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The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
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.
1866-3508
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Reyer, Christopher P.O.
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Silveyra Gonzalez, Ramiro
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Dolos, Klara
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Hartig, Florian
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Noack, Matthias
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Lasch-Born, Petra
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Pretzsch, Hans
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Matteucci, Giorgio
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Cameron, David
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Vieno, Massimo
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Tian, Hanqin
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Palacios-Orueta, Alicia
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Cicuendez, Victor
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Lange, Stefan
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Volkholz, Jan
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Kim, Hyungjun
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Horemans, Joanna A.
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Bohn, Friedrich
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Steinkamp, Jörg
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Chikalanov, Alexander
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Sheffield, Justin
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et al.
Reyer, Christopher P.O.
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Silveyra Gonzalez, Ramiro
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Dolos, Klara
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Hartig, Florian
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Hauf, Ylva
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Noack, Matthias
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Lasch-Born, Petra
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Rötzer, Thomas
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Pretzsch, Hans
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Meesenburg, Henning
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Fleck, Stefan
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Wagner, Markus
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Sanders, Tanja G.M.
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Kolari, Pasi
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Mäkelä, Annikki
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Vesala, Timo
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Mammarella, Ivan
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Collalti, Alessio
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Trotta, Carlo
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Krejza, Jan
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Pilegaard, Kim
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Loustau, Denis
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Berbigier, Paul
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Cameron, David
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Vieno, Massimo
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Tian, Hanqin
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Cicuendez, Victor
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Recuero, Laura
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Wiese, Klaus
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Büchner, Matthias
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Lange, Stefan
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Volkholz, Jan
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Kim, Hyungjun
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Horemans, Joanna A.
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Bohn, Friedrich
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Steinkamp, Jörg
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Chikalanov, Alexander
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Sheffield, Justin
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Reyer, Christopher P.O., Silveyra Gonzalez, Ramiro, Hauf, Ylva and Sheffield, Justin , et al. (2020) The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests. Earth System Science Data, 12 (2), 1295-1320. (doi:10.5194/essd-12-1295-2020).

Record type: Article

Abstract

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.

This record has no associated files available for download.

More information

Accepted/In Press date: 8 May 2020
Published date: 12 June 2020
Additional Information: Funding Information: Ministry of Education, Youth and Sports of CR within the CzeCOS pro gramme, grant number LM2015061 Publisher Copyright:© Author(s) 2020.

Identifiers

Local EPrints ID: 475417
URI: http://eprints.soton.ac.uk/id/eprint/475417
ISSN: 1866-3508
PURE UUID: cb83f988-39dc-4390-b862-db441c5340e7
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

Catalogue record

Date deposited: 17 Mar 2023 17:36
Last modified: 06 Jun 2024 01:54

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Contributors

Author: Christopher P.O. Reyer
Author: Ramiro Silveyra Gonzalez
Author: Klara Dolos
Author: Florian Hartig
Author: Ylva Hauf
Author: Matthias Noack
Author: Petra Lasch-Born
Author: Thomas Rötzer
Author: Hans Pretzsch
Author: Henning Meesenburg
Author: Stefan Fleck
Author: Markus Wagner
Author: Andreas Bolte
Author: Tanja G.M. Sanders
Author: Pasi Kolari
Author: Annikki Mäkelä
Author: Timo Vesala
Author: Ivan Mammarella
Author: Jukka Pumpanen
Author: Alessio Collalti
Author: Alessio Collalti
Author: Carlo Trotta
Author: Giorgio Matteucci
Author: Ettore D'Andrea
Author: Lenka Foltýnová
Author: Jan Krejza
Author: Andreas Ibrom
Author: Kim Pilegaard
Author: Denis Loustau
Author: Jean Marc Bonnefond
Author: Paul Berbigier
Author: Delphine Picart
Author: Sébastien Lafont
Author: Michael Dietze
Author: David Cameron
Author: Massimo Vieno
Author: Hanqin Tian
Author: Alicia Palacios-Orueta
Author: Victor Cicuendez
Author: Laura Recuero
Author: Klaus Wiese
Author: Matthias Büchner
Author: Stefan Lange
Author: Jan Volkholz
Author: Hyungjun Kim
Author: Joanna A. Horemans
Author: Friedrich Bohn
Author: Jörg Steinkamp
Author: Alexander Chikalanov
Corporate Author: et al.

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