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Spatiotemporal scaling of plant species richness and functional diversity in a temperate semi‐natural grassland
Author(s) -
White Hannah J.,
Montgomery W. Ian,
Pakeman Robin J.,
Len Jack J.
Publication year - 2018
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/ecog.03111
Subject(s) - species richness , biodiversity , ecology , grassland , species diversity , gamma diversity , ecosystem , macroecology , diversity (politics) , alpha diversity , geography , biology , sociology , anthropology
The accumulation of biodiversity in space and time has been modelled extensively using the species–area relationship and the species–time relationship, respectively. Recently, these models have been combined into time–area curves in order to investigate spatiotemporal scaling of species richness. This study expands on previous research by applying these spatiotemporal models to functional diversity. Understanding spatiotemporal dynamics of ecological traits is important due to their crucial role in ecosystem functioning and mediating species responses to environmental change. We present a new function based on the semi‐logarithmic species–area relationship, which was applied with a power function to vegetation survey data from Scottish machair grassland for both species richness and two measures of functional diversity. When taking a whole‐study approach using non‐linear mixed effects models, the semi‐logarithmic function used here shows a positive time–area interaction for species richness, contrasting with the negative interaction of the power law found in previous investigations. Although there was a negative time–area interaction for functional diversity measures at the whole‐study scale, parameter estimates were inconsistent at the individual site level. Overall, the results reveal differing spatiotemporal dynamics of species and their traits and suggest that the appropriate scale for space‐for‐time substitutions depends on the aspect of biodiversity being investigated. The new model developed in this study, and the novel application to functional diversity, opens up future possible research into spatiotemporal dynamics of biodiversity.

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