Rooting depth varies differentially in trees and grasses as a function of mean annual rainfall in an African savanna
A significant fraction of the terrestrial biosphere comprises biomes containing tree–grass mixtures. Forecasting vegetation dynamics in these environments requires a thorough understanding of how trees and grasses use and compete for key belowground resources. There is disagreement about the extent to which tree–grass vertical root separation occurs in these ecosystems, how this overlap varies across large-scale environmental gradients, and what these rooting differences imply for water resource availability and tree–grass competition and coexistence. To assess the extent of tree–grass rooting overlap and how tree and grass rooting patterns vary across resource gradients, we examined landscape-level patterns of tree and grass functional rooting depth along a mean annual precipitation (MAP) gradient extending from ~ 450 to ~ 750 mm year−1 in Kruger National Park, South Africa. We used stable isotopes from soil and stem water to make inferences about relative differences in rooting depth between these two functional groups. We found clear differences in rooting depth between grasses and trees across the MAP gradient, with grasses generally exhibiting shallower rooting profiles than trees. We also found that trees tended to become more shallow-rooted as a function of MAP, to the point that trees and grasses largely overlapped in terms of rooting depth at the wettest sites. Our results reconcile previously conflicting evidence for rooting overlap in this system, and have important implications for understanding tree–grass dynamics under altered precipitation scenarios.
KeywordsAfrican savanna Environmental gradients Tree–grass coexistence Two-layer model Stable isotopes
SANParks allowed access to Kruger NP for sample collection. We would like to acknowledge Navashni Govender and the Scientific Services staff at SANParks for assistance. Wayne Twine and Wits University provided access to the field site at Wits Rural Facility. Ben Ketter assisted with laboratory work, and Hloniphani Moyo, Deus Rugemalila, and Zak Ratajczak helped with field data collection. This research was partly funded by a grant from the Andrew W. Mellon Foundation. We thank Kevin Mueller and an anonymous reviewer for helpful suggestions on an earlier version of the manuscript.
RMH designed the study. RMH, JBN and MCM conducted the field work. JBN conducted the laboratory analyses, RMH analyzed the data, and RMH, JBN and MCM wrote the manuscript.
- Development Core Team R (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Guswa AJ, Celia MA, Rodriguez-Iturbe I (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resour Res 38:1–15Google Scholar
- Herr DG (1986) On the history of ANOVA in unbalanced, factorial designs: the first 30 years. Am Stat 40:265–270Google Scholar
- Venter FJ, Scholes RJ, Eckhardt HC (2003) The abiotic template and its associated vegetation pattern. In: Du Toit J, Rogers KH, Biggs H (eds) The Kruger experience: ecology and management of savanna heterogeneity. Island Press, Washington, pp 83–129Google Scholar
- Walter H (1971) Ecology of tropical and subtropical vegetation. Oliver and Boyd, EndinburghGoogle Scholar