4.7 Article

Analyzing floristic inventories with multiple maps

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

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资金

  1. Max Planck Society
  2. Netherlands Organization for Scientific Research (NWO) [680.50.0908]
  3. EU

向作者/读者索取更多资源

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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