Ecological Management of Tropical forests: Implications for climate change and Carbon Fluxes

Tropical deforestation and forest degradation contributes to more than 20% of the global greenhouse gases emitted. Deforestation and its impacts can be more easily estimated with satellite images. Concerning forest degradation, it is difficult with the actual satellite image resolutions to evaluate accurately logging and biomass damage resulting from this activity though it contributes substantially to carbon emissions in the tropics. With increasing CO2 in the atmosphere, there is an urgent need of reliable biomass estimates and carbon pools in tropical forests, most especially in Africa where there is a serious lack of data. Moist tropical forests store large amounts of carbon and need accurate allometric regressions for their estimation. In Africa the absence of species-specific or mixed-species allometric equations has lead to a broad use of pan moist tropical equations to estimate tree biomass. This lack of information has raised many discussions on the accuracy of these data, since equations were derived from biomass collected outside Africa. Developing site-specific equations and pan-moist tropical equations including data from Africa is becoming very important for most ecologists for accurate estimations of this contribution extend, necessary for adaptation and mitigation strategies on climate change impacts. Allometric equations are key tools for climate change scenarios since they are used for estimating biomass and carbon pool at local, regional and world level. Information on net primary production (NPP) resulting from direct biomass field measurements of annual tree ring width is crucial in this context, to know how forest ecosystems will grow in the future with their possible impacts on carbon pools and fluxes and also to calibrate eddy covariance measurements. The overall objective of this study was to provide a scientific contribution for adaptation or mitigation of moist tropical forests on climate change impacts. The specific objectives were to (1) analyze the stand development of a forest in the eastern Cameroon and discuss a methodology for estimating the potential carbon emissions or reductions from forest degradation, (2) develop allometric equations for accurate estimations of biomass and carbon pools in moist forests in Cameroon and also in Africa, (3) estimate carbon pools and Net Primary Productivity (NPP) and their spatial distribution on different strata and land use types of the Campo-Ma an area forest in Cameroon. This dissertation presents results from two field studies conducted at the neighbourhood of Yokadouma in the eastern Cameroon and also in the Campo-Ma an forest in the southern Cameroon. The study conducted at Yokadouma resulted in a paper addressing forest degradation after selective logging and its implications for REDD and carbon pools and flux estimations. To address this situation, a post-logging stand development of a semi-deciduous natural forest in Cameroon was modelled for one felling cycle (30 years) after selective logging. To simulate how different management practices influence post-logging forest dynamics, we modelled how changes in the minimum felling diameter (MFD) affect stem density, basal area and the related carbon biomass at the end of the felling cycle. The study conducted in Campo-Ma an resulted in two other projected articles. The first article addressed site-specific allometric equations and also pan-moist tropical equations which can be used at other locations in moist tropical forests where there are no specific allometric equations. We used for this study 91 destructive sample trees to develop mixed-species allometric equations applying different input variables such as diameter, diameter and height, product of diameter and height, and wood density. Our biomass data were added to 372 biomass data collected across different moist tropical forests in Asia and South America to develop new pan moist tropical allometric regressions. Species-specific and mixed-species height diameter regression equations were also developed to estimate heights using 3833 trees. The second projected article used our site-specific allometric equations to estimate aboveground and belowground biomass and carbon pools. The NPP was estimated using the growth rates obtained from tree ring analysis. A carbon biomass map was also developed in this last paper using GIS technology to show the distribution in the different land uses and vegetation types. The main findings were the following: Forest degradation studies: With these MFDs estimated, at 7% logging damage rate, we found that the stem density of harvestable trees reduces from 12.3 (50.4 MgC ha-1) to 6.7 (32.5 MgC ha-1) trees per ha and the number of residual trees increases from 80 (18.9 MgC ha-1) to 85.7 (36.8 MgC ha-1) trees per ha. This corresponds to an avoided damage estimated at 17.9 MgC ha-1. We also found that increasing mortality and damage intensity also increases the damage on carbon biomass estimated after a felling cycle of 30 years to be 8.9 MgC ha-1 at 10% or to be 17.4 MgC ha-1 at 15% logging damage. This study shows that proper determination of MFD of logged species taking into consideration their capacity of reconstitution at the end of the felling cycle associated with Reduced Impact Logging (RIL) can avoid up to 35 MgC ha-1. These estimations could be achieved if there is a combination of Policy and Measures allowing monitoring of forest development after logging. Allomeric equations Using only tree diameter as input variable, the mixed-species regression equation estimates the aboveground biomass of the study site with an average error of ±7.4%. Adding height or wood density did not improve significantly the estimations. Using the three variables together improved the precision with an average error of ±3.4%. For general allometric equations tree height was a good predictor variable. The best pan moist tropical equation was obtained when the three variables were added together followed by the one which includes diameter and height. This study provides height-diameter relationships and wood density of 31 species. The pan moist tropical equation developed by Chave et al. (2005), estimates total aboveground biomass across different sites with an average error of ±20.3% followed by equations developed in the present study with an average error of ±29.5%. Biomass, carbon, NPP The carbon biomass of Campo-Ma an forest was on average 264 Mg ha 1. This estimate includes aboveground carbon, root carbon and soil organic carbon down to 30 cm depth. This value varied from 231 Mg ha 1 of carbon in Agro-Forests to 283 Mg ha 1 of carbon in Managed Forests and to 278 Mg ha 1 of carbon in National Park. The carbon NPP varied from 2542 kg ha 1 year 1 in Agro-Forests to 2787 kg ha 1 year 1 in Managed Forests and to 2849 kg ha 1 year 1 in National Park. Our NPP values do not include fine litterfall, carbon losses to consumers and emission of volatile organic compounds. We believe that our study provides not only appropriate estimate of biomass, carbon pools and NPP, but also an appropriate methodology to estimate these components and the related uncertainty.