Numerical Ecology and Social Network Analysis of the Forest Community in the Lienhuachih Area of Taiwan

Abstract

In this study, the integration of useful statistical methods from different disciplines for analyzing the forest community of the Lienhuachih area of central Taiwan was attempted. We employed a seriated heat map to confirm the presence of multiple community patterns in the area and used the gap statistics and a clustplot to confirm the number and structure of the patterns, respectively. A minimum spanning tree was used to display a succession series among the quadrats, and Renyi diversity was used to indicate the species composition of these patterns. The results confirmed the existence of six patterns with different biodiversity structures in which pattern C was the succession prototype of the local community patterns. Next, we used the patterns as nodes of a social network to perform bipartite network analysis. The results showed that a community network consisted of 108 taxa and six syntaxa. The syntaxa were highly vulnerable to extinction; therefore, the optimal conservation strategy for local species would be to first protect the syntaxa. The random forest method and bipartite modularity were used to analyze the dominant characteristic species of the six syntaxa. The results showed that these two methods are useful for detecting characteristic species of the syntaxa. Therefore, this study proposed a new nomenclature system, namely the Mathematic Code of Syntaxonomic Nomenclature, to support the results of numerical vegetation analysis. Finally, the potential for an apparently competitive network was examined, the role of an apparently competitive network in the local structuring community was explored, and six new associations in the Lienhuachih area were described.

Keywords

• numerical taxonomy
• random forest
• bipartite networks
• modularity analysis
• apparent competition
• minimum spanning tree