What lies beneath : detecting sub-canopy changes in savanna woodlands using a three-dimensional classification method

QUESTION : Increasing population pressure, socio-economic development and associated natural resource use in savannas are resulting in large-scale land cover changes, which can be mapped using remote sensing. Is a three-dimensional (3D) woody vegetation structural classification applied to LiDAR (Light Detection and Ranging) data better than a 2D analysis to investigate change in fine-scale woody vegetation structure over 2 yrs in a protected area (PA) and a communal rangeland (CR)? LOCATION : Bushbuckridge Municipality and Sabi Sand Wildtuin, NE South Africa. METHODS : Airborne LiDAR data were collected over 3 300 ha in April 2008 and 2010. Individual tree canopies were identified using object-based image analysis and classified into four height classes: 1–3, 3–6, 6–10 and >10 m. Four structural metrics were calculated for 0.25-ha grid cells: canopy cover, number of canopy layers present, cohesion and number of height classes present. The relationship between top-of-canopy cover and sub-canopy cover was investigated using regression. Gains, losses and persistence (GLP) of cover at each height class and the four structural metrics were calculated. GLP of clusters of each structural metric (calculated using LISA – Local Indicators of Spatial Association – statistics) were used to assess the changes in clusters of eachmetric over time. RESULTS : Top-of-canopy cover was not a good predictor of sub-canopy cover. The number of canopy layers present and cohesion showed gains and losseswith persistence in canopy cover over time, necessitating the use of a 3D classification to detect fine-scale changes, especially in structurally heterogeneous savannas. Trees >3 min height showed recruitment and gains up to 2.2 times higher in the CR where they are likely to be protected for cultural reasons, but losses of up to 3.2-foldmore in the PA, possibly due to treefall caused by elephant and/or fire. CONCLUSION : Land use has affected sub-canopy structure in the adjacent sites, with the low intensity use CR showing higher structural diversity. A 3D classification approach was successful in detecting fine-scale, short-term changes between land uses, and can thus be used as amonitoring tool for savannawoody vegetation structure. Remove selectedThe Carnegie Airborne Observatory is made possible by the Avatar Alliance Foundation, Margaret A. Cargill Foundation, John D. and Catherine T. MacArthur Foundation, Grantham Foundation for the Protection of the Environment, W.M. Keck Foundation, Gordon and Betty Moore Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr. and William R. Hearst III. Application of the CAO data in South Africa is made possible by the Andrew Mellon Foundation and the endowment of the Carnegie Institution for Science.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1654-109X2016-07-31hb201

Biomass increases go under cover : woody vegetation dynamics in South African rangelands

Woody biomass dynamics are an expression of ecosystem function, yet biomass estimates do not provide information on the spatial distribution of woody vegetation within the vertical vegetation subcanopy. We demonstrate the ability of airborne light detection and ranging (LiDAR) to measure aboveground biomass and subcanopy structure, as an explanatory tool to unravel vegetation dynamics in structurally heterogeneous landscapes. We sampled three communal rangelands in Bushbuckridge, South Africa, utilised by rural communities for fuelwood harvesting. Woody biomass estimates ranged between 9 Mg ha-1 on gabbro geology sites to 27 Mg ha-1 on granitic geology sites. Despite predictions of woodland depletion due to unsustainable fuelwood extraction in previous studies, biomass in all the communal rangelands increased between 2008 and 2012. Annual biomass productivity estimates (10–14% p.a.) were higher than previous estimates of 4% and likely a significant contributor to the previous underestimations of modelled biomass supply. We show that biomass increases are attributable to growth of vegetation <5 m in height, and that, in the high wood extraction rangeland, 79% of the changes in the vertical vegetation subcanopy are gains in the 1-3m height class. The higher the wood extraction pressure on the rangelands, the greater the biomass increases in the low height classes within the subcanopy, likely a strong resprouting response to intensive harvesting. Yet, fuelwood shortages are still occurring, as evidenced by the losses in the tall tree height class in the high extraction rangeland. Loss of large trees and gain in subcanopy shrubs could result in a structurally simple landscape with reduced functional capacity. This research demonstrates that intensive harvesting can, paradoxically, increase biomass and this has implications for the sustainability of ecosystem service provision. The structural implications of biomass increases in communal rangelands could be misinterpreted as woodland recovery in the absence of three-dimensional, subcanopy information.S1 Dataset. Biomass model data. Data include 2012 LiDAR-derived average height and canopy cover extraction metrics, as well as field-work based allometry. Each line item is per 25 m x 25 m grid cell. Metadata are included in the dataset.S2 Dataset. Biomass and subcanopy data. Data include 2008 and 2012 biomass estimates derived from biomass models as well as % subcanopy returns for voxel data for the height class categories: 1-3m, 3-5m, 5-10m and >10m. Each line item is per 25 m x 25 m grid cell. Data are organized per land extraction category into separate worksheets. Metadata are included in the dataset.S3 Dataset. Biomass changes (Mg ha-1) in relation to relative height and canopy cover change. Data include biomass change estimates (2008–2012), percentage height and canopy cover changes for each 25 m x 25 m grid cell. Each height class (relative to height in 2008) are shown on separate worksheets. Metadata are included in the dataset.S1 Fig. Site-specific biomass model residuals. The residual spread demonstrates heteroskedasticity with increasing biomass fitted values for rangelands with a) high, b) intermediate and c) low extraction pressure.S2 Fig. Biomass changes (%) relative to height-specific change in subcanopy returns (%). Height categories are: 1–3 m, 3–5 m, 5–10 m and >10 m.The Carnegie Airborne Observatory (CAO) is made possible by the Avatar Alliance Foundation, Margaret A. Cargill Foundation, John D. and Catherine T. MacArthur Foundation, Grantham Foundation for the Protection of the Environment, W. M. Keck Foundation, Gordon and Betty Moore Foundation, Mary Anne Nyburg Baker and G. Leonard Baker, Jr., and William R. Hearst III. Application of the CAO data in South Africa is made possible through the Andrew Mellon Foundation and the endowment of the Carnegie Institution for Science, the Council for Scientific and Industrial Research (CSIR), and the South African Department of Science and Technology (grant agreement DST/ CON 0119/2010, Earth Observation Application Development in Support of SAEOS). CSIR coauthors are supported by the European Union’s Seventh Framework Programme (FP7/2007-2013, grant agreement n°282621, AGRICAB). PJM acknowledges funding from the National Research Foundation (NRF: SFH1207203615). Additionally, PJM and ETFW acknowledge the DST-NRF Centre of Excellence in Tree Health Biotechnology (CTHB) and, PJM and BFNE, the Applied Centre for Climate and Earth Systems Science (ACCESS). BFNE acknowledges financial support from Exxaro.http://www.plosone.orgam201

Precipitation gradients drive high tree species turnover in the woodlands of eastern and southern Africa

Savannas cover one-fifth of the Earth's surface, harbour substantial biodiversity, and provide a broad range of ecosystem services to hundreds of millions of people. The community composition of trees in tropical moist forests varies with climate, but whether the same processes structure communities in disturbance-driven savannas remains relatively unknown. We investigate how biodiversity is structured over large environmental and disturbance gradients in woodlands of eastern and southern Africa. We use tree inventory data from the Socio-Ecological Observatory for Studying African Woodlands (SEOSAW) network, covering 755 ha in a total of 6780 plots across nine countries of eastern and southern Africa, to investigate how alpha, beta, and phylogenetic diversity varies across environmental and disturbance gradients. We find strong climate-richness patterns, with precipitation playing a primary role in determining patterns of tree richness and high turnover across these savannas. Savannas with greater rainfall contain more tree species, suggesting that low water availability places distributional limits on species, creating the observed climate-richness patterns. Both fire and herbivory have minimal effects on tree diversity, despite their role in determining savanna distribution and structure. High turnover of tree species, genera, and families is similar to turnover in seasonally dry tropical forests of the Americas, suggesting this is a feature of semiarid tree floras. The greater richness and phylogenetic diversity of wetter plots shows that broad-scale ecological patterns apply to disturbance-driven savanna systems. High taxonomic turnover suggests that savannas from across the regional rainfall gradient should be protected if we are to maximise the conservation of unique tree communities