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Semi‐strong Hybrid Scaling, a new ordination algorithm
Author(s) -
Belbin Lee
Publication year - 1991
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.2307/3236031
Subject(s) - ordination , multidimensional scaling , scaling , algorithm , curse of dimensionality , computer science , basis (linear algebra) , principal component analysis , noise (video) , mathematics , biological system , ecology , statistics , artificial intelligence , biology , geometry , image (mathematics)
There is a small group of association measures that appear optimal for comparing sites on the basis of their species composition. These measures can accurately estimate affinity between sites when they are ecologically similar. Once sites share few or no species, these measures always under‐estimate the ‘ecological distance’ between them. A new ordination algorithm called Semi‐strong Hybrid Scaling, SHS, uses these features in an attempt to provide a better configuration of the sites. The new method is evaluated by a direct comparison of the structure in simulated data with the Hybrid method of Faith, Minchin & Belbin (1987). To evaluate SHS and compare it with Hybrid Scaling, 3240 datasets were generated using the COMPAS simulator (Minchin 1987). The data were designed to simulate as closely as possible, what is known of the distribution of species on environmental gradients. The factors included the dimensionality of the data, the number of sites and species, the shape of the species response surfaces, positioning of the sites in the simulation space, carrying capacity and level of noise. Recovery of the simulated site positions by SHS and Hybrid Scaling was evaluated using Procrustes rotation. SHS produced a better recovery in 88% of the datasets.