ISIMIP2a Simulation Data from the Regional Forests Sector

Cite as

Mats Mahnken, Alessio Collalti, Daniela Dalmonech, Carlo Trotta, Volodymyr Trotsiuk, Andrey Lessa Derci Augustynczik, Rasoul Yousefpour, Martin Gutsch, David Cameron, Harald Bugmann, Nica Huber, Timothy Thrippleton, Friedrich Bohn, Daniel Nadal-Sala, Santiago Sabaté, Rüdiger Grote, Annikki Mäkelä, Francesco Minunno, Mikko Peltoniemi, Patrick Vallet, Marek Fabrika, Katarína Merganičová, Matthew Forrest, Thomas Hickler, Jörg Steinkamp, Marie Dury, Louis François, Alexandra Henrot, Iliusi Vega del Valle, Jan Volkholz, Christopher P.O. Reyer (2025): ISIMIP2a Simulation Data from the Regional Forests Sector (v1.1). ISIMIP Repository. https://doi.org/10.48364/ISIMIP.169780.1

Metadata

DOI:
https://doi.org/10.48364/ISIMIP.169780.1
Title:
ISIMIP2a Simulation Data from the Regional Forests Sector
Version:
1.1
Creators:
Contact person:

For inquiries concerning this dataset, please contact info@isimip.org.

Abstract:

This dataset contains ISIMIP2a (https://www.isimip.org, Schewe et al. 2019) simulation data from thirteen local forest models: 3D-CMCC FEM (3D-CMCC-FEM LUE, Collalti et al. 2014, 2016), 3D-CMCC-CNR-BGC (3D-CMCC-FEM BGC, Collalti et al. 2019, Collalti et al. 2020), 3PG (Landsberg et al. 2002), 3PGN-BW (Landsberg et al. 1997, Xenakis et al. 2008), 4C (Reyer et al. 2013, Lasch-Born et al. 2020), BASFOR (van Oijen et al. 2014, Cameron et al. 2013), CARAIB, ForClim (Bugmann et al. 2006), FORMIND (Bohn et al. 2014), GOTILWA+ (Nadal-Sala et al. 2017, Keenan et al. 2010, Gracia et al. 2011), Landscape-DNDC (Haas et al. 2012, Grote et al. 2008, 2010, 2011, Holst et al. 2009, Lindauer et al. 2014), LPJ-GUESS, PREBAS (Minunno et al. 2016, Valentine et al. 2005), SALEM (Aussenac et al. 2021) and SIBYLA (Fabrika and Ďurský 2006, Hlásny et al. 2014).

Version 1.1 adds the datasets for CARAIB and LPJ-GUESS.

Methods:

The ISIMIP2a local forest outputs are based on simulations from local forest models according to the ISIMIP2a protocol (https://www.isimip.org/protocol/2a/). A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels.

Publication date:
March 5, 2025
Publisher:
ISIMIP Repository
Contributors:

Here we list the persons and organizations, who are responsible for the collection, the management, and the publication of this dataset.

Rights

The datasets for this DOI are published under different usage rights (please check the license statement for each dataset):
When using ISIMIP data for your research, please appropriately credit the data providers, e.g. either by citing the DOI for the dataset, or by appropriate acknowledgment. We strongly encourage to offer co-authorship to at least a representative of the data providers. Further information can be found in our terms of use.

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References

  • A. Collalti, S. Marconi, A. Ibrom, C. Trotta, A. Anav, E. D'Andrea, G. Matteucci, L. Montagnani, B. Gielen, I. Mammarella, T. Grünwald, A. Knohl, R. Valentini, and M. Santini et al. Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for ten European forest sites. Geoscientific Model Development, 9, 1-26, 2016, https://doi.org/10.5194/gmd-9-1-201
  • Aussenac R, Pérot T, Fortin M, de Coligny F, Monnet J, Vallet P et al. The Salem simulator version 2.0: a tool for predicting the productivity of pure and mixed forest stands and simulating management operations. Open Research Europe, 1, 61, 2021, https://doi.org/10.12688/openreseurope.13671.2
  • Bohn F, Frank K, Huth A et al. Of climate and its resulting tree growth: Simulating the productivity of temperate forests. Ecological Modelling, 278, 9-17, 2014, https://doi.org/10.1016/j.ecolmodel.2014.01.021
  • Bugmann H et al. A Simplified Forest Model to Study Species Composition Along Climate Gradients. Ecology, 77, 2055-2074, 2006, https://doi.org/10.2307/2265700
  • Cameron, D. R., Van Oijen, M., Werner, C., Butterbach-Bahl, K., Grote, R., Haas, E., Heuvelink, G. B. M., Kiese, R., Kros, J., Kuhnert, M., Leip, A., Reinds, G. J., Reuter, H. I., Schelhaas, M. J., De Vries, W., & Yeluripati, J. (2013). Environmental change impacts on the C- and N-cycle of European forests: a model comparison study. Biogeosciences, 10(3), 1751-1773. https://doi.org/10.5194/bg-10-1751-2013
  • Collalti A., Perugini L., Santini M., Chiti T., Nolè A., Matteucci G., Valentini R. et al. A process-based model to simulate growth in forests with complex structure: Evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy. Ecological Modelling, 272, 362-378, 2014, https://doi.org/10.1016/j.ecolmodel.2013.09.016
  • Collalti, A., Thornton, P. E., Cescatti, A., Rita, A., Borghetti, M., Nolè, A., Trotta, C., Ciais, P., & Matteucci, G. (2019). The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change. Ecological Applications, 29(2), e01837. https://doi.org/10.1002/eap.1837
  • Collalti, A., Tjoelker, M. G., Hoch, G., Mäkelä, A., Guidolotti, G., Heskel, M., Petit, G., Ryan, M. G., Battipaglia, G., Matteucci, G., & Prentice, I. C. (2020). Plant respiration: Controlled by photosynthesis or biomass? Global Change Biology, 26(3), 1739-1753. https://doi.org/10.1111/gcb.14857
  • Fabrika, M., & Ďurský, J. (2005). Algorithms and software solution of thinning models for SIBYLA growth simulator [Article]. Journal of Forest Science, 51(10), 431-445. https://doi.org/10.17221/4577-jfs
  • Georgios Xenakis, Duncan Ray, Maurizio Mencuccini, Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model, Ecological Modelling, Volume 219, Issues 1–2, 2008, Pages 1-16, ISSN 0304-3800, https://doi.org/10.1016/j.ecolmodel.2008.07.020.
  • Gracia C, Tello E, Sabaté S, Bellot J et al. GOTILWA: An Integrated Model of Water Dynamics and Forest Growth. Ecological Studies, 163-179, 2011, https://doi.org/10.1007/978-3-642-58618-7_12
  • Grote R, Kiese R, Grünwald T, Ourcival J, Granier A et al. Modelling forest carbon balances considering tree mortality and removal. Agricultural and Forest Meteorology, 151, 179-190, 2010, https://doi.org/10.1016/j.agrformet.2010.10.002
  • Grote R, Korhonen J, Mammarella I et al. Challenges for evaluating process-based models of gas exchange. Forest Systems, 20, 389, 2011, https://doi.org/10.5424/fs/20112003-11084
  • Grote R, Lehmann E, Brümmer C, Brüggemann N, Szarzynski J, Kunstmann H et al. Modelling and observation of biosphere–atmosphere interactions in natural savannah in Burkina Faso, West Africa. Physics and Chemistry of the Earth, Parts A/B/C, 34, 251-260, 2008, https://doi.org/10.1016/j.pce.2008.05.003
  • Haas E, Klatt S, Fröhlich A, Kraft P, Werner C, Kiese R, Grote R, Breuer L, Butterbach-Bahl K et al. LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale. Landscape Ecology, 28, 615-636, 2012, https://doi.org/10.1007/s10980-012-9772-x
  • Hlásny, T., Barcza, Z., Barka, I., Merganičová, K., Sedmák, R., Kern, A., Pajtík, J., Balázs, B., Fabrika, M., & Churkina, G. (2014). Future carbon cycle in mountain spruce forests of Central Europe: Modelling framework and ecological inferences. Forest Ecology and Management, 328, 55-68. https://doi.org/10.1016/j.foreco.2014.04.038
  • Holst J, Grote R, Offermann C, Ferrio J, Gessler A, Mayer H, Rennenberg H et al. Water fluxes within beech stands in complex terrain. International Journal of Biometeorology, 54, 23-36, 2009, https://doi.org/10.1007/s00484-009-0248-x
  • J.J. Landsberg, R.H. Waring, A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning, Forest Ecology and Management, Volume 95, Issue 3, 1997, Pages 209-228, ISSN 0378-1127, https://doi.org/10.1016/S0378-1127(97)00026-1.
  • Keenan T, García R, Friend A, Zaehle S, Gracia C, Sabate S et al. Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO2 and water fluxes through combined in situ measurements and ecosystem modelling. Biogeosciences, 6, 1423-1444, 2010, https://doi.org/10.5194/bg-6-1423-2009
  • Lasch-Born, P., Suckow, F., Reyer, C. P. O., Gutsch, M., Kollas, C., Badeck, F. W., Bugmann, H. K. M., Grote, R., Fürstenau, C., Lindner, M., & Schaber, J. (2020). Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites. Geosci. Model Dev., 13(11), 5311-5343. https://doi.org/10.5194/gmd-13-5311-2020
  • Lindauer M, Schmid H, Grote R, Mauder M, Steinbrecher R, Wolpert B et al. Net ecosystem exchange over a non-cleared wind-throw-disturbed upland spruce forest—Measurements and simulations. Agricultural and Forest Meteorology, 197, 219-234, 2014, https://doi.org/10.1016/j.agrformet.2014.07.005
  • Minunno F, Peltoniemi M, Launiainen S, Aurela M, Mammarella I, Lindroth A, Lohela A, Minkkinen K, Mäkelä A et al. A 2016. Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region. . Ecological Modelling ,341,37-52,2016
  • Nadal-Sala D, Keenan T, Sabaté S, Gracia C et al. Forest Eco-Physiological Models: Water Use and Carbon Sequestration. Managing Forest Ecosystems: The Challenge of Climate Change, 81-102, 2017, https://doi.org/10.1007/978-3-319-28250-3_5
  • Reyer C, Lasch-Born P, Suckow F, Gutsch M, Murawski A, Pilz T et al. Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide. Annals of Forest Science, 71, 211-225, 2013, https://doi.org/10.1007/s13595-013-0306-8
  • Schewe, J., Gosling, S.N., Reyer, C. et al. State-of-the-art global models underestimate impacts from climate extremes. Nat Commun 10, 1005 (2019). https://doi.org/10.1038/s41467-019-08745-6
  • Valentine HT, Mäkelä A. Bridging process-based and empirical approaches to modeling tree growth. Tree Physiol. 2005 Jul;25(7):769-79. https://doi.org/10.1093/treephys/25.7.769
  • van Oijen, M., Balkovi, J., Beer, C., Cameron, D. R., Ciais, P., Cramer, W., Kato, T., Kuhnert, M., Martin, R., Myneni, R., Rammig, A., Rolinski, S., Soussana, J. F., Thonicke, K., Van der Velde, M., & Xu, L. (2014). Impact of droughts on the carbon cycle in European vegetation: a probabilistic risk analysis using six vegetation models. Biogeosciences, 11(22), 6357-6375. https://doi.org/10.5194/bg-11-6357-2014

Additional documentation

This DOI is a new version of

  • Mahnken, Mats; Collalti, Alessio; Dalmonech, Daniela; Trotta, Carlo; Trotsiuk, Volodymyr; Augustynczik, Andrey Lessa Derci; Yousefpour, Rasoul; Gutsch, Martin; Cameron, David; Bugmann, Harald; Huber, Nica; Thrippleton, Timothy; Bohn, Friedrich; Nadal-Sala, Daniel; Sabaté, Santiago; Grote, Rüdiger; Mäkelä, Annikki; Minunno, Francesco; Peltoniemi, Mikko; Vallet, Patrick; Fabrika, Marek; Merganičová, Katarína; Vega del Valle, Iliusi; Volkholz, Jan; Reyer, Christopher P.O. (2022): ISIMIP2a Simulation Data from the Regional Forests Sector. Version 1.0. ISIMIP Repository. (Dataset). https://doi.org/10.48364/ISIMIP.169780.

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