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Decomposing changes in phylogenetic and functional diversity over space and time
Author(s) -
Chalmandrier Loïc,
Münkemüller Tamara,
Devictor Vincent,
Lavergne Sébastien,
Thuiller Wilfried
Publication year - 2015
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12297
Subject(s) - diversity (politics) , temporal scales , biodiversity , scale (ratio) , spatial ecology , gamma diversity , antenna diversity , phylogenetic diversity , range (aeronautics) , decomposition , diversity index , computer science , ecology , beta diversity , geography , phylogenetic tree , biology , species richness , cartography , telecommunications , biochemistry , materials science , sociology , anthropology , antenna (radio) , gene , composite material
Summary The α‐, β‐, γ‐diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever‐increasing availability of large‐scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity. Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α‐, β‐, γ‐decomposition of functional or phylogenetic diversity over space and time, thereby combining their respective properties. We also developed guidelines for interpreting both temporal and spatial β‐diversities and their interaction. We characterized the range of β‐diversity estimates and their relationship to the nested decomposition of diversity. Using simulations, we empirically demonstrated that temporal and spatial β‐diversities are independent from each other and from α‐ and γ‐diversities when the study design is balanced, but not otherwise. Furthermore, we showed that the interaction term between the temporal and the spatial β‐diversities lacked such properties. We illustrated our methodology with a case study of the spatio‐temporal dynamics of functional diversity in bird assemblages in four regions of France. Based on these data, our method makes it possible to discriminate between regions experiencing different diversity changes in time. Our methodology may therefore be valuable for comparing diversity changes over space and time using large‐scale data sets of repeated surveys.