A Modeling Analysis of Changing Global Land Use as affected by Changing Demands for Wood Products

The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.

Effects of plant diversity on bioenergy parameters in grassland biomass

Extensive grassland biomass for bioenergy production has long been subject of scientific research. The possibility of combining nature conservation goals with a profitable management while reducing competition with food production has created a strong interest in this topic. However, the botanical composition will play a key role for solid fuel quality of grassland biomass and will have effects on the combustion process by potentially causing corrosion, emission and slagging. On the other hand, botanical composition will affect anaerobic digestibility and thereby the biogas potential. In this thesis aboveground biomass from the Jena-Experiment plots was harvested in 2008 and 2009 and analysed for the most relevant chemical constituents effecting fuel quality and anaerobic digestibility. Regarding combustion, the following parameters were of main focus: higher heating value (HHV), gross energy yield (GE), ash content, ash softening temperature (AST), K, Ca, Mg, N, Cl and S content. For biogas production the following parameters were investigated: substrate specific methane yield (CH4 sub), area specific methane yield (CH4 area), crude fibre (CF), crude protein (CP), crude lipid (CL) and nitrogen-free extract (NfE). Furthermore, an improvement of the fuel quality was investigated through applying the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Through the specific setup of the Jena-Experiment it was possible to outline the changes of these parameters along two diversity gradients: (i) species richness (SR; 1 to 60 species) and (ii) functional group (grasses, legumes, small herbs and tall herbs) presence. This was a novel approach on investigating the bioenergy characteristic of extensive grassland biomass and gave detailed insight in the sward-composition¬ - bioenergy relations such as: (i) the most relevant SR effect was the increase of energy yield for both combustion (annual GE increased by 26% from SR8→16 and by 65% from SR8→60) and anaerobic digestion (annual CH4 area increased by 22% from SR8→16 and by 49% from SR8→60) through a strong interaction of SR with biomass yield; (ii) legumes play a key role for the utilization of grassland biomass for energy production as they increase the energy content of the substrate (HHV and CH4 sub) and the energy yield (GE and CH4 area); (iii) combustion is the conversion technique that will yield the highest energy output but requires an improvement of the solid fuel quality in order to reduce the risk of corrosion, emission and slagging related problems. This was achieved through applying the IFBB-procedure, with reductions in ash (by 23%), N (28%), K (85%), Cl (56%) and S (59%) and equal levels of concentrations along the SR gradient.

Effects of grassland conversion and tillage intensities on soil microbial biomass, residues and community structure

Agricultural intensification has a strong impact on level of soil organic matter (SOM), microbial biomass stocks and microbial community structure in agro-ecosystems. The size of the microbial necromass C pool could be about 40 times that of the living microbial biomass C pool in soils. Due to the specificity, amino sugar analysis gives more important information on the relative contribution of fungal and bacterial residues to C sequestration potential of soils. Meanwhile, the relationship between microbial biomass and microbial necromass in soil and its ecological significance on SOM are not fully understood and likely to be very complex in grassland soils. This thesis focuses on the effects of tillage, grassland conversion intensities and fertilisation on microbial biomass, residues and community structure. The combined analyses of microbial biomass and residue formation of both fungi and bacteria provided a unique opportunity to study the effect of tillage, grassland conversion and fertilisation on soil microbial dynamics. In top soil at 0-30 cm layer, a reduction in tillage intensity by the GRT and NT treatments increased the accumulation of saprotrophic fungi in comparison with the MBT treatment. In contrast, the GRT and NT treatments promoted AMF at the expense of saprotrophic fungi in the bottom soil layer at 30-40 cm depth. The negative relationship between the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio points to the importance of the relationship between saprotrophic fungi and biotrophic AMF for tillage-induced changes in microbial turnover of SOC. One-season cultivation of winter wheat with two tillage events led to a significant loss in SOC and microbial biomass C stocks at 0-40 cm depth in comparison with the permanent grassland, even 5 years after the tillage event. However, the tillage induced loss in microbial biomass C was roughly 40% less in the long-term than in the short-term of the current experiment, indicating a recovery process during grassland restoration. In general, mould board tillage and grassland conversion to maize monoculture promoted saprotrophic fungi at the expense of biotrophic AMF and bacteria compared to undisturbed grassland soils. Slurry application promoted bacterial residues as indicated by the decreases in both, the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio. In addition, the lost microbial functional diversity due to tillage and maize monoculture was restored by slurry application both in arable and grassland soils. I conclude that the microbial biomass C/S ratio can be used as an additional indicator for a shift in microbial community. The strong relationships between microbial biomass and necromass indices points to the importance of saprotrophic fungi and biotrophic AMF for agricultural management induced effects on microbial turnover and ecosystem C storage. Quantitative information on exact biomass estimates of these two important fungal groups in soil is inevitably necessary to understand their different roles in SOM dynamics.