Tackling unresolved questions in forest ecology: The past and future role of simulation models.

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale.

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

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.

Forest disturbances under climate change.

Forest disturbances are sensitive to climate. However, our understanding of disturbance dynamics in response to climatic changes remains incomplete, particularly regarding large-scale patterns, interaction effects and dampening feedbacks. Here we provide a global synthesis of climate change effects on important abiotic (fire, drought, wind, snow and ice) and biotic (insects and pathogens) disturbance agents. Warmer and drier conditions particularly facilitate fire, drought and insect disturbances, while warmer and wetter conditions increase disturbances from wind and pathogens. Widespread interactions between agents are likely to amplify disturbances, while indirect climate effects such as vegetation changes can dampen long-term disturbance sensitivities to climate. Future changes in disturbance are likely to be most pronounced in coniferous forests and the boreal biome. We conclude that both ecosystems and society should be prepared for an increasingly disturbed future of forests.

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe.

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.

Potential stocks and increments of woody biomass in the European Union under different management and climate scenarios.

BACKGROUND: Forests play an important role in the global carbon flow. They can store carbon and can also provide wood which can substitute other materials. In EU27 the standing biomass is steadily increasing. Increments and harvests seem to have reached a plateau between 2005 and 2010. One reason for reaching this plateau will be the circumstance that the forests are getting older. High ages have the advantage that they typical show high carbon concentration and the disadvantage that the increment rates are decreasing. It should be investigated how biomass stock, harvests and increments will develop under different climate scenarios and two management scenarios where one is forcing to store high biomass amounts in forests and the other tries to have high increment rates and much harvested wood. RESULTS: A management which is maximising standing biomass will raise the stem wood carbon stocks from 30 tC/ha to 50 tC/ha until 2100. A management which is maximising increments will lower the stock to 20 tC/ha until 2100. The estimates for the climate scenarios A1b, B1 and E1 are different but there is much more effect by the management target than by the climate scenario. By maximising increments the harvests are 0.4 tC/ha/year higher than in the management which maximises the standing biomass. The increments until 2040 are close together but around 2100 the increments when maximising standing biomass are approximately 50 % lower than those when maximising increments. Cold regions will benefit from the climate changes in the climate scenarios by showing higher increments. CONCLUSIONS: The results of this study suggest that forest management should maximise increments, not stocks to be more efficient in sense of climate change mitigation. This is true especially for regions which have already high carbon stocks in forests, what is the case in many regions in Europe. During the time span 2010-2100 the forests of EU27 will absorb additional 1750 million tC if they are managed to maximise increments compared if they are managed to maximise standing biomass. Incentives which will increase the standing biomass beyond the increment optimal biomass should therefore be avoided. Mechanisms which will maximise increments and sustainable harvests need to be developed to have substantial amounts of wood which can be used as substitution of non sustainable materials.

Forest management under climatic and social uncertainty: trade-offs between reducing climate change impacts and fostering adaptive capacity.

The unabated continuation of anthropogenic greenhouse gas emissions and the lack of an international consensus on a stringent climate change mitigation policy underscore the importance of adaptation for coping with the all but inevitable changes in the climate system. Adaptation measures in forestry have particularly long lead times. A timely implementation is thus crucial for reducing the considerable climate vulnerability of forest ecosystems. However, since future environmental conditions as well as future societal demands on forests are inherently uncertain, a core requirement for adaptation is robustness to a wide variety of possible futures. Here we explicitly address the roles of climatic and social uncertainty in forest management, and tackle the question of robustness of adaptation measures in the context of multi-objective sustainable forest management (SFM). We used the Austrian Federal Forests (AFF) as a case study, and employed a comprehensive vulnerability assessment framework based on ecosystem modeling, multi-criteria decision analysis, and practitioner participation. We explicitly considered climate uncertainty by means of three climate change scenarios, and accounted for uncertainty in future social demands by means of three societal preference scenarios regarding SFM indicators. We found that the effects of climatic and social uncertainty on the projected performance of management were in the same order of magnitude, underlining the notion that climate change adaptation requires an integrated social-ecological perspective. Furthermore, our analysis of adaptation measures revealed considerable trade-offs between reducing adverse impacts of climate change and facilitating adaptive capacity. This finding implies that prioritization between these two general aims of adaptation is necessary in management planning, which we suggest can draw on uncertainty analysis: Where the variation induced by social-ecological uncertainty renders measures aiming to reduce climate change impacts statistically insignificant (i.e., for approximately one third of the investigated management units of the AFF case study), fostering adaptive capacity is suggested as the preferred pathway for adaptation. We conclude that climate change adaptation needs to balance between anticipating expected future conditions and building the capacity to address unknowns and surprises.

Evaluating the accuracy and generality of a hybrid patch model.

Forest patch models have been used extensively to simulate vegetation development under current and changing environmental conditions. However, their physiological foundation is subject to criticism and recent validation experiments against long-term growth and yield data have shown major deficiencies in reproducing observed growth patterns of mixed-species forests. Here we describe the modified forest patch model PICUS Version 1.3, a model variant that couples the structurally detailed three-dimensional patch model PICUS Version 1.2 and the physiologically based stand-level production module of the 3-PG (Physiological Principles in Predicting Growth) model. The approach attempts to combine the ability of PICUS v1.2 to simulate forest dynamics on time scales relevant to forest succession with a simplified but successful production model based on the concept of radiation-use efficiency. We evaluated the hybrid model in a series of simulation experiments. Results indicated a realistic response to a climate sensitivity experiment: the response to environmental gradients was well captured both in terms of productivity on time scales of a rotation length and of forest succession over several hundreds of years. Testing against independent long- term growth and yield data revealed good correspondence between observed and predicted values of volume production and stand structure. Further model development should include a dynamic soil component to consider effects of nutrient cycling.