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

Articolo
Data di Pubblicazione:
2020
Abstract:
Process-based vegetation models are widely used to predict local and global ecosystem dynamicsand climate change impacts. Due to their complexity, they require careful parameterization and evaluation toensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides awide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate cli-mate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multipledata sources at different hierarchical and temporal scales, together with environmental driving data as well asthe 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 standsdistributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heatconduction and soil water are also available. The climate and nitrogen deposition data contain several datasetsfor the historic period and a wide range of future climate change scenarios following the Representative Concen-tration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations thatallow for model runs aimed at disentangling the contribution of climate change to observed forest productivitychanges. 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 contributingdatasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via theProfoundData 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
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Forest Model; Data; Climate Change; Profound; ISIMIP
Elenco autori:
Matteucci, Giorgio; Collalti, Alessio; D'Andrea, Ettore
Autori di Ateneo:
COLLALTI ALESSIO
D'ANDREA ETTORE
MATTEUCCI GIORGIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/403572
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URL

https://essd.copernicus.org/articles/12/1295/2020/
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