ALBERT

Description: The parameter uncertainty of process-based models has received little attention in climate change impact studies. This paper aims to integrate parameter uncertainty into simulations of climate change impacts on forest net primary productivity (NPP). We used either prior (uncalibrated) or posterior (calibrated using Bayesian calibration) parameter variations to express parameter uncertainty, and we assessed the effect of parameter uncertainty on projections of the process-based model 4C in Scots pine (Pinus sylvestris) stands under climate change. We compared the uncertainty induced by differences between climate models with the uncertainty induced by parameter variability and climate models together. The results show that the uncertainty of simulated changes in NPP induced by climate model and parameter uncertainty is substantially higher than the uncertainty of NPP changes induced by climate model uncertainty alone. That said, the direction of NPP change is mostly consistent between the simulations using the standard parameter setting of 4C and the majority of the simulations including parameter uncertainty. Climate change impact studies that do not consider parameter uncertainty may therefore be appropriate for projecting the direction of change, but not for quantifying the exact degree of change, especially if parameter combinations are selected that are particularly climate sensitive. We conclude that if a key objective in climate change impact research is to quantify uncertainty, parameter uncertainty as a major factor driving the degree of uncertainty of projections should be included.

Description: Key message We present simple models of forest net primary production (NPP) in Germany that show increasing productivity, especially in mountainous areas, under warming unless water becomes a limiting factor. They can be used for spatially explicit, rapid climate impact assessment. Context Climate impact studies largely rely on process-based forest models generally requiring detailed input data which are not everywhere available. Aims This study aims to derive simple models with low data requirements which allow calculation of NPP and analysis of climate impacts using many climate scenarios at a large amount of sites. Methods We fitted regression functions to the output of simulation experiments conducted with the process-based forest model 4C at 2342 climate stations in Germany for four main tree species on four different soil types and two time periods, 1951–2006 and 2031–2060. Results The regression functions showed a reasonable fit to measured NPP datasets. Temperature increase of up to 3 K leads to positive effects on NPP. In water-limited regions, this positive effect is dependent on the length of drought periods. The highest NPP increase occurs in mountainous regions. Conclusion Rapid analyses, using reduced models as presented here, can complement more detailed analyses with process-based models. Especially for dry sites, we recommend further study of climate impacts with process-based models or detailed measurements.

Description: The objective of this paper is to assess how much carbon (C) is currently stored in a forest district in Thuringia, Germany, and how the carbon stocks will develop up to the year 2099 with a changing climate and under various management regimes (including no management), with different assumptions about carbon dioxide (CO2) fertilization effects. We applied the process-based model 4C and a wood product model to a forest district in Germany and evaluated both models for the period from 2002 to 2010, based on forest inventory data for the stands in the district. Then, we simulated the growth of the stands in the forest district under three different realizations of a climate change scenario, combined with different management regimes. Our simulations show that in 2099, between 630 and 1149 t C ha−1 will be stored in this district. The simulations also showed that climate change affects carbon sequestration. The no management strategy sequestered the highest amount of carbon (8.7 t C ha−1 year−1), which was greater than the management regimes. In the model, the possible fertilization effect of CO2 is an important factor. However, forest management remains the determining factor in this forest district.

Description: European temperate and boreal forests sequester up to 12% of Europe’s annual carbon emissions. Forest carbon density can be manipulated through management to maximize its climate mitigation potential, and fast-growing tree species may contribute the most to Climate Smart Forestry (CSF) compared to slow-growing hardwoods. This type of CSF takes into account not only forest resource potentials in sequestering carbon, but also the economic impact of regional forest products and discounts both variables over time. We used the process-based forest model 4 C to simulate European commercial forests’ growth conditions and coupled it with an optimization algorithm to simulate the implementation of CSF for 18 European countries encompassing 68.3 million ha of forest (42.4% of total EU-28 forest area). We found a European CSF policy that could sequester 7.3–11.1 billion tons of carbon, projected to be worth 103 to 141 billion euros in the 21st century. An efficient CSF policy would allocate carbon sequestration to European countries with a lower wood price, lower labor costs, high harvest costs, or a mixture thereof to increase its economic efficiency. This policy prioritized the allocation of mitigation efforts to northern, eastern and central European countries and favored fast growing conifers Picea abies and Pinus sylvestris to broadleaves Fagus sylvatica and Quercus species.

Description: The hemiparasite European mistletoe (Viscum albumL.) adversely affects growth and reproduction of the host Scots pine (PinussylvestrisL.) and in consequence may lead to tree death. Here, we aimed to estimate mistletoe-induced losses in timber yieldapplying the process-based forest growth model 4C. The parasite was implemented into the eco-physiological forest growthmodel 4C using (literature-derived) established impacts of the parasite on the tree’s water and carbon cycle. The amended modelwas validated simulating a sample forest stand in the Berlin area (Germany) comprising trees with and without mistletoe infection.At the same forest stand, tree core measurements were taken to evaluate simulated and observed growth. A subsample of treeswere harvested to quantify biomass compartments of the tree canopy and to derive a growth function of the mistletoe population.The process-based simulations of the forest stand revealed 27% reduction in basal area increment (BAI) during the last 9 years ofheavy infection, which was confirmed by the measurements (29% mean growth reduction). The long-term simulations of the foreststand before and during the parasite infection showed that the amended forest growth model 4C depicts well the BAI growth pat-tern during〉100 years and also quantifies well the mistletoe-induced growth reductions in Scots pine stands.