Email updates

Keep up to date with the latest news and content from BMC Ecology and BioMed Central.

Open Access Open Badges Research article

Longevity and growth of Acacia tortilis; insights from 14C content and anatomy of wood

Gidske L Andersen* and Knut Krzywinski

Author Affiliations

Department of Biology, University of Bergen, P.O.Box 7800, N-5020 Bergen, Norway

For all author emails, please log on.

BMC Ecology 2007, 7:4  doi:10.1186/1472-6785-7-4

Published: 15 June 2007



Acacia tortilis is a keystone species across arid ecosystems in Africa and the Middle East. Yet, its life-history, longevity and growth are poorly known, and consequently ongoing changes in tree populations cannot be managed in an appropriate manner. In other arid areas parenchymatic bands marking growth zones in the wood have made dendrochronological studies possible. The possibilities for using pre- and post-bomb 14C content in wood samples along with the presence of narrow marginal parenchymatic bands in the wood is therefore tested to gain further insight into the age, growth and growth conditions of A. tortilis in the hyper-arid Eastern Desert of Egypt.


Based on age scenarios and the Gompertz growth equation, the age of trees studied seems to be from 200 up to 650 years. Annual radial growth estimated from calibrated dates based on the post-bomb 14C content of samples is up to 2.4 mm, but varies both spatially and temporally. Parenchymatic bands are not formed regularly. The correlation in band pattern among trees is poor, both among and within sites.


The post-bomb 14C content of A. tortilis wood gives valuable information on tree growth and is required to assess the age scenario approach applied here. This approach indicates high longevities and slow growth of trees. Special management measures should therefore be taken at sites where the trend in tree population size is negative. The possibilities for dendrochronological studies based on A. tortilis from the Eastern Desert are poor. However, marginal parenchymatic bands can give insight into fine scale variation in growth conditions and the past management of trees.