Varying coefficient analysis for indeterminate species interactions with non-parametric estimation, exemplifying with a fig-fig wasp system

Lei Shi, Rui Wu Wang, Lixing ZHU, Wei Ming Zen, Wang Li Xu, Qi Zheng

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Research on species interactions has generally assumed that species have a fixed interaction and therefore linear or non-linear parametric regression models (e. g. exponential, logistic) have been widely used to describe the species interaction. However, these models that describe the relationship between interacting species as a specific functional response might not be appropriate for real biological communities, for instance, in a chaotic system, when the species relationship varies among different situations. To allow a more accurate description of the relationship, we developed a species correlation model with varying coefficient analysis, in which a non-parametric estimation is applied to identify, as a function of related factors, variation in the correlation coefficient. This was applied to a fig-fig wasp model system. When the effect of the factors on the relationship can be described with parameters, the new method reduces to traditional parametric correlation analysis. In this way, the new method is more general and flexible for empirical data analyses, but different by allowing investigation of whether a species interaction varies with respect to factors, and of the factors that maintain or change the species interaction. This method will have important applications in both theoretical and applied research (e. g. epidemiology, community management).

Original languageEnglish
Pages (from-to)2545-2552
Number of pages8
JournalChinese Science Bulletin
Volume56
Issue number24
DOIs
Publication statusPublished - Aug 2011

Scopus Subject Areas

  • General

User-Defined Keywords

  • chaotic oscillations
  • correlation coefficient
  • density dependence
  • indeterminate interaction
  • non-parametric estimation
  • species interaction
  • varying coefficient analysis

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