Dataset for "Plant traits determining biogeomorphic landscape dynamics: a study on clonal expansion strategies driving cliff formation at marsh edges"
doi:10.4121/16912183.v1
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doi: 10.4121/16912183
doi: 10.4121/16912183
Datacite citation style:
Cao, Haobing (2021): Dataset for "Plant traits determining biogeomorphic landscape dynamics: a study on clonal expansion strategies driving cliff formation at marsh edges". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16912183.v1
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Dataset
usage stats
816
views
323
downloads
categories
geolocation
Yerseke
time coverage
2016-2018
licence
CC BY 4.0
This dataset contains i) the clonal expansion traits of three marsh species (Spartina anglica, Scirpus maritimus, and Phragmites australis) at marsh edges in a series of mesocosm experiments; and ii) cliff formation at mimicked marsh edges (S. anglica and S. maritimus, that with contrasting clonal expansion traits) in a flume experiment. This study examined how species-specific differences in expansion strategy, i.e. clonal step-length of laterally expanding tillers, both respond to sediment type and drive cliff formation and persistence.
history
- 2021-11-01 first online, published, posted
publisher
4TU.ResearchData
format
xlsx, docx
associated peer-reviewed publication
Plant traits determining biogeomorphic landscape dynamics: a study on clonal expansion strategies driving cliff formation at marsh edges
funding
- 2016YFE0133700
- PSA-SA-E-02
- National Natural Science Foundation of China (Grant No: 41876093)
- A Study on the Process and Mechanism of Steady-State Transformation of the Yangtze Estuary Salt Marsh Ecosystem (grant code 41876093) [more info...] National Natural Science Foundation of China
- Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2019ZT08L213)
organizations
NIOZ Royal Netherlands Institute for Sea Research, Department of Estuarine and Delta Systems;
DATA
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- 16,322 bytesMD5:
a814bf01045ec5b5c15a66bf9a6f1f47
README.docx - 75,355 bytesMD5:
1760f8cadf3a480956dacf4255b794ac
Cao et al._2021_lno_dataset.xlsx - 14,162 bytesMD5:
4ed89043d067a440b87655b2844950cd
Cao et al._2021_lno_description_dataset.docx -
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