Managing the future: Post-disturbance forest recovery across management types in Central Europe - Data and analysis scripts

This repository holds data and code for the paper: Krüger, K., Fischer, F.J., Stritih, A., Klemmt. H.J., Seidl, R. (2026). Managing the future: Post-disturbance forest recovery across management types in Central Europe. Forest Ecology and Management (https://doi.org/10.1016/j.foreco.2026.123616). 

NOTE: This is a static repository, but the project may evolve. See the linked GitHub repository for the latest updates!

Most of the data required to reproduce our results can be obtained from public and open-access sources. These sources are referenced in the README files within each data folder of the repository. All additional layers that are not distributed directly can be generated using the code provided in this repository.

The main exception is the forest ownership map used to classify forest management types. Due to data-sharing agreements with the respective regional authority, we are not permitted to redistribute this dataset. We provide the analysis datatable with the respective ownership category in the data repositoy, but without coordinates. For full reproducibility, users should request access to the forest ownership data directly from the regional authority.

In addition, not all canopy height models (CHMs) are publicly available. Several of the photogrammetric canopy height model for some years must also be requested from the local authority (either The Bavarian State Institue of Forestry or the Bavarian Agency for Digitisation, High-Speed Internet and Surveying). This situation may change over time, as the Bavarian Agency for Digitisation, High-Speed Internet and Surveying is progressively expanding its Open Data Portal. Depending on the timing of access, all CHM datasets may become openly accessible. (https://geodaten.bayern.de/opengeodata/) 

Where datasets are not publicly available and cannot be shared, this is explicitly stated in the code and in the corresponding directories, including information on where and how to request them.

We provide fully processed data.tables containing all variables required to reproduce the model fitting and subsequent analyses, enabling complete reproducibility once the necessary input layers have been obtained.

--- To ensure transparency and facilitate navigation, empty folders have been created to reflect the directory structure expected by the scripts. ---