Recognising fuzzy vegetation pattern: the spatial prediction of floristically defined fuzzy communities using species distribution modelling methods
Article first published online: 27 MAY 2013
© 2013 International Association for Vegetation Science
Journal of Vegetation Science
Volume 25, Issue 2, pages 323–337, March 2014
How to Cite
Duff, T. J., Bell, T. L., York, A. (2014), Recognising fuzzy vegetation pattern: the spatial prediction of floristically defined fuzzy communities using species distribution modelling methods. Journal of Vegetation Science, 25: 323–337. doi: 10.1111/jvs.12092
- Issue published online: 24 FEB 2014
- Article first published online: 27 MAY 2013
- Manuscript Accepted: 25 MAR 2013
- Manuscript Received: 19 SEP 2011
- Department of Sustainability and Environment
|jvs12092-sup-0001-AppendixS1.pdf||application/PDF||7K||Appendix S1. Scree plot of PCoA of species data eigenvalues computed with Bray–Curtis distances.|
|jvs12092-sup-0002-AppendixS2.pdf||application/PDF||8K||Appendix S2. Plot of Calinsky criteria values against the number of K mean clusters.|
Appendix S3. Relative frequency, relative abundance, indicator value and significance value of plant species to each community group through indicator species analysis. Only species with statistically signification associations are presented.
Appendix S4. Spatial autocorrelation assessment of model residuals, computed as Moran's I with a permutational significance test.
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