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Productive Norway spruce forests in mountainous growing areas are expected to be affected by increasing climate-driven disturbances, which will most likely result in a reduction of their economic performance. This study seeks to compare the potential of currently discussed management options aiming to maintain the economic performance on typical sites of spruce under a changing climate. For this purpose, we used a combined approach of tree mortality simulation and portfolio optimization to assess the management options: (1) including a deciduous species, (2) establishing mixed stands, (3) shortening the rotation periods, (4) forest protection measures focusing on bark beetles and (5) introducing another highly productive species. As a novel feature, we also compared the effect of combined management strategies on the return and risk of stand management. In our simulation and optimization approach, the inclusion of an alternative, highly productive tree species, such as Douglas fir, into the tree species portfolio outcompeted the forest protection measure of intensive bark beetle monitoring with timely sanitation fellings in terms of balancing risks and returns. The adaptation gain of introducing Douglas fir was further enhanced when combined with additional management options such as adapted rotation periods. The resulting synergies were able to overcompensate for the adverse economic effects of climate change. On the contrary, including beech did not only reduce the risks but also the return in a magnitude which was clearly outcompeted by Douglas fir, even with the assumption of high mortality risks for Douglas fir. These results prove the importance of a proactive tree species selection in relation to more reactive forest protection measures for climate change adaptation. They also advise a careful consideration of expected market demands when selecting an additional species for the portfolio.

Productivity in mixed forest stands is often higher than that in pure forest stands. Economic analyses usually exclude this phenomenon. In our study, we assess the consequences of an increased productivity in mixed forests for the economically optimal proportions of tree species in forest stands. The economic model applied centers around the Modern Portfolio Theory with the Value-at-Risk as the objective function. The methodological approach encompasses a structured Monte Carlo simulation to generate distributions of returns for different scenarios. Risks include price fluctuations for raw wood as well as natural hazards. The study's major novelty is that it combines well-researched productivity relations in mixed forests with recent empirical survival models for mixed and pure stands to address site variability across Bavaria. We parametrized the model with simulated growth data for Norway spruce and European beech for various climatic and geological conditions. From the results, we conclude that decision makers can increase the Value-at-Risk of forest portfolios when overyielding occurs, by choosing higher shares of beech. Climatic conditions and the extent of overyielding strongly influence optimal stand composition. Using Value-at-Risk as a risk measure that regards both expected returns and their variation, however, leads to the observation that increased risk aversion rather favors higher shares of spruce in forest stands, despite its higher biophysical risks.

Economic consequences of altered survival probabilities under climate change should be considered for regeneration planning in Southeast Germany. Findings suggest that species compositions of mixed stands obtained from continuous optimization may buffer but not completely mitigate economic consequences. Mixed stands of Norway spruce ( Picea abies L. Karst . ) and European beech ( Fagus sylvatica L.) (considering biophysical interactions between tree species) were found to be more robust, against both perturbations in survival probabilities and economic input variables, compared to block mixtures (excluding biophysical interactions). Climate change is expected to increase natural hazards in European forests. Uncertainty in expected tree mortality and resulting potential economic consequences complicate regeneration decisions. This study aims to analyze the economic consequences of altered survival probabilities for mixing Norway spruce (Picea abies L. Karst.) and European beech (Fagus sylvatica L.) under different climate change scenarios. We investigate whether management strategies such as species selection and type of mixture (mixed stands vs. block mixture) could mitigate adverse financial effects of climate change. The bio-economic modelling approach combines a parametric survival model with modern portfolio theory. We estimate the economically optimal species mix under climate change, accounting for the biophysical and economic effects of tree mixtures. The approach is demonstrated using an example from Southeast Germany. The optimal tree species mixtures under simulated climate change effects could buffer but not completely mitigate undesirable economic consequences. Even under optimally mixed forest stands, the risk-adjusted economic value decreased by 28%. Mixed stands economically outperform block mixtures for all climate scenarios. Our results underline the importance of mixed stands to mitigate the economic consequences of climate change. Mechanistic bio-economic models help to understand consequences of uncertain input variables and to design purposeful adaptation strategies.

Aim of study: (i) To estimate site productivity based on German national forest inventory (NFI) data using above-ground wood biomass increment (ΔB) of the stand and (ii) to develop a model that explains site productivity quantified by ΔB in dependence on climate and soil conditions as well as stand characteristics for Norway spruce (Picea abies (L.) Karst.).Area of study: Germany, which ranges from the North Sea to the Bavarian Alps in the south encompassing lowlands in the north, uplands in central Germany and low mountain ranges mainly in southern Germany.Material and methods: Biomass increment of the stand between the 2nd and 3rd NFI was calculated as measure for site productivity. Generalized additive models were fitted to explain biomass increment in dependence on stand age, stand density and environmental variables.Main results: Great part of the variation in biomass increment was due to differences in stand age and stand density. Mean annual temperature and summer precipitation, temperature seasonality, base saturation, C/N ratio and soil texture explained further variation. External validation of the model using data from experimental plots showed good model performance.Research highlights: The study outlines both the potential as well as the restrictions in using biomass increment as a measure for site productivity and as response variable in statistical site-productivity models: biomass increment of the stand is a comprehensive measure of site potential as it incorporates both height and basal area increment as well as stem number. However, it entails the difficulty of how to deal with the influence of management on stand density.Keywords: Site index; site potential; biomass increment; statistical model; climate.

Due to climate change for many regions an increase in tree mortality is expected. Considering changes in mortality risk is important for management decisions. Therefore, models are needed that predict mortality risk under future climate. We fitted survival models for Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), Silver Fir (Abies alba Mill.), Douglas fir (Pseudotsuga menziesii (Mirbel) Franco), European beech (Fagus sylvatica L.), sessile oak (Quercus petraea (Mattuschka) Liebl.), and pedunculate oak (Quercus robur L.) based on the German crown condition survey as well as pan-European crown condition data from Level I and Level II plots, thus encompassing large environmental gradients. We used parametric accelerated failure time models assuming Weibull- or log-normal distribution of survival times. The models allow to estimate survival probability in dependence on age, climate and species mixture. For all species, a decrease in survival probability with increasing temperatures was found. Decreasing precipitation increased mortality risk for Norway spruce, Scots pine and Douglas fir. In addition, for Norway spruce and Douglas fir a positive effect of species admixture on survival was found. In summary, we could fit parsimonious parametric survival models explaining differences in survival times by 30-year climate averages that we interpret as predisposing factors that increase a tree’s vulnerability. However, uncertainty in estimations remains high due to limitations of the sampling design and the methodology.

International audience; AbstractKey messageStatic site indices determined from stands’ top height are derived from different forest inventory sources with height and age information and thus enable comparisons and modeling of a species’ productivity encompassing large environmental gradients.ContextEstimating forest site productivity under changing climate requires models that cover a wide range of site conditions. To exploit different inventory sources, we need harmonized measures and procedures for the productive potential. Static site indices (SI) appear to be a good choice.AimsWe propose a method to derive static site indices for different inventory designs and apply it to six tree species of the German and French National Forest Inventory (NFI). For Norway spruce and European beech, the climate dependency of SI is modeled in order to estimate trends in productivity due to climate change.MethodsHeight and age measures are determined from the top diameters of a species at a given site. The SI is determined for a reference age of 100 years.ResultsThe top height proves as a stable height measure that can be derived harmoniously from German and French NFI. The boundaries of the age-height frame are well described by the Chapman-Richards function. For spruce and beech, generalized additive models of the SI against simple climate variables lead to stable and plausible model behavior.ConclusionThe introduced methodology permits a harmonized quantification of forest site productivity by static site indices. Predicting productivity in dependence on climate illustrates the benefits of combined datasets.