Our landscapes reveal that the lignin characteristics do not only depend on the P-factor, as observed, e.g., for xylan extraction from wood , but also on the reaction temperature at a fixed P-factor. The landscape shows that this dependence is surprisingly complex; for example, at a low P-factor (e.g., P = 500) the highest yield is observed for a low reaction temperature (180 • C), but at a high P-factor (e.g., P = 2000) it occurs for the highest reaction temperature (210 • C). This complex dependence can be explained by competing reactions with different activation energies that consequently contribute differently to the overall process. The (P f , T )dependence of all the structural properties we have modeled can, to some extent, be qualitatively explained by well-known principles from lignin chemistry. However, the surrogate model landscapes provide the quantitative predictions necessary for large-scale applications in lignin valorization. As noted for the carbohydrate content, the surrogate models can also provide information on potential problems in the experimental characterization, such as larger than expected measurement noise.