Marine Protected Areas and Spatial Targeting

The MSEtool allows for some paramterization of spatial differences in fishing. Users can close area 1 to fishing for all years (historical and projected) in area 1 by creating a Marine Protected Area (MPA).

More complex MPAs, such as those that are not present for all years of the simulation, can be created using custom parameters. Users can also specify spatial targeting or avoidance behavior by the fleet.


Logical argument (TRUE or FALSE). Creates an MPA in Area 1 for all years if true is selected. Defaults to FALSE.


Distribution of fishing in relation to vulnerable biomass (VB) across areas. The distribution of fishing effort is proportional to VB^Spat_targ. Upper and lower bounds of a uniform distribution. For each simulation a single value is drawn from a uniform distribution specified by the upper and lower bounds provided. This parameter allows the user to model either avoidance or spatial targeting behavior by the fleet. If the parameter value is 1, fishing effort is allocated across areas in proportion to the population density of that area. Values below 1 simulate an avoidance behavior and values above 1 simulate a targeting behavior.

Custom Parameters

See Custom Fleet Parameters for information on specifying spatial closures for specific historical years.

Interactive App

Choose upper and lower bounds for Spat_targ. Based on these ranges, the MSEtool will display parameter values for 5 simulations in the table. Click on any line of the table to view how those parameter values affect spatial targeting behavior in the model.

  • Figure 1 shows the relationship between the fraction of the vulnerable biomass (VB) currently located in Area 1 and the proportion of fishing effort allocated to that area for each simulation. Spat_targ values equal to 1 simulate a situation in which fishing effort in each area is proportional to the vulnerable biomass in the area. Values greater than 1 result in a higher proportion of fishing effort being allocated when the fraction of the VB is greater than 50% (and vice versa), simulating more intense spatial targeting. Values less than 1 but greater than 0 result in a lower proportion of fishing effort being allocated when the fraction of the VB is greater than (less spatial targeting). Values close to 0 result a situation where the amount of fishing effort is evenly divided between areas regardless of the population in each area. Values close to negative 1 result in an avoidance behavior, where the proportion of fishing effort allocated in an area decreases linearly as the VB in area 1 increases. Values below -1 intensify this avoidance behavior.