DOI: 10.5061/dryad.tht76hf97
title: Simulated and observed timings of leaf senescence for <em>Fagus sylvatica</em> (L.) at selected European sites

description: Together with my co-authors, I have formulated a process-oriented model of
 leaf senescence according to the leaf development process, the DP3 model.
 This model clearly stands out from previous models and allows new
 hypotheses to be made, e.g. about ageing or stress-induced senescence. The
 DP3 model was as accurate as the previously published models. A comparison
 with the constant simulation of the average timing of leaf senescence also
 showed that the models are forced to fall back on this average due to the
 noisy leaf senescence data, which complicates model evaluation. All these
 analyses were based on the simulated and observed leaf senescence data,
 which are made available here.
description: # Simulated and observed timings of leaf senescence for *Fagus sylvatica*
 (L.) at selected European sites Dataset DOI:
 [10.5061/dryad.tht76hf97](10.5061/dryad.tht76hf97) ## Description of the
 data and file structure The date of leaf senescence was simulated for
 beech at selected European sites. In particular, the day of year (Doy)
 when 50% and 100% of the leaves have changed color or have fallen
 (referred to as the phenological stages LS50 and LS100, respectively) were
 simulated for the years with corresponding observations between 1950 and
 2022. The simulation were based on the DP3 model (Meier et al. 2025) as
 well as on the previously published models CDD (Dufrêne et al., 2005), DM2
 (Delpierre et al., 2009), and PIA (Zani et al., 2020). All models werte
 driven with climate variables obtained from the E-OBS dataset (Cornes et
 al., 2018), with CO2 concentration data from Cheng et al. (2022) and
 Copernicus Climate Change Service (2018), and with leaf area indices from
 the GIMMS-LAI3g dataset (version 2; Mao and Yan, 2019). For more detailed
 information consult the original publication Meier et al. (2025). **Please
 cite as** Meier, M., Bigler, C., & Chuine, I. (2025). Aging and stress
 explain the earlier start of leaf senescence in trees in warmer years:
 Translating the latest findings on senescence regulation into the DP3
 model (v1.1). Geoscientific Model Development, 18(19), 6963–6985.
 https://doi.org/10.5194/gmd-18-6963-2025 ### Files and variables ####
 File: Data_ModelSimulations_AccToOptimalAlgorithmControls.csv
 **Description:** The simulated Doy of the phenological stages LS50 and
 LS100 paired and the corresponding obseverved Doy at European sites and
 according to the DP3 model and previous models. ##### Variables * Model:
 The process-oriented model that produced the simulated Doy (i.e.,
 'CDD' by Dufrêne et al., 2005; 'DM2' by Delpierre et
 al., 2009; 'DP3' by Meier et al., 2025, and 'PIA' by
 Zani et al., 2020). * nPar: The number of model parameters that were
 calibrated. * Species: The species for which the timing of the
 phenological stages were observed and simulated, i.e., Fagus sylvatica,
 (L.; 'Beech'). * SamplingProcedure: The applied sampling
 procedure, which considered either only the stage LS50 or both the stages
 LS50 and LS100 (sampling procedures 'LS50' and
 'LS50-LS100', respectively; see Meier et al., 2025, for a
 detailed description of these procedures). * Sample: The calibration or
 validation sample ('Cal' and 'Val', respectively). *
 SampleDraw: The draw of the sample. Each pair of calibration and
 validation sample was drawn twice. * CalRun: The calibration run. Each
 model was calibrated five times with each drawn sample. * Algorithm: The
 optimization algorithm used to calibrate the model parameters by minimzing
 the root mean squared error. Here, generalized simulated annealing was
 used ('GenSA'; Xiang et al., 1997, 2017). * MaxIterations: The
 maximum iterations set in the controls of the GenSA algorithm. * MaxCalls:
 The maximum calls set in the controls of the GenSA algorithm. *
 Temperature: The temperature set in the controls of the GenSA algorithm. *
 Site: The identification of the site for which the Doy of the phenological
 stage LS50 or LS100 was simulated and at which it was observed. * Country:
 The country of the site (i.e. 'AUT' = Austria, 'GBR' =
 United Kingdom, 'GER' = Germany, 'SUI' = Switzerland).
 * Latitude: The latitude of the site [°]. * Longitude: The longitude of
 the site [°]. * Elevation: The elevation of the site [meters above sea
 level]. * Year: The year of the respective simulated and observed Doy. *
 PhenoStage: The respective phenological stage the timing was simulated and
 observed (i.e., 'LS50' = 50% of the leaves have changed color or
 have fallen, 'LS100' = 100% of the leaves have changed color or
 have fallen). * ObservedDoy: The day of year at which the respective
 phenological stage was observed. * SimulatedDoy: The day of year at which
 the respective phenological stage was simulated. * PhenoSource: The source
 of the visually observed timings of LS50 and LS100 (i.e., the European and
 Swiss databases 'PEP725' and 'SPN', respectively;
 Swiss phenology network, 2025; Templ et al., 2018). ## Code/software Among
 others, the CSV file may be viewed with Excel
 ([https://www.microsoft.com/](https://www.microsoft.com/)), LibreOffice
 Calc ([https://de.libreoffice.org/](https://de.libreoffice.org/)), and R
 ([https://www.r-project.org/](https://www.r-project.org/)). ## References
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 W., Liu, Z., Zheng, X., Zhou, D., Jiang, S., Zhao, H., and Wang, X.
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