Summary of the study

7.1.1 Summary of research objective

Forestry is of paramount importance to the state of Baden‐Württemberg, as it supplies wood resources for material and energetic use, and plays a central role in energy transition, climate protection, etc. On the other hand, Baden‐Württemberg has been and will might hit by extreme winter storms that significantly damage the forest resources and wildlife habitat, as well as roads and infrastructure. Such storms may occur with greater intensity and more frequently than before, which might cause increased associated costs.

The identification of the vulnerability of forest resources to extreme storms and the assessment of the related economic impact are very complex. Both require highly detailed sets of multi‐sectoral data, a robust modelling approach, as well as consideration of the spatial and temporal aspects, dynamics and interactions of different factors associated with forestry, markets and management decisions. To address these challenges, two models are developed in this research (Figure 1.14). The first model ‘Weight of Evidence (WofE)’ is based on a combined GIS and statistical analyses to identify the posterior probability maps of vulnerable forest areas in the state of Baden‐Württemberg in Germany. The outcome of the WofE model is used as an input into a system dynamics model ‐ which is based on a dynamic feedback structure and economic theories ‐ to evaluate the economic impacts due to a particular event, considering different forest management and salvage operation decision options. The model is able to demonstrate the changes in impacts over time across all the districts, as the model components constantly evolve due to previous feedback actions and conditions. A decision support tool is also developed to simulate the impact of alternative management strategies.

7.1.2 Summary of vulnerability analysis

In analysing the vulnerability, forest resources and forest management practices with reference to the state of Baden‐Württemberg are primarily explained in Chapter 2. In this regard, a statistical overview of the forest resources, use and flow

Summary of the study

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of wood resources, forest management before and after extreme storms, as well as various statistical data and assumptions are described.

Later, the wind effects on trees and a comprehensive literature review on the assessment of storm damage, factors of windthrow and related windthrow modelling approaches in different geographic extents and scales are illustrated in Chapter 3.

The empirical WofE model is found to be a suitable approach to analyse the vulnerability of forest resources in Baden‐Württemberg. Different steps associated with this approach are systematically described; multiple model outcomes are evaluated and validated in order to justify the acceptance of the posterior probability maps of the vulnerable forest areas in Baden‐Württemberg. In this regard, 11 different models with varying combinations of predictor variables (evidence themes) are tested to understand the most important variables.

The most significant model (M8) uses 3,221 known windthrow affected areas as training points in conjunction with four evidence themes, i.e., soil type, forest type, topographic exposure in direction of west and gust wind speed greater than 35 m/s to produce the posterior probability maps of windthrow vulnerability ‐ at a raster grid with cells in a one ha unit area ‐ in the state of Baden‐Württemberg. Posterior probabilities are calculated for approximately 14 million ha of forests. A classification reveals that majority of the forests (62%) are within the lowest damage class. The moderate damage probability class covers 20%, and the highest damage probability class covers 18% of the area (Figure 3.7). The probability values are highest in the west, where topographic exposure values are at a maximum, soil is acidic and forests are coniferous. The districts of Calw, Freudenstadt. Breisgau‐ Hochschwarzwald, Ortenaukreis, Schwarzwald‐Baar‐Kreis are found to be the most vulnerable districts in Baden‐Württemberg. The outcome of the WofE model is used to investigate windthrow probability and is meant to provide scientists and policy makers with a state‐wide perspective of expected damage patterns of different magnitudes, considering the present conditions. Moreover, with the delineation of areas with different vulnerabilities, economic impacts can be analysed and evaluated considering typical post storm forest management and salvage operation practices.

7.1.3 Summary of economic impact assessment

In assessing economic impacts, the theoretical framework needed to assess the impacts of extreme winter storms on forest resources is at first thoroughly

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discussed in Chapter 4. The different conditions after winter storms ‐ such as economics of salvage decisions, market behaviour and their characteristics ‐ are explained. The system dynamics model proves to be a suitable approach to assess the impacts. Its components and application in the field of economic and spatial modelling, as well as its limitations and advantages are described.

In Chapter 5, the combined spatial and system dynamic based economic model is formulated. Five submodels (Figure 5.1) are developed to assess the values related to salvage, standing timber and forest clearing areas. A model boundary chart, a subsystem diagram and causal loop diagrams are prepared to explain the scope and dependencies of different parameters and the feedback structures of the submodels. Finally, stock and flow diagrams and related input data are explained to illustrate the reference simulation runs in the districts of Baden‐Württemberg.

The reference simulation runs illustrate the main characteristics of the model behaviour, aiming to promote understanding of the dynamic properties of the multidimensional and interdisciplinary aspects of the model. Since different districts accommodate varying forest resources, they are impacted differently by the stochastic storm. The model is also validated with a set of structural and behavioural tests, as suggested by the system dynamics literature and best practices.

The salvage price submodel dynamically determines the salvage price in the state of Baden‐Württemberg in each simulation run, considering the initial reference salvage price, price adjustment time, reference supply, demand, and their elasticities. During the first three years, prices decline, e.g., from 55 to 21 Euro/m³ but then grow again to 32 Euro/m³ in the fifth year. The forest clearing area and standing timber value submodels are run in all districts in Baden‐Württemberg over 20 years. The pre‐storm timber value submodel illustrates the pre‐storm conditions in all these districts, assuming that another extreme storm would not occur. The outcome of the reference simulation runs of different submodels can be used to understand how individual districts might become economically vulnerable or adversely, gain from the effects of an extreme storm.

In Chapter 6, two policy based scenarios are formulated to identify the impacts of alternative forest management and salvage operation strategies. The immediate salvage operation proves profitable, compared to the reference scenarios and delayed salvage operation. For example, in the district of Schwarzwald‐Baar‐Kreis, the net present value of the discounted salvage is higher in the immediate salvage operation policy (226 million Euros), than in the reference scenario (187 million Euros), and in the delayed salvage operation policy (77 million Euros). However, the

Limitation and open research questions 154 delayed salvage operation policy offers environmental and ecological benefits which are difficult to quantify in terms of monetary values. Finally, four sensitivity analyses are performed to identify the impact of some of the most important parameters on model outcome. The price elasticity of demand proved critical to the final salvage price, as a small variation of elasticity leads to a larger change in final salvage price. For example, an increase of demand elasticity from ‐0.5 to +0.5, reduces the salvage price by 67% in the fourth year, and a decrease of elasticity to ‐1 increases the price by 20%. The discount rate also proves to be highly critical in assessing values related to forest clearing area or standing timber, as it runs over 20 years. It is less important in assessing the salvage price which runs for 5 years. By studying the possible future impacts of an extreme winter storm, forest managers and private forest owners are able to prepare marketing strategies in order to control the sale of salvage timber, prevent the depreciation of its value, reduce unintended economic loss or plan sustainable forest management. Assessing the net value (considering the positive and negative cash flows) is critical, since the total cost related to forest clearing areas, salvage operation as well as the value of the wood, is tied up for a prolonged period of time, potentially leading to a heavy economic loss in some districts.

Proposed system dynamics approach ‐ with its scalability in terms of time and space ‐ provides an important basis to evaluate the impacts in forestry. It can be applied to both operational challenges and policy analysis, as well as the exploration of possible future scenarios.