Data from: Mapping beta diversity from space: Sparse Generalized Dissimilarity Modelling (SGDM) for analysing high-dimensional data

Pedro J. Leitão, Stefan Suess, Marcel Schwieder, Inês Catry, Edward Milton, Francisco Moreira, Patrick E. Osborne, Manuel J. Pinto, Sebastian Van Der Linden, Patrick Hostert & Edward J. Milton
1. Spatial patterns of community composition turnover (beta diversity) may be mapped through Generalised Dissimilarity Modelling (GDM). While remote sensing data are adequate to describe these patterns, the often high-dimensional nature of these data poses some analytical challenges, potentially resulting in loss of generality. This may hinder the use of such data for mapping and monitoring beta-diversity patterns. 2. This study presents Sparse Generalised Dissimilarity Modelling (SGDM), a methodological framework designed to improve the use...
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