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    The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
    (Katlenburg-Lindau : Copernics Publications, 2020) Reyer, Christopher P.O.; Silveyra Gonzalez, Ramiro; Dolos, Klara; Hartig, Florian; Hauf, Ylva; Noack, Matthias; Lasch-Born, Petra; Rötzer, Thomas; Pretzsch, Hans; Meesenburg, Henning; Fleck, Stefan; Wagner, Markus; Bolte, Andreas; Sanders, Tanja G.M.; Kolari, Pasi; Mäkelä, Annikki; Vesala, Timo; Mammarella, Ivan; Pumpanen, Jukka; Collalti, Alessio; Trotta, Carlo; Matteucci, Giorgio; D'Andrea, Ettore; Foltýnová, Lenka; Krejza, Jan; Ibrom, Andreas; Pilegaard, Kim; Loustau, Denis; Bonnefond, Jean-Marc; Berbigier, Paul; Picart, Delphine; Lafont, Sébastien; Dietze, Michael; Cameron, David; Vieno, Massimo; Tian, Hanqin; Palacios-Orueta, Alicia; Cicuendez, Victor; Recuero, Laura; Wiese, Klaus; Büchner, Matthias; Lange, Stefan; Volkholz, Jan; Kim, Hyungjun; Horemans, Joanna A.; Bohn, Friedrich; Steinkamp, Jörg; Chikalanov, Alexander; Weedon, Graham P.; Sheffield, Justin; Babst, Flurin; Vega del Valle, Iliusi; Suckow, Felicitas; Martel, Simon; Mahnken, Mats; Gutsch, Martin; Frieler, Katja
    Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.
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    Available and missing data to model impact of climate change on European forests
    (Amsterdam [u.a.] : Elsevier Science, 2019) Ruiz-Benito, Paloma; Vacchiano, Giorgio; Lines, Emily R.; Reyer, Christopher P.O.; Ratcliffe, Sophia; Morin, Xavier; Hartig, Florian; Mäkelä, Annikki; Yousefpour, Rasoul; Chaves, Jimena E.; Palacios-Orueta, Alicia; Benito-Garzón, Marta; Morales-Molino, Cesar; Camarero, J. Julio; Jump, Alistair S.; Kattge, Jens; Lehtonen, Aleksi; Ibrom, Andreas; Owen, Harry J.F.; Zavala, Miguel A.
    Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. © 2019 The Author(s)
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    Forest carbon allocation modelling under climate change
    (Victoria, BC : Heron, 2019) Merganičová, Katarína; Merganič, Ján; Lehtonen, Aleksi; Vacchiano, Giorgio; Ostrogović Sever, Maša Zorana; Augustynczik, Andrey L. D.; Grote, Rüdiger; Kyselová, Ina; Mäkelä, Annikki; Yousefpour, Rasoul; Krejza, Jan; Collalti, Alessio; Reyer, Christopher P. O.
    Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions. © The Author(s) 2019. Published by Oxford University Press.