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- ItemTackling unresolved questions in forest ecology: The past and future role of simulation models([S.l.] : John Wiley & Sons, Inc., 2021) Maréchaux, Isabelle; Langerwisch, Fanny; Huth, Andreas; Bugmann, Harald; Morin, Xavier; Reyer, Christopher P.O.; Seidl, Rupert; Collalti, Alessio; Dantas de Paula, Mateus; Fischer, Rico; Gutsch, Martin; Lexer, Manfred J.; Lischke, Heike; Rammig, Anja; Rödig, Edna; Sakschewski, Boris; Taubert, Franziska; Thonicke, Kirsten; Vacchiano, Giorgio; Bohn, Friedrich J.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.
- ItemA framework for modeling adaptive forest management and decision making under climate change(Wolfville : The Resilience Alliance, 2017) Yousefpour, Rasoul; Temperli, Christian; Bredahl Jacobsen, Jette; Thorsen, Bo Jellesmark; Meilby, Henrik; Lexer, Manfred J.; Lindner, Marcus; Bugmann, Harald; Borges, Jose G.; Palma, João H.N.; Ray, Duncan; Zimmermann, Niklaus E.; Delzon, Sylvain; Kremer, Antoine; Kramer, Koen; Reyer, Christopher P.O.; Lasch-Born, Petra; Garcia-Gonzalo, Jordi; Hanewinkel, MarcAdapting 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.
- ItemAre forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?(Bristol : IOP Publishing, 2017) Reyer, Christopher P.O.; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G.; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P.; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Hernández, Juan Guerra; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J.; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João HN; Paulo, Joana A.; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E.; Hanewinkel, MarcRecent 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.
- ItemTree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale(Ithaca, NY : ESA, 2019) Bugmann, Harald; Seidl, Rupert; Hartig, Florian; Bohn, Friedrich; Bruna, Josef; Cailleret, Maxime; Francois, Louis; Heinke, Jens; Henrot, Alexandra-Jane; Hickler, Thomas; Huelsmann, Lisa; Huth, Andreas; Jacquemin, Ingrid; Kollas, Chris; Lasch-Born, Petra; Lexer, Manfred J.; Merganic, Jan; Merganicova, Katarna; Mette, Tobias; Miranda, Brian R.; Nadal-Sala, Daniel; Rammer, Werner; Rammig, Anja; Reineking, Bjoern; Roedig, Edna; Sabate, Santi; Steinkamp, Jorg; Suckow, Felicitas; Vacchiano, Giorgio; Wild, Jan; Xu, Chonggang; Reyer, Christopher P.O.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. © 2019 The Authors.