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Klimawandel und Störungsereignisse stellen eine grosse Herausforderung für die Bewirtschaftung von Gebirgswäldern dar. Im Rahmen der naturnahen Waldbewirtschaftung könnte eine Erhöhung der Bewirtschaftungsintensität (INC-Strategie) die Störungsanfälligkeit verringern, jedoch ist wenig zu den Zielkonflikten mit der Biodiversitätsförderung und der Bereitstellung von Ökosystemleistungen auf Ebene des Forstbetriebes bekannt. In dieser Studie wurden die Auswirkungen verschiedener Bewirtschaftungsintensitäten auf die Störungsanfälligkeit gegenüber Windwurf und Borkenkäfer mit einem Entscheidungsunterstützungssystem (Decision Support System, DSS) untersucht. Dies erfolgte im Dischmatal bei Davos (1350 ha, Teil des Forstbetriebes Davos), für das Simulationen der Waldentwicklung über einen Zeitraum den 2010 bis 2100 unter historischem Klima und Klimawandelszenarien (RCP4.5, RCP8.5) durchgeführt wurden. Zudem wurden Indikatoren für die Biodiversität sowie für Ökosystemleistungen einbezogen. Die Ergebnisse der Fallstudie zeigten, dass die INC-Strategie die Störungsanfälligkeit gegenüber Windwurf und Borkenkäfer verringerte. Der Effekt auf die Borkenkäferanfälligkeit war jedoch relativ gering verglichen mit dem verstärkenden Effekt des Klimawandels unter dem RCP8.5-Szenario. Die INC-Strategie führte zu einer Erhöhung der Erholungsfunktion und der Holzproduktion und zu Zielkonflikten mit der Kohlenstoffspeicherung und der Schutzwirkung. Ausserdem zeigte sich ein positiver Zusammenhang zwischen der Verbesserung der Biodiversitätsindikatoren und dem Rückgang der Störungsanfälligkeit. Unsere Ergebnisse weisen auf eine starke Zunahme der Störungsanfälligkeit unter einem RCP8.5-Klimawandelszenario hin, welche die forstliche Planung vor grosse Herausforderungen stellt. Entscheidungsunterstützungssysteme können helfen, in solch komplexen Planungssituationen die Anpassung an den Klimawandel und die Störungsanfälligkeit mit der Biodiversitätsförderung und der Bereitstellung von Ökosystemleistungen in Einklang zu bringen.

Der Klimawandel verändert die Wuchsbedingungen der Waldbäume, weshalb langfristig markante Verschiebungen in der Baumartenzusammensetzung des Schweizer Waldes zu erwarten sind. Die TreeApp ist ein Werkzeug für die Forstpraxis zur Ermittlung von Baumarten, die für das zukünftige Klima wahrscheinlich geeignet sind. In dieser Arbeit vergleichen wir Empfehlungen der TreeApp mit der im 4. Landesforstinventar (LFI4) beobachteten Artenzusammensetzung der Bäume (≥12 cm Brusthöhendurchmesser [BHD]) und der Verjüngung (

Climate change severely affects mountain forests and their ecosystem services, e.g., by altering disturbance regimes. Increasing timber harvest (INC) via a close-to-nature forestry may offer a mitigation strategy to reduce disturbance predisposition. However, little is known about the efficiency of this strategy at the scale of forest enterprises and potential trade-offs with biodiversity and ecosystem services (BES). We applied a decision support system which accounts for disturbance predisposition and BES indicators to evaluate the effect of different harvest intensities and climate change scenarios on windthrow and bark beetle predisposition in a mountain forest enterprise in Switzerland. Simulations were carried out from 2010 to 2100 under historic climate and climate change scenarios (RCP4.5, RCP8.5). In terms of BES, biodiversity (structural and tree species diversity, deadwood amount) as well as timber production, recreation (visual attractiveness), carbon sequestration, and protection against gravitational hazards (rockfall, avalanche and landslides) were assessed. The INC strategy reduced disturbance predisposition to windthrow and bark beetles. However, the mitigation potential for bark beetle disturbance was relatively small (− 2.4%) compared to the opposite effect of climate change (+ 14% for RCP8.5). Besides, the INC strategy increased the share of broadleaved species and resulted in a synergy with recreation and timber production, and a trade-off with carbon sequestration and protection function. Our approach emphasized the disproportionally higher disturbance predisposition under the RCP8.5 climate change scenario, which may threaten currently unaffected mountain forests. Decision support systems accounting for climate change, disturbance predisposition, and BES can help coping with such complex planning situations.

Damit der Wald Ökosystemleistungen erbringen kann, sind waldbauliche Lenkungsmassnahmen erforderlich. Für die effiziente Durchführung dieser Lenkungsmassnahmen ist eine gute Erschliessung mit Waldstrassen nötig. In diesem Artikel werden drei neue Produkte des Schweizerischen Landesforstinventars (LFI) vorgestellt, die dazu beitragen, die Holzernte effizienter auszugestalten und die Walderschliessung zu optimieren. Beim ersten Produkt handelt es sich um ein Modell zur Herleitung des wirtschaftlich günstigsten Holzernteverfahrens auf jeder LFI-Probefläche. Dazu wurden räumliche Daten zur Topografie und zum Waldstrassennetz, Bestandesdaten und Informationen zu den auf den LFI-Probeflächen eingesetzten Holzernteverfahren sowie expertenbasierte Entscheidungsbäume verwendet. Die Resultate zeigen, dass unter Anwendung des wirtschaftlich besten Verfahrens allgemein höher mechanisierte Verfahren eingesetzt würden und somit Kosten eingespart werden könnten. Das zweite Produkt beinhaltet eine einheitliche und flächendeckende Beurteilung der Erschliessungsgüte. Dabei wurden unter anderem die Topografie, die Bodeneigenschaften, das Waldstrassennetz und die Hindernisse für die Holzernte berücksichtigt. Die Beurteilung ergab, dass sich die Erschliessung auf rund der Hälfte der Schweizer Waldfläche gut für eine effiziente Waldbewirtschaftung eignet, auf je einem Viertel aber nur bedingt oder gar nicht. Für das dritte Produkt wurde unter Berücksichtigung von Strassen- und Rückekosten die optimale Strassendichte ermittelt. Im Vergleich mit der aktuellen Strassendichte kann nun für grössere Gebiete ein Überblick über die ökonomische Effizienz von Walderschliessungen gewonnen werden. Die drei Produkte schaffen Grundlagen für eine detaillierte und flächendeckende Beurteilung der Erschliessungssituation und der Holzerntesysteme im Schweizer Wald und kamen auch schon in der kantonalen Waldplanung von Bern und Graubünden zur Anwendung.

Der Schweizer Wald erbringt verschiedene Leistungen: Insbesondere dient er der Holzproduktion und dem Schutz gegen Naturgefahren, speichert Kohlenstoff und beherbergt eine vielfältige Tier- und Pflanzenwelt. Die gleichzeitige Erbringung dieser Waldleistungen kann jedoch zu Zielkonflikten führen. Zusätzlich beeinflussen Störungsereignisse wie Windwurf und Borkenkäferbefall die nachhaltige und langfristige Bereitstellung der Waldleistungen. Hier stellen wir eine Arbeit vor, die mithilfe von Simulationen des Modells MASSIMO Waldleistungen und Störungsanfälligkeit anhand von Indikatoren in die Zukunft projiziert und potenzielle Zielkonflikte und Synergien mittels einer Multikriterienanalyse bewertet. Dazu wurde die Waldentwicklung ausgehend von Daten des Landesforstinventars (LFI) unter vier Bewirtschaftungsszenarien für die Jahre 2016 bis 2106 unter konstantem Klima simuliert. Über alle Waldleistungen und die ganze Schweiz gesehen schnitt das Business-as-usual- Szenario am besten ab. Jedoch wurden dabei die möglichen Holznutzungspotenziale nicht ausgeschöpft, und es bestanden Zielkonflikte zwischen Biodiversitätsförderung und Kohlenstoffspeicherung. Am meisten Kohlenstoff konnte mit einem Szenario gespeichert werden, unter dem Nadelbäume gefördert und viel Holz geerntet wurde. Dies, weil so viel Kohlenstoff in Holzprodukten gebunden und erdölbasierte Materialien ersetzt werden konnten. Allerdings führte der höhere Nadelholzanteil (vor allem Fichten) zu einer höheren Störungsanfälligkeit gegenüber dem Borkenkäfer. Generell sank die Anfälligkeit gegenüber Sturm und Borkenkäfer bei Szenarien mit verstärkter Holznutzung. Dies führte jedoch aufgrund von weniger Tot- und Altholz zu einem Zielkonflikt mit der Biodiversitätsförderung. Die Störungsanfälligkeit war in LFI-Probeflächen mit hoher Schutzwirkung gegenüber Lawinen und Steinschlag leicht erhöht. Der gewählte Ansatz brachte neue Erkenntnisse zu den Wechselwirkungen zwischen Waldleistungen und Störungsanfälligkeit und bietet Grundlagen für die Entscheidungsunterstützung in der Waldplanung und der Waldpolitik auf regionaler und nationaler Ebene.

Increasing disturbances may significantly impact the long-term protective effect of forests against natural hazards. Quantifying the temporal evolution of the protection service of forests after disturbances is thus crucial for finding optimal management strategies. In this study, we quantified the long-term protective effect of spruce, beech and fir forests against rockfall after severe disturbances based on a straightforward modeling approach. We therefore modelled stand growth of the three tree species based on data of the Swiss National Forest Inventory (NFI) and parameterized the potential rockfall energy dissipation capacity of these stands as a function of their age. We then quantified the evolution of their protective effect for varying rockfall dispositions. The recovery of the protective effect mainly depends on the increase in basal area of a stand, the block volume and the forested slope length. While maximum protection against small blocks is guaranteed after only 10 to 50 yr, 50-150 yr are necessary to regain the maximum possible protective effect against blocks $\ge 1$ m\textsuperscript{3}. The here presented approach can serve practitioners to forecast the recovery of the protection provided by forest stands. As a next step, the proposed model should be adapted to future climate conditions.

Climate-Smart Forestry (CSF) is a developing concept to help policymakers and practitioners develop focused forestry governance and management to adapt to and mitigate climate change. Within the EU COST Action CA15226, CLIMO (Climate-Smart Forestry in Mountain Regions), a CSF definition was developed considering three main pillars: (1) adaptation to climate change, (2) mitigation of climate change, and (3) the social dimension. Climate mitigation occurs through carbon (C) sequestration by trees, C storage in vegetation and soils, and C substitution by wood. However, present and future climate mitigation depends on the adaptation of trees, woods, and forests to adapt to climate change, which is also driven by societal change.Criteria and Indicators (C & I) can be used to assess the climate smartness of forestry in different conditions, and over time. A suite of C & I that quantify the climate smartness of forestry practices has been developed by experts as guidelines for CSF. This chapter charts the development of this definition, presents initial feedback from forest managers across Europe, and discusses other gaps and uncertainties, as well as potential future perspectives for the further evolution of this concept.

Models to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients.

Borkenkäferdynamik im Klimawandel: die Bedeutung der Landschaftsebene Der Klimawandel wirkt auf die Waldentwicklung direkt über steigende Temperaturen und veränderte Niederschlagsmuster und indirekt über Änderungen im Störungsregime. Wo die Fichte (Picea abies) dominiert, ist der Borkenkäfer ein Schlüsselfaktor in der zukünftigen Waldentwicklung, doch die vielfältigen Interaktionen zwischen Baumbestand, Borkenkäfer und Witterung bzw. Klima sind schwierig zu analysieren. Um diese Einflüsse quantifizieren zu können, wurden Wald-Landschaftsmodelle wie LandClim entwickelt. Typischerweise kombinieren diese Modelle Prozesse der lokalen Waldentwicklung (Wachstum, Mortalität, Verjüngung) mit solchen, die auf der Landschaftsebene ablaufen (Samenausbreitung, Bewirtschaftung, Störungen). Dieser Artikel zeigt anhand von LandClim, wie Wald-Landschaftsmodelle strukturiert sind und wie sie angewendet werden können, um die zukünftige Waldentwicklung auf Landschaftsebene abzuschätzen. Im Fallbeispiel wurde die Dynamik von Störungen durch den Buchdrucker (Ips typographus) im Dischmatal bei Davos (Kanton Graubünden) unter historischem Klima und unter einem Klimawandelszenario mit jeweils zwei Windwurfszenarien untersucht. Die Simulationen zeigten einen markanten Anstieg der käferbedingten Fichtenmortalität im Zuge des Klimawandels und einen verstärkenden Effekt von Windwurf auf Käferschäden, der nur beim Klimawandelszenario, nicht aber unter dem historischen Klima auftritt. Wir diskutieren den breiten Anwendungsbereich von LandClim, der von der klimaadaptiven Bewirtschaftung bis zur Störungs- und Paläoökologie reicht, sowie die Nachteile, die sich aus der generellen Modellstruktur ergeben. LandClim eignet sich am besten, um die relative Bedeutung von Klima-, Störungs- und Bewirtschaftungseffekten zu verstehen, aber weniger, um den Holzvorrat, die Stammzahl oder das Erntepotenzial präzise vorherzusagen.

Climate-adaptive forest management aims to sustain the provision of multiple forest ecosystem services and biodiversity (ESB). However, it remains largely unknown how changes in adaptive silvicultural interventions affect trade-offs and synergies among ESB in the long term. We used a simulation-based sensitivity analysis to evaluate popular adaptive forest management interventions in representative Swiss low- to mid-elevation beech- and spruce-dominated forest stands. We predicted stand development across the twenty-first century using a novel empirical and temperature-sensitive single-tree forest stand simulator in a fully crossed experimental design to analyse the effects of (1) planting mixtures of Douglas-fir, oak and silver fir, (2) thinning intensity, and (3) harvesting intensity on timber production, carbon storage and biodiversity under three climate scenarios. Simulation results were evaluated in terms of multiple ESB provision, trade-offs and synergies, and individual effects of the adaptive interventions. Timber production increased on average by 45% in scenarios that included tree planting. Tree planting led to pronounced synergies among all ESBs towards the end of the twenty-first century. Increasing the thinning and harvesting intensity affected ESB provision negatively. Our simulations indicated a temperature-driven increase in growth in beech- (+ 12.5%) and spruce-dominated stands (+ 3.7%), but could not account for drought effects on forest dynamics. Our study demonstrates the advantages of multi-scenario sensitivity analysis that enables quantifying effect sizes and directions of management impacts. We showed that admixing new tree species is promising to enhance future ESB provision and synergies among them. These results support strategic decision making in forestry., European Journal of Forest Research, 141, ISSN:1612-4677, ISSN:1612-4669

National Forest Inventory (NFI) data are the main source of information on forest resources at country and subcountry levels. This chapter explores the strengths and limitations of NFI-derived indicators to assess forest development with respect to adaptation to and mitigation of climate change, that is, the criteria of Climate-Smart Forestry (CSF). We reflect on harmonizing NFI-based indicators across Europe, use literature to scrutinize available indicators to evaluate CSF, and apply them in 1) Switzerland, where CSF is evaluated for NFI records and simulation model projections with four management scenarios; 2) 43 selected European countries, for which the indicators for Sustainable Forest Management (SFM) are used. The indicators were aggregated to composite indices for adaptation and mitigation and to an overall CSF rating. The Swiss NFI records showed increased CSF ratings in mountainous regions, where growing stocks increased. Simulations under business-as-usual management led to a positive CSF rating, whereas scenarios of increased harvesting decreased either only adaptation or both mitigation and adaptation. European-level results showed increases in CSF ratings for most countries. Negative adaptation ratings were mostly due to forest damages. We discuss the limitations of the indicator approach, consider the broader context of international greenhouse gas reporting, and conclude with policy recommendations.

Centro de Investigación Forestal (CIFOR), The increasing demand for innovative forest management strategies to adapt to and mitigate climate change and benefit forest production, the so-called Climate-Smart Forestry, calls for a tool to monitor and evaluate their implementation and their effects on forest development over time. The pan-European set of criteria and indicators for sustainable forest management is considered one of the most important tools for assessing many aspects of forest management and sustainability. This study offers an analytical approach to selecting a subset of indicators to support the implementation of Climate-Smart Forestry. Based on a literature review and the analytical hierarchical approach, 10 indicators were selected to assess, in particular, mitigation and adaptation. These indicators were used to assess the state of the Climate-Smart Forestry trend in Europe from 1990 to 2015 using data from the reports on the State of Europe’s Forests. Forest damage, tree species composition, and carbon stock were the most important indicators. Though the trend was overall positive with regard to adaptation and mitigation, its evaluation was partly hindered by the lack of data. We advocate for increased efforts to harmonize international reporting and for further integrating the goals of Climate-Smart Forestry into national-and European-level forest policy making., This study generated from the COST (European Cooperation in Science and Technology) Action CLIMO (Climate-Smart Forestry in Mountain Regions — CA15226) was financially supported by the EU Framework Programme for Research and Innovation HORIZON 2020. Most of the work was carried out during the Short Term Scientific Mission that Giovanni Santopuoli undertook at the WSL in Birmensdorf (Switzerland) hosted by Christian Temperli, Alessandra Bottero, Paolo Cherubini, and Marco Ferretti., 10 Pág.

Climate-Smart Forestry (CSF) is an emerging branch of sustainable forest management that aims to manage forests in response to climate change. Specific CSF strategies are viewed as a way forward for developing suitable management responses and enhancing the provision of ecosystem services. However, there is currently a lack of comprehensive and cohesive assessment to implement CSF. This paper describes the step-by-step process that developed a comprehensive and shared definition of CSF, and the process for selecting indicators that assess the “climate-smartness” of forest management. Adaptation, mitigation and social dimensions are the core focus of the CSF definition, which recognises the need to integrate and avoid development of these aspects in isolation. An iterative participatory process was used with a range of experts in forest-related fields from the CLIMO project, this was subsequently supported by a network analysis to identify sustainable forest management indicators important to CSF. The definition developed here, is an important first step in to promote CSF that will aid practice in the forestry sector. It can be used as a template across Europe, tailored to local contexts. Further work communicating CSF to practitioners and policy-makers will create a CSF practice and culture that will help to safeguard future forest economies and communities.

Background Scenario analyses that evaluate management effects on the long-term provision and sustainability of forest ecosystem services and biodiversity (ESB) also need to account for disturbances. The objectives of this study were to reveal potential trade-offs and synergies between ESB provision and disturbance predisposition at the scale of a whole country. Methods The empirical scenario model MASSIMO was used to simulate forest development and management from years 2016 to 2106 on 5086 sample plots of the Swiss National Forest Inventory (NFI). We included a business-as-usual (BAU) scenario and four scenarios of increased timber harvesting. Model output was evaluated with indicators for 1) ESB provision including a) timber production, b) old-growth forest characteristics as biodiversity proxies and c) protection against rockfall and avalanches and 2) for a) storm and b) bark beetle predisposition. Results The predisposition indicators corresponded well (AUC: 0.71–0.86) to storm and insect (mostly bark beetle) damage observations in logistic regression models. Increased timber production was generally accompanied with decreased predisposition (storm: >−11%, beetle: >−37%, depending on region and scenario), except for a scenario that promoted conifers where beetle predisposition increased (e.g. + 61% in the Southern Alps). Decreased disturbance predisposition and decreases in old-growth forest indicators in scenarios of increased timber production revealed a trade-off situation. In contrast, growing stock increased under BAU management along with a reduction in conifer proportions, resulting in a reduction of beetle predisposition that in turn was accompanied by increasing old-growth forest indicators. Disturbance predisposition was elevated in NFI plots with high avalanche and rockfall protection value. Conclusions By evaluating ESB and disturbance predisposition based on single-tree data at a national scale we bridged a gap between detailed, stand-scale assessments and broader inventory-based approaches at the national scale. We discuss the limitations of the indicator framework and advocate for future amendments that include climate-sensitive forest development and disturbance modelling to strengthen decision making in national forest policy making.

Timber use in central Europe is expected to increase in the future, in line with forest policy goals to strengthen local wood supply for CO2-neutral energy production, construction and other uses. Growing stocks in low-elevation forests in Switzerland are currently high as exemplified by the Swiss canton of Aargau, for which an average volume of 346 ± 16 m3 ha−1 was measured in the 3rd Swiss National forest inventory (NFI) in 2004–2006. While this may justify a reduction of growing stocks through increased timber harvesting, we asked whether such a strategy may conflict with the sustainability of timber production and conservation goals. We evaluated a range of operationally relevant forest management scenarios that varied with respect to rotation length, growing stock targets and the promotion of conifers in the regeneration. The scenarios aimed at increased production of softwood, energy wood, the retention of potential habitat trees (PHTs) and the conversion to a continuous cover management system. They were used to drive the inventory-based forest simulator MASSIMO for 100 years starting in 2007 using the NFI sampling plots in Aargau. We analyzed model outputs with respect to projected future growing stock, growth, timber and energy yield and harvesting costs. We found growing stock to drop to 192 m3 ha−1 in 2106 if business-as-usual (BAU as observed between the 2nd and 3rd NFI) timber volumes were set as harvesting targets for the whole simulation period. The promotion of conifers and a reduction of rotation lengths in a softwood scenario yielded 25% more timber over the whole simulation period than BAU. An energy wood scenario that reduced growing stock to 200 m3 ha−1 by 2056 and promoted the natural broadleaved regeneration yielded 9% more timber than BAU before 2056 and 30% less thereafter due to decreasing increments. The softwood scenario resulted in higher energy yield than the energy wood scenario despite the lower energy content of softwood. Retaining PHT resulted in a reduction of timber harvest (0.055 m3 ha−1 yr−1 per habitat tree) and higher harvesting costs. Continuous cover management yielded moderate timber amounts throughout the simulation period, yet sustainably. Considering climate change, we discuss the risks associated with favoring drought- and disturbance-susceptible conifers at low elevations and emphasize that continuous cover management must allow for the regeneration of drought-adapted tree species. In conclusion, our simulations show potential for short-term increases in timber mobilization but also that such increases need to be carefully balanced with future forest productivity and other forest ecosystem services.

The demand for wood as construction material, renewable source for energy and feedstock for chemicals is expected to increase. However, timber increments are currently only partly harvested in many European mountain regions, which may lead to supply shortages for local timber industries, decreases in forest resistance to disturbances and functioning as protection from gravitational hazards. Using an inventory-based forest simulator, we evaluated scenarios to increase wood mobilization in the 7105-km2 Swiss canton of Grisons for the period 2007–2106. Scenarios varied with respect to landscape-scale harvesting amounts and silvicultural strategies (low vs. high stand-scale treatment intensity) and accounted for regulations and incentives for protection forest management. With 50 and 100% increases of harvests, the current average growing stock of 319 m3 ha−1 was simulated to be reduced by 12 and 33%, respectively, until 2106 in protection forests of Northern Grisons, where management is prioritized due to subsidies. Outside protection forests and in Southern Grisons, growing stock was simulated to continually increase, which led to divergent developments in forest structure in- and outside protection forests and in the Northern and Southern Grisons. The effect of silvicultural strategies on simulated forest structure was small compared to the effect of future harvesting levels. We discuss opportunities and threats of decreasing management activities outside protection forests and advocate for incentives to promote natural regeneration also outside protection forests to safeguard long-term forest stability.

Forest development models have been used to predict future harvesting potentials and forest management reference levels under the Kyoto guidelines. This contribution aims at presenting the individual-tree simulator MASSIMO (MAnagement Scenario SImulation Model) and demonstrating its scope of applications with simulations of two possible forest management reference levels (base or business as usual) in an example application. MASSIMO is a suitable tool to predict timber harvesting potentials and forest management reference levels to assess future carbon budgets of Swiss forests. While the current version of MASSIMO accurately accounts for legacy effects and management scenarios, effects of climate and nitrogen deposition on growth, mortality, and regeneration are not yet included. In addition to including climate sensitivity, the software may be further improved by including effects of species mixture on tree growth and assessing ecosystem service provision based on indicators.

Forest development models have been used to predict growth and yield for a long time. Yield tables, for example, have been optimised to predict the yield of pure even-aged stands on the basis of long-term observations from experimental forest plots. However, forests in Switzerland cover a broad ecological gradient and forest structures are diverse, with several even- and uneven-aged stand types that can include various species mixtures. Given such diverse forest ecosystems, we predict harvesting potentials and forest management reference levels using the Swiss National Forest Inventory-based individual-tree growth simulator MASSIMO.

The transition to a climate-neutral economy is expected to increase future timber demands and endanger the multifunctionality of forests. National scenario analyses are needed to determine long-term forest management impacts and support forest policy making in defining guidelines for the sustainable provision of forests’ ecosystem services and biodiversity (ESB). Using national forestry inventory data, the forest management model MASSIMO and a model to estimate harvesting costs, we simulated forest development in Switzerland under five politically relevant timber harvesting scenarios until 2106 (business as usual and four increased timber mobilisation scenarios). Model results were analysed using a utility-based multi-criteria approach regarding timber production, protection against gravitational hazards, carbon sequestration and biodiversity conservation for the whole of Switzerland and for five sub-regions. The development of ESB benefits over time and existing trade-offs were analysed. Apart from the Plateau region, the business-as-usual scenario resulted in the highest overall ESB benefits. However, this scenario did not mobilise possible timber potentials, which is not in line with current forest policies. In the Plateau region, ESB benefited most under a constant growing stock scenario that guaranteed long-term sustainable timber usage. Nevertheless, both scenarios showed strong trade-offs between biodiversity conservation and the service carbon sequestration. The latter was achieved best under a scenario with conifer promotion and increased harvested timber volumes that can be used for long-living timber products and substitution of energy intensive materials and fossil fuels. Even though weighting the ESB according to regional management priorities further increased the trade-off situation, it also increased the overall benefits of harvesting scenarios, except for in mountainous regions. We conclude that no single scenario can maximize all ESB benefits simultaneously. A combination of locally adapted scenarios with targeted priorities can guarantee a higher degree of multifunctionality and long-term timber supply, but at the cost of locally more accentuated trade-offs. Overall, our study provides new insights into ESB interactions, and the presented multi-criteria framework and results provide a valuable basis to support forest policy decision making in Switzerland and beyond.

Past and future forest composition and distribution in temperate mountain ranges is strongly influenced by temperature and snowpack. We used LANDCLIM, a spatially explicit, dynamic vegetation model, to simulate forest dynamics for the last 16,000 years and compared the simulation results to pollen and macrofossil records at five sites on the Olympic Peninsula (Washington, USA). To address the hydrological effects of climate-driven variations in snowpack on simulated forest dynamics, we added a simple snow accumulation-and-melt module to the vegetation model and compared simulations with and without the module. LANDCLIM produced realistic present-day species composition with respect to elevation and precipitation gradients. Over the last 16,000 years, simulations driven by transient climate data from an atmosphere-ocean general circulation model (AOGCM) and by a chironomid-based temperature reconstruction captured Late-glacial to Late Holocene transitions in forest communities. Overall, the reconstruction-driven vegetation simulations matched observed vegetation changes better than the AOGCM-driven simulations. This study also indicates that forest composition is very sensitive to snowpack-mediated changes in soil moisture. Simulations without the snow module showed a strong effect of snowpack on key bioclimatic variables and species composition at higher elevations. A projected upward shift of the snow line and a decrease in snowpack might lead to drastic changes in mountain forests composition and even a shift to dry meadows due to insufficient moisture availability in shallow alpine soils.

The future trajectory of forest ecosystems under climate change is heavily debated. Previous studies on the impacts of climate change on forest ecosystems have focused mainly on direct effects of altered climatic conditions, whereas interactions with disturbance events have been largely neglected. The aim of this study is to explore interactions of drought with fire disturbance and to assess their effects on tree species shifts in the European Central Alps. Tree recruitment after a stand replacing wildfire in the Rhone valley, Switzerland, was measured along an altitudinal temperature moisture gradient. Recruitment was more successful in pioneer species (Betula pendula, Populus tremula and Salix appendiculata) than in pre-fire stand forming (PFSF) species (Larix decidua, Picea abies and Pinus sylvestris). Seedling and sapling density was not related to fire intensity, but it correlated with the distance to the forest edge in PFSF species. The window of opportunity for seedling establishment was short (1–2 years), and moisture deficit was the main limiting factor for tree recruitment at lower altitudes. We suggest that prolonged drought periods, as projected under continued global warming, will further aggravate tree recruitment success after fire disturbance at low altitudes of the Central Alps and may eventually lead to a shift from PFSF species to either more drought-tolerant species or to forest-free vegetation.

Timber mobilization possibilities for the chestnut belt of Ticino Many of the traditionally managed chestnut groves and coppice forests in the canton of Ticino have been abandoned in the second half of the 20th century. The ensuing natural development resulted in homogenized stand structures across the landscape, increasing growing stocks and diminishing provision of ecosystem services (e.g. timber, protection from gravitational hazards, nature conservation and recreation services). We used a forest growth simulator (“Massimo”) to simulate a range of management scenarios and possible consequences. Under the current low intensity management growing stocks and tree mortality continue to increase, which – at a large scale – could further reduce the protection and other services and increase the risk of forest fires. This process could be countered with more intense management practices, yet facing relatively high timber harvesting costs. An optimized forest management in the chestnut belt would require the definition of the dominating forest functions, the designation of priority areas and monetary compensation schemes for the provision of the respective forest ecosystem services.

While bark beetle disturbance is an inherent component of coniferous forest ecosystems throughout the northern hemisphere, associated tree mortality and ensuing changes in forest composition and structure may conflict with timber, wildlife, water and other resource management objectives. Therefore, host tree density reduction has been suggested as a management option to increase forest stand resistance to beetle infestation, protect remaining trees and maintain forest resources. However, little is known about the effectiveness of such treatments to mitigate spruce beetle (Dendroctonus rufipennis) infestation or their influence on the stand structural controls of beetle disturbance in subalpine spruce-fir forests in the Rocky Mountains. We addressed this research gap in a retrospective assessment of the impact of density reduction treatments on stand composition and structure and subsequent (ca. 5–20 years later) spruce beetle infestation in southwestern Colorado. The study area was located at the fringe of an ongoing spruce beetle outbreak and at the time of sampling was affected by endemic to incipient beetle pressure. Stand structural attributes and beetle infestation were measured in treated and untreated control stands at four sites. Classification tree analyses revealed spruce diameter and its interaction with spruce basal area percentage as the most important drivers of tree-level beetle infestation. The number, basal area and proportions of beetle-infested spruce were lower in treated stands at sites where treatments significantly reduced the abundance of large spruce trees and where the abundance of large spruce was relatively high prior to tree removal. However, spruce density reduction did not result in a reduction of infestation rates in the remaining large (>25 cm DBH) spruce during the ongoing beetle outbreak. While confirming previous assessments on the limited effectiveness of density reduction treatments for mitigating stand-level beetle infestation, this study provides further insights on the stand structural controls that mediate forest management effects on beetle disturbance dynamics. We conclude by suggesting that priority should be given to management practices that enhance resilience by increasing spruce advance regeneration in the understory as opposed to treatments aimed at achieving resistance to beetle disturbance.

Biomass and species composition of a forest district in the North-Eastern Carpathian Mountains were simulated until 2100 using the forest landscape model LandClim, driven by climate data from three general circulation models that projected the local climate change under the A1B emission scenario. Four different management scenarios were used: business as usual and three adaptive management scenarios characterized by an intensification of interventions: more intense thinnings and shorter rotations. The total biomass at the end of the simulation differed greatly according to the climate scenario but was comparatively much less influenced by the management scenarios. Forest biomass was projected to increase markedly under the model which forecast the lowest climate change (CCSM3), remained approximately constant in the intermediate climate model (ECHAM5) but decreased severely in the hypothesis of the largest climate changes (HadCM3). Our results showed that developments in species composition differed much more between climate change scenarios than between management scenarios. Under moderate and intermediate climate scenarios, changes in species composition occurred principally in harvested stands, while stands not harvested did not display species replacements. Under extreme climate change (HadCM3) on the other hand, the species change occurred even before harvest. The model projections highlight the inadequacy of some species for the new growing and regeneration conditions that accompany the extreme climate scenario. Harvesting can be seen as a chance to undergo active adaptation with respect to species composition.

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures., published version, peerReviewed

Bark beetles are a key forest disturbance agent worldwide, with their impact shaped by climate, forest susceptibility, and interactions with other disturbances such as windthrow and fire. There is ample evidence of the interactions among these factors at small spatial and temporal scales, but projecting their long-term and landscape-scale impacts remains a challenge. We developed a spatially explicit model of European spruce bark beetle (Ips typographus) dynamics that incorporates beetle phenology and forest susceptibility and integrated it in a climate-sensitive landscape model (LandClim). We first corroborated model outputs at various spatial and temporal scales and then applied the model in three case studies (in the Black Forest, Germany, and Davos, Switzerland) that cover an extended climatic gradient. We used this model and case study framework to examine the mechanisms and feedbacks that are driving short-term and long-term interactions among beetle disturbance, climate change, and windthrow, and h...

Projections of indicators of forest ecosystem goods and services (EGS) based on process-based landscape models are critical for adapting forest management to climate change. However, the scarcity of fine-grained, spatially explicit forest data means that initializing these models is both a challenge and a source of uncertainty. To test how different initialization approaches influence the simulation of forest dynamics and EGS indicators we initialized the forest landscape model LandClim with fine resolution empirical data, coarse empirical data, and simulation-derived data, and evaluated the results at three spatial scales (stand, management area and landscape). Simulations were performed for a spruce (Picea abies) dominated landscape in the Black Forest, Germany, under current climate and a climate change scenario. We found that long-term (>150 years) projections are robust to initialization uncertainty. In contrast, shorter-term projections are sensitive to initialization uncertainty, with sensitivity increasing when EGS are assessed at smaller spatial scales, and when the EGS indicators depend on the spatial distribution of individual species. EGS dynamics are strongly influenced by interactions between the density, species composition, and age structure of initialized forests and simulated forest management. If EGS dynamics are strongly influenced by climate change, such as when climate change induces mortality in drought-sensitive species, some of the initialization uncertainty can be masked. We advocate for initializing landscape models with fine-grained data in applications that focus on spatial management problems in heterogeneous landscapes, and stress that the scale of analysis must be in accordance with the accuracy that is warranted by the initialization data.

Developing adaptive forest management strategies is essential to maintain the provisioning of forest goods and services (FGS) under future climate change. We assessed how climate change and forest management affect forest development and FGS for a diverse case-study landscape in Central Europe. Using a process-based forest model (LandClim) we simulated forest dynamics and FGS under a range of climate change and management scenarios in the Black Forest, Germany, which is shaped by various management practices. We focused on the interdependencies between timber production and forest diversity, the most valued FGS in this region. We found that the conversion to more drought-adapted forest types is required to prevent climate change-induced forest dieback and that this conversion must be the target of any adaptive management, especially in areas where monocultures of drought-sensitive Norway spruce (Picea abies) were promoted in the past. Forest conversion takes up to 120 years, however, with past and future adaptive management being the key drivers of timber and forest diversity provision. The conversion of drought-sensitive conifer monocultures maintains timber production in the short-term and enhances a range of forest diversity indices. Using uneven-aged forest management that targets a drought-adapted, diverse, and resilient species mixture, high species diversity can be combined with timber production in the long term. Yet, the promotion of mature-stand attributes requires management restrictions. Selecting future adaptive management options thus implies the consideration of trade-offs between forest resource use and environmental objectives, but also the exploitation of synergies between FGS that occur during forest conversion. Lastly, the large impact of past management practices on the spatial heterogeneity of forest dynamics underpins the need to assess FGS provisioning at the landscape scale.

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.

The risk of bark beetle outbreaks is widely predicted to increase because of a warming climate that accelerates temperature-driven beetle population growth and drought stress that impairs host tree defenses. However, few if any studies have explicitly evaluated climatically enhanced beetle population dynamics in relation to climate-driven changes in forest composition and structure that may alter forest suitability for beetle infestation. We synthesized current understanding of the interactions among climate, spruce beetles (Dendroctonus rufipennis) and forest dynamics to parameterize and further advance the bark beetle module of a dynamic forest landscape model (LandClim) that also integrates fire and wind disturbance and climate-driven forest succession. We applied the model to a subalpine watershed in northwestern Colorado to examine the mechanisms and feedbacks that may lead to shifts in forest composition and spruce beetle disturbance under three climate change scenarios. Simulation results suggest increased drought- and beetle-induced reduction of large Engelmann spruce (Picea engelmannii) trees while Douglas-fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosa) increased in dominance throughout the study area under all climate change scenarios. This shift in forest composition and structure counterbalances the enhancing effects of accelerated beetle population development and increased drought-induced susceptibility of spruce to beetles. As a result, we projected a long-term decrease in beetle-induced spruce mortality to below historical values under all climate scenarios at low elevations (

Adapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the “no-change,” the “reactive,” the “trend-adaptive,” and the “forward-looking adaptive” decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe. Adapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the “no-change,” the “reactive,” the “trend-adaptive,” and the “forward-looking adaptive” decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe.