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: 10.4121/9b381ed1-de8d-4e44-bf52-c4e8bd8669e7

Zhiyuan Zhao; Capelle, Jacob; de Smit, Jaco; Gerkema, Theo; van de Koppel, Johan et. al. (2024): Data underlying the publication: Boosting efficiency of mussel seed collection for ecological sustainability: identifying critical drivers and informing management. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/9b381ed1-de8d-4e44-bf52-c4e8bd8669e7.v1

Dataset

• Ecological Applications
• Environmental Sciences

Aquaculture, Ecological sustainability, Feature selection, Machine learning, Mussels, Spat collectors, Wadden Sea

2011-2021

CC BY 4.0

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

by Zhiyuan Zhao , Jacob Capelle , Jaco de Smit , Theo Gerkema , Johan van de Koppel , Lin Yuan , Tjeerd J. Bouma

In this study, our objective is to examine the variability of SMCs (suspended mussel spat collectors) efficiency under different habitat conditions and management options. Specifically, we dedicated to address the following key research questions (KRQ):

1)   Is SMCs efficiency consistent across time and space?

2)   Does SMCs efficiency rely on biotic drivers in response to mussel life cycle, such as larval abundance and spat settlement?

3)   Are there critical drivers that would improve the predictability of SMCs efficiency?

4)   How does SMCs efficiency change with potential management strategies targeting identified critical drivers?

Adopting the Dutch Wadden Sea as a model system, we first addressed KRQ_1 by investigating the deployment and harvesting of SMCs in this region over an 11-year period. Secondly, KRQ_2 was validated through a four-year experiment at four representative sites. Thirdly, we utilized machine learning algorithms on an integrated 11-year dataset to identify dominant factors affecting SMCs efficiency and develop a predictive model, addressing KRQ_3. Finally, KRQ_4 was addressed by conducting model experiments that evaluated the sensitivity of SMCs efficiency to critical factors.

 

These files include the data used to create each figure in the manuscript, organized as follows:

1. The 11-year dataset

 

2. Field experiments

 a)       Larval abundance

 b)       Spat settlement

 

For a complete description, see 'Data description.docx'

• 2024-05-29 first online, published, posted

4TU.ResearchData

g-zipped shape files

Boosting efficiency of mussel spat collection for ecological sustainability: identifying critical drivers and informing management

• Dynamos (grant code Dynamos ) the European Fisheries Fund, in collaboration with Producers’ Organization of Dutch Mussel culture (POM).

Royal Netherlands Institute for Sea Research, Department of Estuarine and Delta Systems
Wageningen Marine Research