ALBERT

Description: The temporal variability of ecosystem respiration (R ECO ) has been reported to have important effects on the temporal variability of net ecosystem exchange, the net amount of carbon exchanged between an ecosystem and the atmosphere. However, our understanding of ecosystem respiration is rather limited compared with photosynthesis or gross primary productivity, particularly in Mediterranean montane ecosystems. In order to investigate how environmental variables and forest structure (tree classes) affect different respiration components and R ECO in a Mediterranean beech forest, we measured soil, stem and leaf CO 2 efflux rates with dynamic chambers and R ECO by the eddy-covariance technique over 1 year (2007–2008). Ecosystem respiration showed marked seasonal variation, with the highest rates in spring and autumn and the lowest in summer. We found that the soil respiration (SR) was mainly controlled by soil water content below a threshold value of 0.2 m 3  m –3 , above which the soil temperature explained temporal variation in SR. Stem CO 2 effluxes were influenced by air temperature and difference between tree classes with higher rates measured in dominant trees than in co-dominant ones. Leaf respiration (LR) varied significantly between the two canopy layers considered. Non-structural carbohydrates were a very good predictor of LR variability. We used these measurements to scale up respiration components to ecosystem respiration for the whole canopy and obtained cumulative amounts of carbon losses over the year. Based on the up-scaled chamber measurements, the relative contributions of soil, stem and leaves to the total annual CO 2 efflux were: 56, 8 and 36%, respectively. These results confirm that SR is the main contributor of ecosystem respiration and provided an insight on the driving factors of respiration in Mediterranean montane beech forests.

Description: 29 April 2020: Release of Version 0.3 This is an updated version of Reyer et al., (2019, V. 0.1.12, http://doi.org/10.5880/PIK.2019.008). All changes and updates are documented in the changelog available via the data download section. Current process-based vegetation models are complex scientific tools that require proper evaluation of the different processes included in the models to prove that the models can be used to integrate our understanding of forest ecosystems and project climate change impacts on forests. The PROFOUND database (PROFOUND DB) described here aims to bring together data from a wide range of data sources to evaluate vegetation models and simulate climate impacts at the forest stand scale. It has been designed to fulfill two objectives: - Allow for a thorough evaluation of complex, process-based vegetation models using multiple data streams covering a range of processes at different temporal scales - Allow for climate impact assessments by providing the latest climate scenario data. Therefore, the PROFOUND DB provides general a site description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level and remote sensing data for 9 forest stands spread throughout Europe. Moreover, for a subset of 5 sites, also time series of carbon fluxes, energy balances and soil water are available. The climate and nitrogen deposition data contains several datasets for the historic period and a wide range of future climate change scenarios following the Representative Emission Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). In addition, 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 Database is available freely but we incite users to respect the data policies of the individual datasets as provided in the metadata of each data file. The database can also be accessed via the PROFOUND R-package, which provides basic functions to explore, plot and extract the data. The data (PROFOUND DB) are provided in two different versions (ProfoundData.sqlite download as ProfoundData.zip, ProfoundData_ASCII.zip) accompanied by a change-log to the previous published version (changelog_Profound-DB_v03.pdf), auxiliary data of reconstructed single tree data at the site Sorø (Soroe_DBH_H_AGE_20200428.zip) and documented by the three explanatory documents: (1) PROFOUNDdatabase.pdf: describes the structure, organisation and content of the PROFOUND DB. (2) PROFOUNDsites.pdf: displays the main data of the PROFOUND DB for each of the 9 forest sites in tables and plots. (3) ProfoundData.pdf: explains how to use the PROFOUND R-Package "ProfoundData" to access the PROFOUND DB and provides example scripts on how to apply it.

Description: 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 vapor 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.

Description: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Description: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.