期刊
ECOLOGICAL INFORMATICS
卷 9, 期 -, 页码 1-10出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecoinf.2012.01.005
关键词
Species occurrence modeling; Data visualization; Multi-dimensional scaling; Non-metric similarities; t-Distributed Stochastic Neighbor Embedding
类别
资金
- Max Planck Society
- Netherlands Organization for Scientific Research (NWO) [680.50.0908]
- EU
Spatial observations of plant occurrences contain a wealth of information on relations among species and on the relation between species and environmental conditions. Typically, inventory data of this kind are large co-occurrence matrices, and hence, direct ecological interpretations based on expert knowledge are often very difficult. Hitherto, ordination approaches have been used to construct a virtual ordination space (represented as one or multiple scatter plots) in which species that often co-occur are situated close together, whereas species that hardly co-occur are found far apart. In this study, we investigate a recently proposed ordination approach, multiple maps t-SNE, that constructs multiple, independent ordination spaces in order to reveal and visualize complementary structure in the data. We compare multiple maps t-SNE to several conventional ordination approaches, exploring a large inventory of vascular plant occurrences (FLORKART). Our results reveal that multiple maps t-SNE is well suited for the analysis of floristic inventories. In particular, multiple maps t-SNE uncovers the major dependencies of species co-occurrences on climate and soil biogeo-chemical preconditions. (C) 2012 Elsevier B.V. All rights reserved.
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