Scientific publications related to SVD
Model development and applications are reported in top-level journals such as Science, Nature communications Earth & Environment, Global Change Biology, Methods in Ecology and Evolution:
Modeling papers
- Rammer W, Seidl R, 2019. A scalable model of vegetation transitions using deep neural networks. Methods Ecol. Evol., DOI: 10.1111/2041-210X.13171, download Supplementary information
Application papers
Grünig, M., Rammer, W., Senf, C., Albrich, K., André, F., Augustynczik, A. L. D., Baumann, M., Bohn, F. J., Bouwman, M., Bugmann, H., Collalti, A., Cristal, I., Dalmonech, D., De Coligny, F., Dobor, L., Dollinger, C., Espelta, J. M., Forrester, D. I., Garcia-Gonzalo, J., … Seidl, R. (2026). Climate change will increase forest disturbances in Europe throughout the 21st century. Science, 391(6789), eadx6329. https://doi.org/10.1126/science.adx6329, data repository: https://datadryad.org/dataset/doi:10.5061/dryad.tb2rbp0dv
Rammer, W., Braziunas, K. H., Hansen, W. D., Ratajczak, Z., Westerling, A. L., Turner, M. G., & Seidl, R. (2021). Widespread regeneration failure in forests of Greater Yellowstone under scenarios of future climate and fire. Global Change Biology, 27(18), 4339–4351. https://doi.org/10.1111/gcb.15726