Literature DB >> 29322322

Functional traits can improve our understanding of niche- and dispersal-based processes.

Feng Jiang1, Yanhan Xun1, Huiying Cai1, Guangze Jin2.   

Abstract

Ecologists often determine the relative importance of niche- and dispersal-based processes via variation partitioning based on species composition. Functional traits and their proxies of phylogeny are expected to increase the detection of niche-based processes and reduce the unexplained variation relative to species identity. We collected eight adult tree traits and phylogenetic data of 41 species and employed a phylogenetic fuzzy weighting method to address this issue in a 9-ha temperate forest dynamics plot. We used redundancy analysis to relate species, phylogenetic and functional compositions to environmental (soil resources and topography) and spatial variables. We also performed multi-scaled analyses on spatial variables by adding environment as the covariates to determine if functional traits increase the detection of niche-based processes at broad scales. The functional traits and intraspecific variation of the wood density among ontogenetic stages could dramatically increase the detection of niche-based processes and reduce the unexplained variation relative to species identity. Phylogenetic and functional compositions were mainly driven by total soil P and elevation, while species composition was weakly affected by multiple environmental variables. After controlling for the environment, a larger amount of the compositional variations in seed mass and maximum height were explained by finer-scaled spatial variables, indicating that dispersal processes may be important at fine spatial scales. Our results suggested that considering functional traits and their intraspecific variations could improve our understanding of ecological processes and increase our ability to predict the responses of plants to environmental change.

Keywords:  Intraspecific trait variation; Maximum height; Phylogenetic fuzzy weighting; Seed mass; Variation partitioning

Mesh:

Substances:

Year:  2018        PMID: 29322322     DOI: 10.1007/s00442-018-4060-3

Source DB:  PubMed          Journal:  Oecologia        ISSN: 0029-8549            Impact factor:   3.225


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