Abstract
SummaryFunctional trait space analyses are pivotal to define species’ ecological strategies across the tree of life. Yet, there is no single application that streamlines the many sometimes-troublesome steps needed to build and analyze functional trait spaces.To fill this gap, we proposefunspace, an R package to easily handle bivariate and multivariate (PCA-based) functional trait space analyses. The six functions that constitute the package can be grouped in three modules: ‘Building and exploring’, ‘Mapping’, and ‘Plotting’.The building and exploring module defines the main features of a functional trait space (e.g., functional diversity metrics) by leveraging kernel density-based methods. The mapping module uses general additive models to map how a target variable distributes within a trait space. The plotting module provides many options for creating flexible and high-quality figures representing the outputs obtained from previous modules. We provide a worked example to demonstrate a completefunspaceworkflow.funspacewill provide researchers working with functional traits across the tree of life with an indispensable asset to easily explore: (i) the main features of any functional trait space, (ii) the relationship between a functional trait space and any other biological or non-biological factor that might contribute to shaping species’ functional diversity.
Publisher
Cold Spring Harbor Laboratory
Cited by
6 articles.
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