Redundancy analysis (RDA) is a constrained ordination analysis used for linear relationships.
Canonical Correspondence Analysis (CCA) is a constrained multivariate ordination used to explore relationships between species abundance data and environmental variables when unimodal responses are expected.
Canonical Analysis on Principal Coordinates (CAP) is related to Principal Coordinate Analysis and allows the exploration of complex, non-linear relationships between two sets of variables, typically species data and environmental factors.
Distance-based Redundancy Analysis (db-RDA) is a constrained multivariate ordination that is related to RDA but allows the use of alternative distance matrices.
Correspondence analysis (CA) is an unconstrained ordination analysis used for unimodal relationships, preferably with ordinal abundance values.
Principal Component Analysis (PCA) is an unconstrained ordination analysis suitable for linear (monotonic) relationships.
Detrended Correspondence Analysis (DCA) is an extension of CA that aims to avoid the arch effect in the resulting ordination.
Non-Metric Multidimensional Scaling (NMDS) is a distance-based ordination that focuses on preserving the rank order of pairwise dissimilarities.
Vegetation plots collected in several East African countries, including some species attributes.
Principal Coordinate Analysis (PCOA) is a distance-based ordination that aims to compress similarity patterns into an ordination diagram.
A transect along an elevation gradient from 860 to 2,180 m asl. in a subtropical forest in Taiwan.
