Networks of plants: how to measure similarity in vegetable species
arXiv:1602.05887
Abstract
Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature.
arXiv comment18 pages, 6 figures, 7 tables, 1 section of Supplementary Material
References in corpus (10)
- Fast unfolding of communities in large networks
- Finding and evaluating community structure in networks
- Finding community structure in very large networks
- Fast algorithm for detecting community structure in networks
- The architecture of complex weighted networks
- Near linear time algorithm to detect community structures in large-scale networks
- Hierarchical structure and the prediction of missing links in networks
- Emotional Dynamics in the Age of Misinformation
- Twitter-based analysis of the dynamics of collective attention to political parties
- Preferential Exchange: Strengthening Connections in Complex Networks