Title
Trait-environment relationships and tiered forward model selection in linear mixed models Trait-environment relationships and tiered forward model selection in linear mixed models
Author
Faculty/Department
Faculty of Sciences. Biology
Publication type
article
Publication
Subject
Biology
Source (journal)
International journal of ecology
Volume/pages
(2012) , 12 p.
ISSN
1687-9708
Article Reference
947103
Carrier
E-only publicatie
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
To understand patterns of variation in species biomass in terms of species traits and environmental variables a one-to-one approach might not be sufficient, and a multitrait multienvironment approach will be necessary. A multitrait multienvironment approach is proposed, based on a mixed model for species biomass. In the model, environmental variables are species-dependent random terms, whereas traits are fixed terms, and trait-environment relationships are fixed interaction terms. In this approach, identifying the important trait-environment relationship becomes a model selection problem. Because of the mix of fixed and random terms, we propose a novel tiered forward selection approach for this. In the first tier, the random factors are selected; in the second, the fixed effects; in the final tier, nonsignificant terms are removed using a modified Akaike information criterion. We complement this tiered selection with an alternative selection method, namely, type II maximum likelihood. A mesocosm experiment on early community assembly in wetlands with three two-level environmental factors is analyzed by the new approach. The results are compared with the fourth corner problem and the linear trait-environment method. Traits related to germination and seedling establishment are selected as being most important in the community assembly in these wetland mesocosms.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/2ed56e/9fc716c9.pdf
Handle