No abstract

No abstract

This study investigates whether the assumed increase of winter and spring temperatures is depicted by phenological models in correspondingly earlier bud burst (BB) dates. Some studies assume that rising temperatures lead to an earlier BB, but even later BB has been detected. The phenological model PIM (promoter-inhibitor-model) fitted to the extensive phenological database of the German Weather Service was driven by several climate scenarios. This model accounts for the complicated mechanistic interactions between chilling requirements, temperature and photo-period. It predicts BB with a r between 0.41 and 0.62 and a RMSE of around 1 week, depending on species. Parameter sensitivities depict species dependent interactions between growth and chilling requirements as well as photo-period. A mean trend to earlier BB was revealed for the period 2002- 2100, varying between -0.05 and -0.11 days per year, depending on species. These trends are lower than for the period 1951- 2009. Within climate scenario period, trends are decreasing for beech and chestnut, stagnating for birch and increasing for oak. Results suggest that not fulfilled chilling requirements accompanied by an increasing dependency on photo-period potentially limit future BB advancement. The combination of a powerful phenological model, a large scale phenological database and several climate scenarios, offers new insights into the mechanistic comprehension of spring phenology.

Global change scenarios predict an increased risk for declining amounts of soil organic matter (SOM) for Central Germany. Within this region the production of bioenergy is one important strategy to counteract the rising anthropogenic CO 2 -emissions. Both issues have a close connection: SOM is an important basis for soil productivity and requires a steady reproduction flux. Bioenergy production requires productive soils and partly consumes plant biomass C. Therefore, the available amount for SOM reproduction is reduced. This study provides a methodology for the largescale identification of areas with possible conflicts between bioenergy production and SOM reproduction based on (1) the prediction of climate change impact on SOM reproduction and (2) an analysis of the regional distribution of biogas plants. With the C demand index (CDI) and the capacity index (CAP), two indicators were developed which enable the identification of hot spots of high carbon demand for SOM reproduction due to climate change and the usage of bioenergy. As a result of low data requirements, the indicators are widely applicable and transferable to other large-scale studies. The proposed methodology was applied to Central Germany as a pilot region. Results indicate a growing demand (10-40%) of fresh organic C from biomass for SOM production in comparison to the current level. The analysis reveals that the bioenergy C demand is not evenly distributed within the study region. It also shows some regional clustering. Furthermore, the analysis identifies certain hot spots of a high C demand, where a high capacity of biogas production may conflict with rising demands for biomass to mitigate climate change effects on SOM storage. The hot spot areas-identified and selected on a large scale-can subsequently be analyzed in more detail on a local to farm scale by using high-resolution data and models which enable the quantification of soil C dynamics.