Analyzing community‐weighted trait means across environmental gradients: should phylogeny stay or should it go?

Abstract

Functional traits mediate ecological responses of organisms to the environment, determining community structure. Community-weighted trait means (CWM) are often used to characterize communities by combining information on species traits and distribution. Relating CWM variation to environmental gradients allows for evaluating species sorting across the metacommunity, either based on correlation tests or ordinary least squares (OLS) models. Yet, it is not clear if phylogenetic signal in both traits and species distribution affect those analyses. On one hand, phylogenetic signal might indicate niche conservatism along clade evolution, reinforcing the environmental signal in trait assembly patterns. On the other hand, it might introduce phylogenetic autocorrelation to mean trait variation among communities. Under this latter scenario, phylogenetic signal might inflate type I error in analysis relating CWM variation to environmental gradients. We explore multiple ways phylogenetic history may influence analysis relating CWM to environmental gradients. We propose the concept of neutral trait diffusion, which predicts that for a functional trait x, CWM variation among local communities does not deviate from the expectation that x evolved according to a neutral evolutionary process. Based on this framework we introduce a graphical tool called neutral trait diffusion representation (NTDR) that allows for the evaluation of whether it is necessary to carry out phylogenetic correction in the trait prior to analyzing the association between CWM and environmental gradients. We illustrate the NTDR approach using simulated traits, phylogenies and metacommunities. We show that even under moderate phylogenetic signal in both the trait used to define CWM and species distribution across communities, OLS models relating CWM variation to environmental gradients lead to inflated type I error when testing the null hypothesis of no association between CWM and environmental gradient. To overcome this issue, we propose a phylogenetic correction for OLS models and evaluate its statistical performance (type I error and power). Phylogeny-corrected OLS models successfully control for type I error in analysis relating CWM variation to environmental gradients but may show decreased power. Combining the exploratory tool of NTDR and phylogenetic correction in traits, when necessary, guarantees more precise inferences about the environmental forces driving trait-mediated species sorting across metacommunities.

Combining functional traits and phylogeny to disentangling Amazonian butterfly assemblages on anthropogenic gradients

“…2). Considering only traits that showed a significant relationship with forest gradients, we tested for the importance of the succession stages and the fragment sizes separately, performing a CWM.sig analysis (Duarte et al 2018). Firstly, we tested the effect both forest fragmentation and succession in view of the functional responses (all fragments as a single category vs. continuous forest; all succession stages as a single category vs. continuous forest).…”

“…Some trait-environment relationships across environmental gradients can result from phylogenetic influence (Pavoine et al 2014, Duarte et al 2018. In other words, evolutionary closer lineages in butterflies show similar functional traits to environmental variation also due to their shared evolutionary history.…”

“…These characteristics can summarize the response many organisms give to forest area suppression, and to help understand their occurrence in different habitats (Vandewalle et al 2010). This is possible when both life traits and species composition across communities are phylogenetically structured (Duarte et al 2018). This is possible when both life traits and species composition across communities are phylogenetically structured (Duarte et al 2018).…”

Trait‐based numerical classification of mesic and wet grasslands in Poland

“…With the application of community‐weighted mean in the description of plot‐level trait values, and using their Euclidean distances as dissimilarity measure, we neglected the role of intraspecific variation, despite growing evidence on its significant role in community assembly and response to environmental gradients (Bolnick et al, ; Siefert et al, ; Violle et al, ). Phylogenetic constraints may also bias the relationship between CWM values and an environmental gradient (Duarte, Debastiani, Carlucci, & Diniz‐Filho, ). Since there is no obvious implementation of phylogenetic correction into a classification framework yet, we neglected this effect.…”

“…Phylogenetic constraints may also bias the relationship between CWM values and an environmental gradient (Duarte, Debastiani, Carlucci, & Diniz-Filho, 2018 we neglected this effect. Despite the greatest and honourable efforts of database curators, differences in measurement protocols or technicalities may have caused an amount of variation between data sets coming from different providers.…”