Climate change causes critical transitions and irreversible alterations of mountain forests.

Mountain forests are at particular risk of climate change impacts due to their temperature limitation and high exposure to warming. At the same time, their complex topography may help to buffer the effects of climate change and create climate refugia. Whether climate change can lead to critical transitions of mountain forest ecosystems and whether such transitions are reversible remain incompletely understood. We investigated the resilience of forest composition and size structure to climate change, focusing on a mountain forest landscape in the Eastern Alps. Using the individual-based forest landscape model iLand, we simulated ecosystem responses to a wide range of climatic changes (up to a 6°C increase in mean annual temperature and a 30% reduction in mean annual precipitation), testing for tipping points in vegetation size structure and composition under different topography scenarios. We found that at warming levels above +2°C a threshold was crossed, with the system tipping into an alternative state. The system shifted from a conifer-dominated landscape characterized by large trees to a landscape dominated by smaller, predominantly broadleaved trees. Topographic complexity moderated climate change impacts, smoothing and delaying the transitions between alternative vegetation states. We subsequently reversed the simulated climate forcing to assess the ability of the landscape to recover from climate change impacts. The forest landscape showed hysteresis, particularly in scenarios with lower precipitation. At the same mean annual temperature, equilibrium vegetation size structure and species composition differed between warming and cooling trajectories. Here we show that even moderate warming corresponding to current policy targets could result in critical transitions of forest ecosystems and highlight the importance of topographic complexity as a buffering agent. Furthermore, our results show that overshooting ambitious climate mitigation targets could be dangerous, as ecological impacts can be irreversible at millennial time scales once a tipping point has been crossed.

Simulating forest resilience: A review.

AIM: Simulation models are important tools for quantifying the resilience (i.e., persistence under changed environmental conditions) of forest ecosystems to global change. We synthesized the modelling literature on forest resilience, summarizing common models and applications in resilience research, and scrutinizing the implementation of important resilience mechanisms in these models. Models applied to assess resilience are highly diverse, and our goal was to assess how well they account for important resilience mechanisms identified in experimental and empirical research. LOCATION: Global. TIME PERIOD: 1994 to 2019. MAJOR TAXA STUDIED: Trees. METHODS: We reviewed the forest resilience literature using online databases, selecting 119 simulation modelling studies for further analysis. We identified a set of resilience mechanisms from the general resilience literature and analysed models for their representation of these mechanisms. Analyses were grouped by investigated drivers (resilience to what) and responses (resilience of what), as well as by the type of model being used. RESULTS: Models used to study forest resilience varied widely, from analytical approaches to complex landscape simulators. The most commonly addressed questions were associated with resilience of forest cover to fire. Important resilience mechanisms pertaining to regeneration, soil processes, and disturbance legacies were explicitly simulated in only 34 to 46% of the model applications. MAIN CONCLUSIONS: We found a large gap between processes identified as underpinning forest resilience in the theoretical and empirical literature, and those represented in models used to assess forest resilience. Contemporary forest models developed for other goals may be poorly suited for studying forest resilience during an era of accelerating change. Our results highlight the need for a new wave of model development to enhance understanding of and management for resilient forests.

What drives the future supply of regulating ecosystem services in a mountain forest landscape?

Forest ecosystems provide a wide variety of ecosystem services to society. In harsh mountain environments, the regulating services of forests are of particular importance. Managing mountain forests for regulating services is a cost- and labor intensive endeavor. Yet, also unmanaged forests regulate the environment. In the context of evidence-based decision making it is thus important to scrutinize if current management recommendations improve the supply of regulating ecosystem services over unmanaged development trajectories. A further issue complicating decision making in the context of regulating ecosystem services is their high sensitivity to climate change. Climate-mediated increases in natural disturbances, for instance, could strongly reduce the supply of regulating services from forests in the future. Given the profound environmental changes expected for the coming decades it remains unclear whether forest management will still be able to significantly control the future trajectories of mountain forest development, or whether the management effect will be superseded by a much stronger climate and disturbance effect. Here, our objectives were (i) to quantify the future regulating service supply from a 6456 ha landscape in the Stubai valley in Tyrol, Austria, and (ii) to assess the relative importance of management, climate, and natural disturbances on the future supply of regulating ecosystem services. We focused our analysis on climate regulation, water regulation, and erosion regulation, and used the landscape simulation model iLand to quantify their development under different climate scenarios and management strategies. Our results show that unmanaged forests are efficient in providing regulating ecosystem services. Both climate regulation and erosion regulation were higher in unmanaged systems compared to managed systems, while water regulation was slightly enhanced by management. Overall, direct effects of climate change had a stronger influence on the future supply of regulating services than management and natural disturbances. The ability of management to control ecosystem service supply decreased sharply with the severity of future climate change. This finding highlights that forest management could be severely stymied in the future if climate change continues to proceed at its current rate. An improved quantitative understanding of the drivers of future ecosystem service supply is needed to more effectively combine targeted management efforts and natural ecosystem dynamics towards sustaining the benefits society derives from forests in a rapidly changing world.

Trade-offs between temporal stability and level of forest ecosystem services provisioning under climate change.

The ability of forests to continuously provide ecosystem services (ES) is threatened by rapid changes in climate and disturbance regimes. Consequently, these changes present a considerable challenge for forest managers. Management of forests often focuses on maximizing the level of ES provisioning over extended time frames (i.e., rotation periods of more than 100 yr). However, temporal stability is also crucial for many ES, for example, in the context of a steady provisioning of resources to the industry, or the protection of human infrastructure against natural hazards. How temporal stability and the level of ES provisioning are related is of increasing interest, particularly since changing climate and disturbance regimes amplify temporal variability in forest ecosystems. In this simulation study, we investigated whether forest management can simultaneously achieve high levels and temporal stability of ES provisioning. Specifically, we quantified (1) trade-offs between ES stability and level of ES provisioning, and (2) the effect of tree species diversity on ES stability. Simulating a wide range of future climate scenarios and management strategies, we found a negative relationship between temporal stability and level of ES provisioning for timber production, carbon cycling, and site protection in a landscape in the Austrian Alps. Tree species diversity had a predominantly positive effect on ES stability. We conclude that attempts to maximize the level of ES provisioning may increase its temporal variability, and thus threaten the continuity of ES supply. Consequently, considerations of stability need to be more explicitly included in forest management planning under increasingly variable future conditions.

Harnessing landscape heterogeneity for managing future disturbance risks in forest ecosystems.

In order to prevent irreversible impacts of climate change on the biosphere it is imperative to phase out the use of fossil fuels. Consequently, the provisioning of renewable resources such as timber and biomass from forests is an ecosystem service of increasing importance. However, risk factors such as changing disturbance regimes are challenging the continuous provisioning of ecosystem services, and are thus a key concern in forest management. We here used simulation modeling to study different risk management strategies in the context of timber production under changing climate and disturbance regimes, focusing on a 8127 ha forest landscape in the Northern Front Range of the Alps in Austria. We show that under a continuation of historical management, disturbances from wind and bark beetles increase by +39.5% on average over 200 years in response to future climate change. Promoting mixed forests and climate-adapted tree species as well as increasing management intensity effectively reduced future disturbance risk. Analyzing the spatial patterns of disturbance on the landscape, we found a highly uneven distribution of risk among stands (Gini coefficients up to 0.466), but also a spatially variable effectiveness of silvicultural risk reduction measures. This spatial variability in the contribution to and control of risk can be used to inform disturbance management: Stands which have a high leverage on overall risk and for which risks can effectively be reduced (24.4% of the stands in our simulations) should be a priority for risk mitigation measures. In contrast, management should embrace natural disturbances for their beneficial effects on biodiversity in areas which neither contribute strongly to landscape-scale risk nor respond positively to risk mitigation measures (16.9% of stands). We here illustrate how spatial heterogeneity in forest landscapes can be harnessed to address both positive and negative effects of changing natural disturbance regimes in ecosystem management.

Parameters of 150 temperate and boreal tree species and provenances for an individual-based forest landscape and disturbance model.

Understanding the impacts of changing climate and disturbance regimes on forest ecosystems is greatly aided by the use of process-based models. Such models simulate processes based on first principles of ecology, which requires parameterization. Parameterization is an important step in model development and application, defining the characteristics of trees and their responses to the environment, i.e., their traits. For species-specific models, parameterization is usually done at the level of individual species. Parameterization is indispensable for accurately modeling demographic processes, including growth, mortality, and regeneration of trees, along with their intra- and inter-specific interactions. As it is time-demanding to compile the parameters required to simulate forest ecosystems in complex models, simulations are often restricted to the most common tree species, genera, or plant-functional types. Yet, as tree species composition might change in the future, it is important to account for a broad range of species and their individual responses to drivers of change explicitly in simulations. Thus, species-specific parameterization is a critical task for making accurate projections about future forest trajectories, yet species parameters often remain poorly documented in simulation studies. We compiled and harmonized all existing tree species parameters available for the individual-based forest landscape and disturbance model (iLand). Since its first publication in 2012, iLand has been applied in 50 peer-reviewed publications across three continents throughout the Northern Hemisphere (i.e., Europe, North America, and Asia). The model operates at individual-tree level and simulates ecosystem processes at multiple spatial scales, making it a capable process-based model for studying forest change. However, the extensive number of processes and their interactions as well as the wide range of spatio-temporal scales considered in iLand require intensive parameterization, with tree species characterized by 66 unique parameters in the model. The database presented here includes parameters for 150 temperate and boreal tree species and provenances (i.e., regional variations). Excluding missing values, the database includes a total of 9,249 individual parameter entries. In addition, we provide parameters for the individual susceptibility of tree species to wind disturbance (five parameters) for a subset of 104 tree species and provenances (498 parameter entries). To guide further model parameterization efforts, we provide an estimate of uncertainty for each species based on how thoroughly simulations with the respective parameters were evaluated against independent data. Our dataset aids the future parameterization and application of iLand, and sets a new standard in documenting parameters used in process-based forest simulations. This dataset will support model application in previously unstudied areas and can facilitate the investigation of new tree species being introduced to well-studied systems (e.g., simulating assisted migration in the context of rapid climate change). Given that many process-based models rely on similar underlying processes our harmonized parameter set will be of relevance beyond the iLand community. Our work could catalyze further research into improving the parameterization of process-based forest models, increasing the robustness of projections of climate change impacts and adaptation strategies.

A harmonized database of European forest simulations under climate change.

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.