Comparing simulations of three conceptually different forest models with National Forest Inventory data

Although they were originally introduced for different purposes, forest models are often used today for scenario development, which includes forest production as one aspect of forest development. However, studies using an independent data set to compare different simulators are rarely found. In this study a subset of National Forest Inventory data for the whole of Austria was compared to simulations of the biogeochemistry model Biome-BGC, the hybrid gap model PICUS and a climate sensitive version of the growth and yield model PrognAus. The models were used to simulate the development of approximately 700 forest inventory sample plots over a period of 15 years. The study focussed on the models\u27 sensitivity to varying environmental conditions; thus, the comparison was based on the mean current annual volume increment per hectare. All models showed a significant average deviation from the inventory (over- or under-estimation). The estimated year-to-year variation was best reproduced by PICUS. However, the 15 year growth trend was also shown by Biome-BGC and PrognAus. Potential model users interested in relating mean current annual volume increment to climate data will need to weigh accuracy against applicability when choosing among these models

Methyl-Specific Isotope Labeling Strategies for NMR Studies of Membrane Proteins

International audienceMethyl groups are very useful probes of structure, dynamics and interactions in protein NMR spectroscopy. In particular, methyl-directed experiments provide high sensitivity even in very large proteins, such as membrane proteins in a membrane-mimicking environment. In this chapter we discuss the approach for labelling methyl groups in E. coli based protein expression, as exemplified with the mitochondrial carrier GGC