A comparison of reciprocal averaging and non-centred principal components analysis

✍ Scribed by Ezcurra, Exequiel

• Publisher: Springer-Verlag
• Year: 1987
• Tongue: English
• Weight: 546 KB
• Volume: 71
• Category: Article
• ISSN: 1573-5052
• DOI: 10.1007/bf00048510

✦ Synopsis

Non-centred Principal Components Analysis (NPCA) ordinates sites and species simultaneously, and can be solved either by direct iteration or by eigenvector calculation. The weight of sites and species in the analysis is proportional to their overall abundance. Because of this, the method is not susceptible to distortion by rare species, as is the case with Reciprocal Averaging (RA). Detrending techniques can also be applied to this method to eliminate arch effects.

When NPCA was tried with field data, it produced ordination axes that were significantly associated to independently measured environmental variables. In contrast, RA failed to produce axes related to environmental factors, even after the main rare species had been eliminated from the analysis.