Mahecha, M.D.; Martinez, A.; Lange, H. & Beck, E. (2009): <b>Identification of characteristic plant co-occurrences in neotropical secondary montane forests</b>. <i>Journal of Plant Ecology</i> <b>2</b>, 31-41.
Resource Description
Title:
Identification of characteristic plant co-occurrences in neotropical secondary montane forests
FOR816dw ID:
423
Publication Date:
2009-03-01
License and Usage Rights:
Resource Owner(s):
Individual:
Miguel D. Mahecha
Contact:
email:
webmaster <at> tropicalmountainforest.com
Individual:
Alfredo Martinez
Contact:
email:
webmaster <at> tropicalmountainforest.com
Individual:
Holger Lange
Contact:
email:
webmaster <at> tropicalmountainforest.com
Individual:
Erwin Beck
Contact:
email:
erwin.beck <at> uni-bayreuth.de
Universitätsstr. 30
Faculty of Biology, Chemistry and Geoscience
University of Bayreuth
95440 Bayreuth
Germany
Abstract:
Aims: Inferring environmental conditions from characteristic patterns of plant co-occurrences can be crucial for the development of conservation strategies concerning secondary neotropical forests. However, no methodological agreement has been achieved so far regarding the identification and classification of characteristic groups of vascular plant species in the tropics. This study examines botanical and, in particular, statistical aspects to be considered in such analyses. Based on these, we propose a novel data-driven approach for the identification of characteristic plant co-occurrences in neotropical secondary mountain forests.<br/>
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Methods: Floristic inventory data were gathered in secondary tropical mountain forests in Ecuador. Vegetation classification was performed by coupling locally adaptive isometric feature mapping, a non-linear ordination method and fuzzy-c-means clustering. This approach was designed for dealing with underlying non-linearities and uncertainties in the inventory data.<br/>
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Important Findings: The results indicate that the applied non-linear mapping in combination with fuzzy classification of species occurrence allows an effective identification of characteristic groups of co-occurring species as fuzzy-defined clusters. The selected species indicated groups representing characteristic life-form distributions, as they correspond to various stages of forest regeneration. Combining the identified ?characteristic species groups? with meta-information derived from accompanying studies indicated that the clusters can also be related to habitat conditions.<br/>
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In conclusion, we identified species groups either characteristic of different stages of forest succession after clear-cutting or of impact by fire or a landslide. We expect that the proposed data-mining method will be useful for vegetation classification where no a priori knowledge is available.
Literature type specific fields:
ARTICLE
Journal:
Journal of Plant Ecology
Volume:
2
Page Range:
31-41
Metadata Provider:
Individual:
Kristin Roos
Contact:
email:
biene.tomate <at> gmx.net
Faculty of Biology, Chemistry and Geoscience
Department of Plant Physiology
Universitätsstr. 30
95440 Bayreuth
Germany
