Data and Code from: Sheltered or suppressed? Tree regeneration in unmanaged European forests

Tree regeneration is a key demographic process influencing long-term forest dynamics. It is driven by climate, disturbances, biotic factors, and their interactions. Thus, predictions of tree regeneration are challenging due to complex feedbacks along the wide climatic gradients covered by most tree species. We developed statistical models based on >50,000 recruitment events observed for 24 tree species in an extensive permanent plot network (6,540 plots from 299 unmanaged European temperate, boreal, and subalpine forests) covering a wide climatic gradient. This repository stores csv files with response and explanatory variables and R-Scripts that are needed to run the analysis and create the figures that are presented in the accompanying article titled "Sheltered or suppressed? Tree regeneration in unmanaged European forests" which was published in Journal of Ecology in 2023. Our study shows that competition between trees towards climatic stress decreases systematically but depends on species stress tolerance to climate and shade. These findings explain within- and between-species differences in tree recruitment patterns in European temperate forests. Moreover, our findings imply that projections of forest dynamics along wide climatic gradients and under climate change must accommodate both competition and positive interactions, as they strongly affect rates of community turnover.Data description These files are used as input for the scripts/fit_models.R script. File Description data/processed_data/site_data_unique_plot_id2.csv This file stores the environmental variables for temperature (degree day sum) and water balance. It serves as input for scripts/fit_models.R. data/processed_data/stand_variables_dbh7.csvdata/processed_data/stand_variables_dbh10.csv These files store the leaf area index (LAI_tot) and other variables which are used as predictors in the model and the Number of recruited trees for each inventory period and species in the. The file serves as input for scripts/fit_models.R. The files with the endings dbh7 and dbh10 show the variables for all plots with a size measurment threshold of a diameter at breast height (dbh) of 7 and 10 cm respectivtly. data/raw_data This folder stores files needed as input for creating the figures of the manuscript. data/raw_data/expectations.csv This file contains information which is needed to run the script script/fit_models.R. The variables in this csv represent the expectations of the Stress Gradient Hypotheses illustrated in Figure 1 of the paper. Each row corresponds to a different species strategy under high and low leaf area index. 'stol' is stress tolerance (0 = high stress tolerance, 1 = low stress tolerance); 'comp' indicates the competitive ability of the species which may also be the shade tolerance (0 = low shade tolerance, 1 = high shade tolerance); 'fav' is the relative regeneration intensity under favorable conditions or the position of the line along the y-axis on the left side of the x-axis; 'stress' is the relative regeneration intensity und stressful conditions or the position of the line along the y-axis on the right side of the x-axis; 'lai' is the leaf area index for which the species strategy is specified by the other variables; 'pannel' specifies the pannel of Figure 1 in which the line is drawn. data/raw_data/interpretation/icons This folder contains various icons which have been processed with gimp. These files are not necessary to conduct the statistical analysis but are needed to run the script script/fitmodels.R without error. Scripts These scripts are used to run the statistical analysis. File Description scripts/fit_models.R This file performs the analysis and creates the figures presented in the paper. scripts/data_preparation This folder stores scripts used to derive the variables used in the models. Raw data used by these scripts consists of extremely large files from CHELSA (https://chelsa-climate.org), ISRIC Data Hub (https://data.isric.org), and EU-DEM (https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1). The origin of these files are described in detail in the subfolder scripts/data_preparation/site_level_data. Funding provided by: Eidgenössische Technische Hochschule ZürichCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100003006Award Number: ETH-35 18-1The files with the endings dbh7 and dbh10 show the variables for all plots with a size measurement threshold of a diameter at breast height (dbh) of 7 and 10 cm respectively. Environmental Variables data/processed_data/site_data_unique_plot_id2.csv unique_plot_id2: ID of the forest sampling plot. dds: the seasonal degree-day sum (DDS) is the integral under the temperature curve when ignoring temperatures be-low 5.5 °C (Allen 1976; Fischlin et al. 1995). swb: the site water balance (SWB; cf. Speich 2019). The calculation of the SWB is explained in detail in Appendix A1 of the main article. The unit of the SWB is mm and refers to the amount of water which can be storred in the soil. Allen, J. C. (1976). A modified sine wave method for calculating degree days. Environmental Entomology, 5(6), 388–396. https://doi.org/10.1093/ee/5.3.388 Fischlin, A., Bugmann, H., & Gyalistras, D. (1995). Sensitivity of a forest ecosystem model to climate parametrization schemes. Environmental Pollution, 87(3), 267–282. https://doi.org/10.1016/0269-7491(94)P4158-K Speich, M. J. R. (2019). Quantifying and modeling water availability in temperate forests: A review of drought and aridity indices. IForest, 12(1), 1–16. https://doi.org/10.3832/ifor2934-011 Stand Variables data/processed_data/stand_variables_dbh7.csvdata/processed_data/stand_variables_dbh10.csv The files with the endings dbh7 and dbh10 show the variables for all plots with a size measurement threshold of a diameter at breast height (dbh) of 7 and 10 cm respectively. species: tree species name in latin r.trees: number of trees that surpass the measurement threshold of diameter at breast height (dbh) of 7 or 10 cm. plot_area2: plot area in ha. This variable is used as an offset in the models. period_length: number of years between two consecutive forest inventories. This variable is used as an offset in the models. LAI_tot: sum of gFolA over all species. gFolA: species' one sided foliage area of all leafs per ha. These variables are derived as described in Bugmann (1994) year: ID of the forest inventory period. unique_plot_id2: ID of the forest sampling plot. site_id: ID of site within institute institute_id: ID of institute Bugmann, H. (1994). On the ecology of mountainous forests in a changing climate: A simulation study [PhD Thesis]