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In order to investigate how environmental factors other than light availability affect tree architecture, differences in branching architecture and allometry were analysed in populations of Acacia karroo Hein. from three different environments in South Africa: forests, savannas and arid-shrublands. Factors such as fire and herbivory have a large effect on tree life history in certain environments and are likely to have selected for trees that have different architectures from those of forest trees, whose major limitation is light assimilation. Significant differences were found in stem architecture and branching architecture between trees in each environment. Compared with forest trees, trees in savannas had an elongated growth form with small canopy and leaf areas, and tall, thin, unbranched trunks. Trees in arid areas showed opposite trends with wider canopies, and increased lateral branching. Savanna trees had significantly smaller spines than trees in other environments, and both forest and savanna trees showed delayed reproduction. These differences are probably related to a trade-off between an architecture geared towards rapid height-gain and one promoting lateral spread, and can be explained with reference to the different selective pressures in each environment. In forests, vertical and horizontal growth are both important. However, in savannas there is a great pressure for rapid vertical growth to escape fires, while in arid areas a defensive, lateral growth form is selected for. Savanna trees and arid karoo trees have evolved architectures that are more extreme vertically and laterally than the range of architectures displayed in a forest community. [ABSTRACT FROM AUTHOR]

The need for accurate quantification of the amount of carbon stored in the environment has never been greater. Carbon sequestration has become a vital component of the battle against global climate change, and monitoring and quantifying this process are major challenges for policymakers. Plant allometric equations allow managers and scientists to quantify the biomass contained in a tree without cutting it down, and therefore can play a pivotal role in measuring carbon sequestration in forests and savannahs. These equations have been available since the beginning of the 20th century, but their usefulness depends on the ability to estimate the error associated with the equations - something which has received scant attention in the past. This paper provides a method based on the theory of linear regression and the lognormal distribution to derive confidence limits for estimates of biomass derived from plant allometric equations. Allometric equations for several southern African savannah species are provided, as well as the parameters and equations required to calculate the confidence intervals. This method was applied to data collected from a sampling campaign carried out in a savannah landscape at the Skukuza flux site, Kruger National Park, South Africa. Here the error was 10% of the total site biomass for the woody biomass and 2% for the leaf biomass. When the data were split into individual plots and used to estimate site biomass (as would occur in most sampling schemes) the error increased to 16% and 12% of the woody and leaf biomasses, respectively, as the sampling errors were added to the errors in the allometric equation. These methods can be used in any discipline that applies allometric equations, such as health sciences and animal physiology. [ABSTRACT FROM AUTHOR]