The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/9b2fb6d8-e2e7-4768-ad1a-bcf903c4eb20

Cornacchia, Loreta; van de Vijsel, Roeland; van der Wal, Daphne; Ysebaert, Tom; Sun, Jianwei et. al. (2024): Data underlying the publication: Vegetation traits and biogeomorphic complexity shape the resilience of salt marshes to sea-level rise. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/9b2fb6d8-e2e7-4768-ad1a-bcf903c4eb20.v1

Dataset

• Ecology
• Geophysics
• Physical Geography and Environmental Geoscience
• Earth Sciences
• Biological Sciences

ecological complexity, resilience, salt marsh, sea-level rise

2006, 2017, 2020

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Loreta Cornacchia , Roeland van de Vijsel , Daphne van der Wal , Tom Ysebaert , Jianwei Sun , Bram van Prooijen , Paul Lodewijk Maria de Vet , Quan-Xing Liu , Johan van de Koppel

This dataset contains the data presented in the article:

Cornacchia, L., van de Vijsel, R.C., van der Wal, D., Ysebaert, T., Sun, J., van Prooijen, B., de Vet, P.L.M., Liu, Q.-X., van de Koppel, J. Vegetation traits and biogeomorphic complexity shape the resilience of salt marshes to sea-level rise. Communications Earth & Environment (2024).

The aim of this research was to investigate the interaction and relative importance of salt marsh vegetation characteristics and creek network complexity for salt marsh resilience to increased water levels, as can be expected with sea-level rise.

This dataset therefore contains: i) model scripts and results from the numerical model (SFERE) for vegetation effects on tidal network formation; 2) digital terrain models of real-world tidal channel networks; 3) data from field experiments in real-world tidal channels where hydrodynamics, sediment transport and deposition patterns were measured. The README-file explains the exact contents of this dataset. This version of the SFERE model can also be found on Zenodo (https://doi.org/10.5281/zenodo.13895003).

• 2024-10-23 first online, published, posted

4TU.ResearchData

Jupyter Notebook and OpenCL model scripts (ipynb, cl); Python model results (npz); data from field experiments and model outputs (csv, xlsx); digital terrain models (tif).

• Coping with deltas in transition (grant code PSA-SA-E-02) Royal Netherlands Academy of Arts and Sciences (KNAW)

NIOZ Royal Netherlands Institute for Sea Research