Physiological, morphological and functional traits of encroaching and non-encroaching savanna trees under contrasting CO2 concentrations, water stress, and grass competition, South Africa, 2022

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Authors: Brad S. Ripley, K. Simpson, Sarah Lynn Raubenheimer, Edith Joana Singini, Jones, E., T. Burgess, Richard Carkeek, Michael Denis Cramer, R.B. Dixon, Katie J. Field, H. Hawkins, Rhys Nell
+7 more N. Ngqiyaza, Nita C. M. Pallett, L. Reynolds, Elizabeth Telford, S. Vetter, Caroline E. R. Lehmann, Colin P. Osborne
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Abstract

This dataset provides physiological, morphological, and functional trait measurements for twelve African savanna tree species belonging to the Vachellia and Senegalia genera (Fabaceae family). The data encompasses six species classified as encroaching (increasing in density in African savannas) and six non-encroaching species, facilitating comparative analysis of traits facilitating encroachment ability. The variables capture sapling responses to a factorial combination of environmental conditions, specifically atmospheric carbon dioxide concentration, water availability, and interspecific grass competition. The dataset details plant performance under elevated CO2 versus ambient CO2 and contrasts well-watered and water-limited conditions. Furthermore, the data includes comparative metrics for trees grown with and without competition from the grass species Themeda triandra. All measurements were derived from saplings grown for 11 months in large pots containing local savanna soil within open-top chambers (Rhodes University Elevated CO2 Facility, Makhanda, South Africa), culminating in physiological assessments and destructive harvesting for morphological analysis. The work was supported by the Natural Environment Research Council (Grant NE/T000759/1).

Fields of Study & Subjects

Plant responses to elevated CO2 Plant Water Relations and Carbon Dynamics Ecology and Vegetation Dynamics Studies

Publication details

Journal / source
NERC Environmental Data Service
Publication date
4 February 2026
Language
EN
Document type
Dataset