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




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Chinese Science Bulletin

, Volume 56, Issue 24, pp 2545–2552

First Online: 06 August 2011Received: 25 February 2011Accepted: 13 May 2011

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.

Keywordsspecies interaction non-parametric estimation correlation coefficient varying coefficient analysis chaotic oscillations density dependence indeterminate interaction These authors contributed equally to this work.

This article is published with open access at Springerlink.com

Electronic Supplementary MaterialSupplementary material is available for this article at 10.1007-s11434-011-4564-2 and is accessible for authorized users.

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Autor: Lei Shi - RuiWu Wang - LiXing Zhu - WeiMing Zen - WangLi Xu - Qi Zheng

Fuente: https://link.springer.com/article/10.1007/s11434-011-4564-2







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