Abstract
Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers governing the observed conditions. This study uses data from 29 sentinel landscapes (4640 plots) across the southern Africa. We used T-Square distance method to sample trees. Allometric models were used to estimate aboveground tree biomass from which aboveground biomass carbon stock (AGBCS) was derived for each site. Results show average tree density of 502 trees·ha−1 with semi-arid areas having the highest (682 trees·ha−1) and arid regions the lowest (393 trees·ha−1). The overall AGBCS was 56.4 Mg·ha−1. However, significant site to site variability existed across the region. Over 60 fold differences were noted between the lowest AGBCS (2.2 Mg·ha−1) in the Musungwa plains of Zambia and the highest (138.1 Mg·ha−1) in the scrublands of Kenilworth in Zimbabwe. Semi-arid and humid sites had higher carbon stocks than sites in sub-humid and arid regions. Anthropogenic activities also influenced the observed carbon stocks. Repeated measurements would reveal future trends in tree cover and carbon stocks across different systems.
Highlights
Woody plants in forests, croplands and rangelands of southern Africa play crucial socio-economic and ecological functions [1,2]
In addition to ecological limits, woody biomass stocks vary across landscapes as a result of land cover and land use changes associated with anthropogenic activities [4,5]
Understanding spatial variability of carbon stock across land use and eco-zones can play a crucial role in the design of management strategies
Summary
Woody plants in forests, croplands and rangelands of southern Africa play crucial socio-economic and ecological functions [1,2]. In addition to being a larger pool of terrestrial carbon sink, biomass is the chief source of energy for more than 80% of the population and replenishes soil fertility in traditional farming systems [3]. In addition to ecological limits, woody biomass stocks vary across landscapes as a result of land cover and land use changes associated with anthropogenic activities [4,5]. Different approaches have been used to estimate carbon stock and understand drivers of biomass distribution and extraction [6,7,8]. The errors associated with sample size and topographic differences can be resolved by estimating distribution and density at larger
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