Comparative study of modern phytolith assemblages from inter-tropical Africa

Abstract

We present a synthesis of modern phytolith studies from Africa, to infer the potential and limitations of phytolith assemblages to reconstruct vegetation and tree cover density. The modern dataset includes 149 phytolith assemblages of surface soil samples from 10 phytogeographical zones and sub-zones from East and West Africa, as well as 500 m-resolution satellite estimates of the percent tree cover at the sampling sites. To test the potential of phytolith assemblages to discriminate vegetation types we used principal component analysis. For each phytogeographical zone and sub-zone, we also provided the mean values, standard errors, and 95% confidence intervals for the means obtained on the modern African dataset for the abundance of the 13 most common phytolith types preserved in soil samples, and for four phytolith indices. Results from the modern African dataset show that 1) the relative abundances of 11 (out of 13) phytolith types allow discrimination of all vegetation zones but the Somalia–Masaï steppe region, which at elevation < 600 m asl, exhibits a high proportion of rondel and trapeziform short cell phytoliths, like in the Afromontane region; 2) the co-occurrence of rondels and trapeziform polylobates characterises zones above 1900 m asl and/or current annual temperatures < 19 °C; 3) the relative abundance of globular phytoliths (granulate, smooth, and echinate) is better correlated to 500 m-resolution satellite estimates of the tree cover ( R 2 = 0.60 for n = 149, and R 2 = 0.57 for n = 85, p < 0.005) than is the abundance of arboreal pollen ( R 2 = 0.42, p < 0.005, only for n = 85). The tree cover, however, is largely under-estimated in the Afromontane zone, where globular phytoliths do not trace high-elevation forests. Limitations in our interpretation do exist, but could be overcome in the future through additional studies along an elevation/temperature gradient in the Somalia–Masaï region of East Africa, and with more precise identifications of phytolith types and sub-types.