Abstract
AbstractAimExisting phytogeographical frameworks for tropical Africa lack either spatial completeness, unit definitions smaller than the regional scale or a quantitative approach. We investigate whether physical environmental variables can be used to interpolate floristically defined vegetation units, presenting an interpolated, hierarchical, quantitative phytogeographical framework for tropical Africa, which is compared to previously defined regions.LocationTropical mainland Africa 24°N to 24°S.Taxon31,046 vascular plant species and infraspecific taxa.MethodsWe calculate a betasim dissimilarity matrix from a comprehensive whole‐flora database of plant species distributions. We investigate environmental correlates of floristic turnover with local non‐metric multidimensional scaling. We derive a hierarchical biogeographical framework by clustering the dissimilarity matrix. The framework is modelled using a classification decision tree method and 12 physical environmental variables to interpolate and increase the resolution of the framework across the study region.ResultsFloristic turnover is related strongly to water availability and temperature, with smaller contributions from land cover, topographic ruggedness and lithology. Region can be predicted with 90% accuracy by the model. We define 19 regions and 99 districts. We find a novel arrangement of the arid regions. Regional subdivision within the savanna biome is supported with minor variation to borders. Within the forests of west and central Africa, our whole‐flora gridded regionalization supports the divisions identified by a previous analysis of trees only.Main conclusionsPhysical environmental variables can be used to predict floristically defined vegetation units with very high accuracy, and the approach could be pursued for other incompletely sampled taxa and areas outside of tropical Africa. Geographical coherence is higher than in previous quantitative phytoregional definitions. For most tropical African vascular plant species, we provide predictions of which species will occur within each mapped district and region of tropical Africa. The framework should be useful for future studies in ecology, evolution and conservation.
Highlights
By defining areas of relatively homogeneous species composition, biogeographical frameworks provide spatial units of analysis that are useful in macroecological, evolutionary and systematic studies of the processes which shaped or maintain species distributions (Morrone, 2018)
We can use theory generated by such studies to improve the biogeographical framework itself, predicting where species are likely to occur for areas which are incompletely collected, providing increasingly complete geographical and taxonomic coverage (Holt et al, 2013)
Droissart et al used bipartite network analysis (Edler, Guedes, Zizka, Rosvall, & Antonelli, 2017). These quantitative floristic frameworks have left much of the area of tropical Africa unassigned to a spatial unit, due to the insufficiency of plant species distribution data from many parts of the continent, and because there is currently no comprehensive set of species distribution models for African plants
Summary
By defining areas of relatively homogeneous species composition, biogeographical frameworks provide spatial units of analysis that are useful in macroecological, evolutionary and systematic studies of the processes which shaped or maintain species distributions (Morrone, 2018). Droissart et al used bipartite network analysis (Edler, Guedes, Zizka, Rosvall, & Antonelli, 2017) These quantitative floristic frameworks have left much of the area of tropical Africa unassigned to a spatial unit, due to the insufficiency of plant species distribution data from many parts of the continent, and because there is currently no comprehensive set of species distribution models for African plants. The aim of this study is to present a spatially complete quantitative phytogeographical framework for tropical mainland continental Africa (24°N to 24°S) that can predict which plant species occur at regional to more local scale across the study area, useful for future studies in ecology, evolution and conservation, and to facilitate (online) identification tools. We ask: 1. Can physical environmental variables be used to predict floristically defined vegetation units?
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