Potential of tree-ring analysis in a wet tropical forest: A case study on 22 commercial tree species in Central Africa

Implementing sustainable forest management requires basic information on growth, ages, reproduction and survival of exploited tree species. This information is generally derived from permanent sample plots where individual trees are monitored. Accurately estimating growth rates and especially tree ages from plots is however challenging, as plots often contain only few individuals of the exploited species and monitoring periods cover only a fraction of the life-span of most trees. Alternatively, tree-ring analysis is increasingly used to obtain accurate age estimates and growth rates for tropical tree species, especially in regions with seasonally harsh conditions. However, for species from wet tropical forests (>4000 mm year-1 rainfall) few tree-ring studies exist. Under persistent high levels of rainfall, formation of distinct tree rings is uncertain due to the lack of strong seasonal variation in climate factors. Here we evaluated the potential of applying tree-ring analysis on commercial tree species in a wet tropical forest in Central-Africa. For this purpose we screened the wood anatomy of 22 tree species for the presence of tree-ring structures and, on a subset of five species, we assessed crossdating potential and evaluated the annual character of tree-ring formation by radiocarbon dating. A total of 14 of the 22 tree species showed distinct tree-ring boundaries. Radiocarbon proved annual tree-ring formation in four of the five tested species. Crossdating between trees was problematic for all species and impeded exactly dating each detected ring and building tree-ring chronologies. We also show that diameter growth rates vary strongly between and among species, with important consequences for the calculation of future timber yields. Tree-ring analysis can thus be applied on tree species growing in wet tropical forests to obtain growth rates. We argue that tree-ring analysis should actually be applied on more tree species from different areas to obtain accurate, site specific growth data. This data is urgently required to design and improve sustainable forest management practices