funspace: An R package to build, analyse and plot functional trait spaces
DIVERSITY AND DISTRIBUTIONS(2024)
摘要
Aim: Functional trait space analyses are pivotal to describe and compare organisms' functional diversity across the tree of life. Yet, there is no single application that streamlines the many sometimes-troublesome steps needed to build and analyse functional trait spaces. Innovation: To fill this gap, we propose funspace, an R package to easily handle bivariate and multivariate 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 publication-ready figures representing the outputs obtained from previous modules. We provide a worked example to demonstrate a complete funspace workflow. Main Conclusions: funspace will provide researchers working with functional traits across the tree of life with a new tool 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.
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关键词
data imputation,functional diversity,functional traits,general additive models,kernel density,principal component analysis,trait space
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