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2015 ; 10
(12
): e0145192
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Multiple Scales of Control on the Structure and Spatial Distribution of Woody
Vegetation in African Savanna Watersheds
#MMPMID26660502
Vaughn NR
; Asner GP
; Smit IP
; Riddel ES
PLoS One
2015[]; 10
(12
): e0145192
PMID26660502
show ga
Factors controlling savanna woody vegetation structure vary at multiple spatial
and temporal scales, and as a consequence, unraveling their combined effects has
proven to be a classic challenge in savanna ecology. We used airborne LiDAR
(light detection and ranging) to map three-dimensional woody vegetation structure
throughout four savanna watersheds, each contrasting in geologic substrate and
climate, in Kruger National Park, South Africa. By comparison of the four
watersheds, we found that geologic substrate had a stronger effect than climate
in determining watershed-scale differences in vegetation structural properties,
including cover, height and crown density. Generalized Linear Models were used to
assess the spatial distribution of woody vegetation structural properties,
including cover, height and crown density, in relation to mapped hydrologic,
topographic and fire history traits. For each substrate and climate combination,
models incorporating topography, hydrology and fire history explained up to 30%
of the remaining variation in woody canopy structure, but inclusion of a spatial
autocovariate term further improved model performance. Both crown density and the
cover of shorter woody canopies were determined more by unknown factors likely to
be changing on smaller spatial scales, such as soil texture, herbivore abundance
or fire behavior, than by our mapped regional-scale changes in topography and
hydrology. We also detected patterns in spatial covariance at distances up to
50-450 m, depending on watershed and structural metric. Our results suggest that
large-scale environmental factors play a smaller role than is often attributed to
them in determining woody vegetation structure in southern African savannas. This
highlights the need for more spatially-explicit, wide-area analyses using high
resolution remote sensing techniques.