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CCA was developed in 1986 by Cajo ter Braak and implemented in the program CANOCO, an extension of DECORANA. To date, CCA is one of the most popular multivariate methods in ecology, despite the availability of contemporary alternatives. CCA was originally derived and implemented using an algorithm
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The requirements of a CCA are that the samples are random and independent. Also, the data are categorical and that the independent variables are consistent within the sample site and error-free. The original publication states the need for equal species tolerances, equal species maxima, and
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technique that determines axes from the response data as a unimodal combination of measured predictors. CCA is commonly used in
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in order to extract gradients that drive the composition of ecological communities. CCA extends
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of weighted averaging, though
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equispaced or uniformly distributed species optima and site scores.
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with regression, in order to incorporate predictor variables.
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Multivariate
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