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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.

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.

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.

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.

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.