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Catastrophes, connectivity and Allee effects in the design of marine reserve networks

Cite this dataset

White, Easton; Baskett, Marissa; Hastings, Alan (2020). Catastrophes, connectivity and Allee effects in the design of marine reserve networks [Dataset]. Dryad.


Catastrophic events, like oil spills and hurricanes, occur in many marine systems. One potential role of marine reserves is buffering populations against disturbances, including the potential for disturbance-driven population collapses under Allee effects. This buffering capacity depends on reserves in a network providing rescue effects, setting up a trade-off where reserves need to be connected to facilitate rescue, but also distributed in space to prevent simultaneous extinction. We use a set of population models to examine how dispersal ability and the disturbance regime interact to determine the optimal reserve spacing. We incorporate fishing in a spatially-explicit model to understand the effect of objective choice (e.g., conservation versus fisheries yield) on the optimal reserve spacing. We show that the optimal spacing between reserves increases when accounting for catastrophes with larger spacing needed when Allee effects interact with catastrophes to increase the probability of extinction. We also show that classic tradeoffs between conservation and fishing objectives disappear in the presence of catastrophes. Specifically, we found that at intermediate levels of disturbance, it is optimal to spread out reserves in order to increase both population persistence and to maximize spillover into non-reserve areas.


This repository contains R markdown files and scripts to produce the figures and supplementary material for a paper at Oikos:

The R markdown files run simulations and create figures. Therefore, it takes a long time (several days on a typical laptop) to compile the file. Please contact Easton White ( with any concerns or feedback. The code will also be maintained at:

Usage notes

ReadMe file is included


National Science Foundation, Award: DMS-1817124