Tree-ring analysis and stem biomass estimation of limba (Terminalia superba Engl. & Diels) in the framework of sustainable forest management

Sustainable forest management primarily depends on the availability of quantitative data, often not available in tropical forests. The lack of long-term data on tree growth, wood production and carbon stocks hampers the implementation of sustainable forest management and possible financing by Kyoto Protocol related tools like REDD+ and Clean Development Mechanisms. Africa is the continent with the lowest percentage of sustainably managed forests and especially African rainforests are currently poorly sampled. Data on wood production and carbon stocks can be collected in several ways but mostly originate from large-scale inventories or repeated measurements of permanent sample plots. These methods are time- and labour-intensive in tropical forests. Moreover, the inventory data require a temporal scale that enables long-term planning. Measurements of carbon stock include the weighing of aboveground biomass of complete trees. Pantropical models are based on these destructive measurements and use variables such as diameter, height and wood density to estimate aboveground biomass in the world’s tropical forests. These models are based on biomass measurements of a large range of tree species and diameters. African rainforests remain underrepresented in these datasets, creating large uncertainties on their carbon stock estimates. Tree-ring observations and detailed information of wood density enable the collection of long-term, accurate data on wood production and carbon stocks in a less destructive, less expensive way. Both approaches are performed on Terminalia superba Engl. & Diels, a long-lived pioneer species. Stem disks and increment cores of planted and natural forest trees were collected in Ivory Coast and in the southernmost part of the Mayombe Forest in the Democratic Republic of Congo. Annual tree rings are observed in both study regions. Growth of T. superba appears to be related to global climate variables like the El Niño-Southern Oscillation in both study regions but a clear link with local precipitation patterns is only found in the Mayombe Forest. Growth curves were also more directly used to document sustainable forest management. On the one hand, growth curves offer the opportunity to calculate growth-based variables for sustained yield like biological rotation ages and associated minimum logging diameters, variables that appeared site-specific. On the other hand, a study on growth changes revealed that T. superba generally reaches the canopy without releases or suppressions, validating that this species does not demand for intensive silvicultural management. Sustainable forest management of T. superba nevertheless appears dependent on forest type and cannot just be scaled up to the species level. Wood density was measured directly at high resolutions (50 μm) on increment cores from the Ivorian sample trees, using state-of-the-art helical X-ray scanning. Combining annual tree-ring data and pith-to-bark wood density profiles enables the extraction of annual wood densities. Wood density increases from pith to bark and allows for detailed estimates of carbon stocks over time using individual ring data. The assumed overestimation of carbon stocks in tropical Africa was confirmed and related to the use of fixed instead of annual wood densities. Furthermore, pantropical models, including those with wood density as a variable, probably even lead to higher overestimates. This work confirms the huge potential of tree-ring analysis and detailed wood density data for long-term planning of sustainable forest management and carbon stocks. Both methods can be used complementary to inventories, combining the diversity of inventory variables (height, recruitment, mortality) with tree rings that extend decades to centuries into time. A larger sample size, including older trees, is recommended to lengthen regional tree-ring chronologies for future dendroclimatological studies. It would also enable a better detection of sampling biases, more reliable estimates of the culmination of growth variables and serve as a solid base for bootstrapping. Apart from the tree level and the inter-annual level, the obtained high-resolution wood density profiles offer also possibilities to study intra-annual density variations and their possible relation with climate and wood anatomy