Landscape‐scale variation in plant community composition of an African savanna from airborne species mapping

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.

Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

“…The spatial distribution of trees in the study area has shown concentration of woody vegetation along the river valley, as attributed to fertile soil deposits from upland areas [73]. Further, Scholtz et al and Baldeck et al [74,75] cited soil catenal formations and associated soil and hydrological characteristics as major influences on landscape-scale vegetation structure and compositional variability.…”

“…The spatial distribution of woody biomass around Skukuza is highly variable and this study showed higher biomass values occurring more frequently around seasonal rivers and stream valleys. Studies by [14,75,77,78] have cited soil catenal formations and associated soil and hydrological characteristics as major influences on landscape-scale vegetation structure and compositional variability. This is also visible in biomass change and landcover overlay maps.…”

Identifying drivers that influence the spatial distribution of woody vegetation in Kruger National Park, South Africa

“…Using aerial remote sensing mapping techniques, Baldeck et al (2014) illustrated that patterns in community structure were strongly linked to catenal poitions, alluding to the importance of geomorphology and the associated soil types in shaping savanna vegetation communities. Furthermore Sankaran et al (2005) highlighted the importance of rainfall in maintaining woody cover in savannas, particularly how future changes in precipitation may influence global savanna distribution and dynamics (complimented by recent work done by February et al [2013] and Kulmatiski and Beard [2013]).…”

“…Venter et al (2003) provided an in-depth description of the soil types and their associated vegetation, from the broadest (landscape scale) to the finest scale (catenal sequences). Baldeck et al (2014) recently conducted a study in the KNP that showed, using airborne species mapping, that species composition found within catenal sequences varied substantially, highlighting the heterogeneous landscapes found within KNP. Species distribution studies are seldom conducted at the landscape scale in the KNP due to the time and financial constraints associated with field data collection.…”

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

“…Similar to vegetation and wetland mapping, hyperspectral data perform high in species mapping and plant invasion applications during the last years (He et al 2011), especially in areas of high habitat and species diversity (Nagendra et al 2013), and are widely employed (Clark and Roberts 2012;Artigas and Pechmann 2010;Féret and Asner 2013;Colgan et al 2012;Hestir et al 2008;Baldeck et al 2014;Ghiyamat et al 2013;Pengra et al 2007;Miao et al 2006;Somers and Asner 2012). Thenkabail et al (2004) demonstrated the use of hyperspectral data by simulating the bands of Hyperion with a hand-held spectroradiometer to discriminate vegetation and agricultural crops.…”