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Abstract In savannas, partitioning of below‐ground resources by depth could facilitate tree–grass coexistence and shape vegetation responses to changing rainfall patterns. However, most studies assessing tree versus grass root‐niche partitioning have focused on one or two sites, limiting generalization about how rainfall and soil conditions influence the degree of rooting overlap across environmental gradients.We used two complementary stable isotope techniques to quantify variation (a) in water uptake depths and (b) in fine‐root biomass distributions among dominant trees and grasses at eight semi‐arid savanna sites in Kruger National Park, South Africa. Sites were located on contrasting soil textures (clayey basaltic soils vs. sandy granitic soils) and paired along a gradient of mean annual rainfall.Soil texture predicted variation in mean water uptake depths and fine‐root allocation. While grasses maintained roots close to the surface and consistently used shallow water, trees on sandy soils distributed roots more evenly across soil depths and used deeper soil water, resulting in greater divergence between tree and grass rooting on sandy soils. Mean annual rainfall predicted some variation among sites in tree water uptake depth, but had a weaker influence on fine‐root allocation.Synthesis. Savanna trees overlapped more with shallow‐rooted grasses on clayey soils and were more distinct in their use of deeper soil layers on sandy soils, consistent with expected differences in infiltration and percolation. These differences, which could allow trees to escape grass competition more effectively on sandy soils, may explain observed differences in tree densities and rates of woody encroachment with soil texture. Differences in the degree of root‐niche separation could also drive heterogeneous responses of savanna vegetation to predicted shifts in the frequency and intensity of rainfall.
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A LiDAR‐driven pruning algorithm to delineate canopy drainage areas of stemflow and throughfall drip points
Precipitation channelled down tree stems (stemflow) or into drip points of ‘throughfall’ beneath trees results in spatially concentrated inputs of water and chemicals to the ground. Currently, these flows are poorly characterised due to uncertainties about which branches redirect rainfall to stemflow or throughfall drip points.We introduce a graph theoretic algorithm that ‘prunes’ quantitative structural models of trees (derived from terrestrial LiDAR) to identify branches contributing to stemflow and those contributing to throughfall drip points. To demonstrate the method's utility, we analysed two trees with similar canopy sizes but contrasting canopy architecture and rainfall partitioning behaviours.For both trees, the branch ‘watershed’ area contributing to stemflow (under conditions assumed to represent moderate precipitation intensity) was found to be only half of the total ground area covered by the canopy. The study also revealed significant variations between trees in the number and median contribution areas of modelled throughfall drip points (69 vs. 94 drip points tree−1, with contributing projected areas of 28.6 vs. 7.8 m2tree−1, respectively). Branch diameter, surface area, volumes and woody area index of components contributing to stemflow and throughfall drip points may play a role in the trees' differing rainfall partitioning behaviours.Our pruning algorithm, enabled by the proliferation of LiDAR observations of canopy structure, promises to enhance studies of canopy hydrology. It offers a novel approach to refine our understanding of how trees interact with rainfall, thereby broadening the utility of existing LiDAR data in environmental research.
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- Award ID(s):
- 2213623
- PAR ID:
- 10596346
- Publisher / Repository:
- British Ecological Society
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 15
- Issue:
- 11
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 1997 to 2009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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