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Abstract:
Information on landscape-scale patterns in species distributions and community
types is vital for ecological science and effective conservation assessment and planning.
However, detailed maps of plant community structure at landscape scales seldom exist due to
the inability of field-based inventories to map a sufficient number of individuals over large
areas. The Carnegie Airborne Observatory (CAO) collected hyperspectral and lidar data over
Kruger National Park, South Africa, and these data were used to remotely identify .500 000
tree and shrub crowns over a 144-km2 landscape using stacked support vector machines. Maps
of community compositional variation were produced by ordination and clustering, and the
importance of hillslope-scale topo-edaphic variation in shaping community structure was
evaluated with redundancy analysis. This remote species identification approach revealed
spatially complex patterns in woody plant communities throughout the landscape that could
not be directly observed using field-based methods alone. We estimated that topo-edaphic
variables representing catenal sequences explained 21% of species compositional variation,
while we also uncovered important community patterns that were unrelated to catenas,
indicating a large role for other soil-related factors in shaping the savanna community. Our
results demonstrate the ability of airborne species identification techniques to map biodiversity
for the evaluation of ecological controls on community composition over large landscapes.
