Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/194351
Title: Accuracy, realism and general applicability of European forest models
Author: Mahnken, Mats
Cailleret, Maxime
Collalti, Alessio
Trotta, Carlo
Biondo, Corrado
D'Andrea, Ettore
Dalmonech, Daniela
Marano, Gina
Mäkelä, Annikki
Minunno, Francesco
Peltoniemi, Mikko
Trotsiuk, Volodymyr
Nadal Sala, Daniel
Sabaté i Jorba, Santi
Vallet, Patrick
Aussenac, Raphaël
Cameron, David
Bohn, Friedrich J.
Grote, Rüdiger
Augustynczik, Andrey L. D.
Yousefpour, Rasoul
Huber, Nica
Bugmann, Harald
Merganič
ová, Katarina
Merganic, Jan
Valent, Peter
Lasch-Born, Petra
Hartig, Florian
Vega Del Valle, Iliusi D.
Volkholz, Jan
Gutsch, Martin
Matteucci, Giorgio
Krejza, Jan
Ibrom, Andreas
Meesenburg, Henning
Rötzer, Thomas
van der Maaten-Theunissen, Marieke
van der Maaten, Ernst
Reyer, Christopher P. O.
Keywords: Ecologia forestal
Models biològics
Europa
Forest ecology
Biological models
Europe
Issue Date: 19-Sep-2022
Publisher: John Wiley & Sons
Abstract: Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.
Note: Versió postprint del document publicat a: https://doi.org/10.1111/gcb.16384
It is part of: Global Change Biology, 2022, num. 28, p. 6921-6943
URI: http://hdl.handle.net/2445/194351
Related resource: https://doi.org/10.1111/gcb.16384
ISSN: 1354-1013
Appears in Collections:Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)

Files in This Item:
File Description SizeFormat 
731329.pdf3.99 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.