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Dataset: Size-based, spatially explicit, stochastic demographic model for green abalone

View Data: Data not available yet
Project: 
Program: 
Principal Investigator: 
Giulio Alessandro De Leo (Stanford University)
Co-Principal Investigator: 
James P. Barry (Monterey Bay Aquarium Research Institute, MBARI)
Stephen G. Monismith (Stanford University)
Clifton Brock Woodson (University of Georgia, UGA)
Contact: 
Steven Y. Litvin (Monterey Bay Aquarium Research Institute, MBARI)
BCO-DMO Data Manager: 
Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Restricted: 
No
Validated: 
No
Current State: 
Preliminary and in progress

Size-based, spatially explicit, stochastic demographic model for green abalone

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Description

[2017-08-28]: The metadata for this dataset page is in progress.

R code and associated data for a size-based, spatially explicit, stochastic demographic model to explore how different spatial configurations of marine reserve (MR) networks can affect the abundance and commercial yield of the green abalone (Haliotis fulgens), taking as a reference case the abalone fishery of Isla Natividad in Baja California Sur (Mexico).

The model code is available in as .zip file:  Rossetto_etal_2015_CJFAS-1.0.zip containing R-files. These files are also available in the following GitHub repository: Rossetto_etal_2015_CJFAS (release 1.0).

The model and results were described in the following publication:

Rossetto, M., Micheli, F., Saenz-Arroyo, A., Montes, J. A. E., & De Leo, G. A. (2015). No-take marine reserves can enhance population persistence and support the fishery of abalone. Canadian Journal of Fisheries and Aquatic Sciences, 72(10), 1503-1517. https://doi.org/10.1139/cjfas-2013-0623

More Information about this dataset