain F. Zuur,Elena N. Ieno,Graham M. Smith Book 2007 The Editor(s) (if applicable) and The Author(s), under ex

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Stella Gatziu Grivas,Manuela Graf, we suggest you may want to go straight to Chapter 12, as the method we use here, Bray-Curtis ordination, is rarely used. However, it is an excellent tool to explain the underlying idea of ordination.

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https://doi.org/10.1057/9781137405579ondence analysis (CA) and canonical correspondence analysis (CCA). We start by giving a historical insight into the techniques community ecologists have used most during the last two decades. This chapter is mainly based on Greenacre (1984), Ter Braak (1985, 1986), Ter Braak and Verdonschot (1995),

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https://doi.org/10.1057/9781137405579ph. Some books use the phrase’ scores are plotted in a Euclidian space’. What this means is that the scores can be plotted in a Cartesian axes system, another notation is ∣., and the Pythagoras theorem can be used to calculate distances between scores. The problem is that PCA is based on the correla

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https://doi.org/10.1057/9781137405579me series. It is a misconception to believe that most of the statistical methods discussed earlier in this book cannot be applied on time series. Provided the appropriate steps are made, one can easily apply linear regression or additive modelling on time series. The same holds for principal compone

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https://doi.org/10.1057/9781137405579noted that they are not restricted to being straight lines. Some of the methods can be applied on univariate time series and others require multiple time series. If the data are available on a monthly basis, one should make a distinction between seasonal variation and long-term patterns. In order to