## Fishing Effort

This section includes parameters related to historical and future fishing effort. The MSEtool needs to determine how the fishing mortality rate, which is defined as the proportion of the stock that dies due to fishing, has changed over time. However, in many fisheries, especially those that are data poor, it is easier determine how fishing effort, which can be measured in terms of number of boats, traps, trips, etc., has changed. Fishing effort is related to the fishing mortality rate via the “catchability” parameter (q), and so with some information about historical fishing effort (along with the other information provided) the model is able to infer plausible historical fishing mortality rates.

The EffUpper and EffLower slots provide a way to include information on how fishing effort changes over the history of the fishery. This information is used to help guide the initialization of the model. When the model is initialized, it samples possible time series of fishing mortality rates and recruitment events that fit the information provided. Series that cannot achieve the specified current depletion level (D) are discarded.

While historical fishing effort data may be absent in data poor fisheries, there are a number of different types of information that can be used to define EffUpper and EffLower. Information on number of participants or vessels may serve as a proxy if direct effort data (such as number of trips or trawl hours) are not available. Information from older participants may also be used to determine the years during which the fishery first developed, when effort increased, peak effort, and/or effort declines. It is not necessary to include data for every year; the MSEtool will interpolate linearly between the years for which values are provided. While catch can increase or decrease for reasons other than changes in fishing effort, in the absence of effort data catches along with information about participation, market conditions, regulations, etc., may be used to identify historical effort patterns.

The width of the upper and lower bounds can be used to indicate the level of confidence in the historical effort estimates. More precise effort estimates can be parameterized with smaller ranges between the upper and lower bounds (for example, EffUpper and EffLower are parameterized as +/- 10% of the estimate), while less certain information should have wider bounds to allow the model more freedom in selecting plausible historical fishing mortality rates. In data rich fisheries where estimates of yearly historical fishing mortality rates may be available from a stock assessment, these point values can be provided directly to the model by using the custom parameter OM@cpars\$F_Ind. If F_Ind is provided there is no need to specify EffLower, EffUpper, and Esd. See the Custom Parameters section for more details.

### EffYears

Vector indicating the historical years where there is information available to infer the relative fishing effort expended.This vector is specified in terms of the position of the year in the vector rather than the calendar year. For example, say our simulation starts with an unfished stock in 1975,and the current year (the last year for which there is data available) is 2019. Then there are 45 historical years simulated, and EffYears should include numbers between 1 and 45. Note that there may not be information available for every historical year, especially for data poor fisheries. In these situations, the EffYears vector should include only the positions of the years for which there is information, and the vector may be shorter than the total number of simulated historical years (nyears).

### EffLower

Lower bound on relative fishing effort corresponding to EffYears. EffLower must be a vector that is the same length as EffYears describing how fishing effort has changed over time. Information on relative fishing effort can be entered in any units provided they are consistent across the entire vector because the data provided will be scaled to 1 (divided by the maximum number provided).

### EffUpper

Upper bound on relative fishing effort corresponding to EffYears. EffUpper must be a vector that is the same length as EffYears describing how fishing effort has changed over time. Information on relative fishing effort can be entered in any units provided they are consistent across the entire vector because the data provided will be scaled to 1 (divided by the maximum number provided).

### Esd

Additional inter-annual variability in fishing mortality rate. For each historical simulation a single value is drawn from a uniform distribution specified by the upper and lower bounds provided. If this parameter has a positive (non-zero) value, the yearly fishing mortality rate is drawn from a log-normal distribution with a standard deviation (in log space) specified by the value of Esd drawn for that simulation. This parameter applies only to historical projections.

### Custom Parameters

See Custom Fleet Parameters for information on specifying simulation- and year-specific values for historical fishing effort/mortality.

### Interactive App

Choose from one of three historical effort patterns.

Table 1 shows the EffYears, EffUpper, and EffLower values associated with each pattern, and Figure 1 shows the upper and lower bounds on historical fishing effort over time. Then, select upper and lower bounds for the Esd parameter. Table 2 shows randomly drawn parameter values for 5 simulations. Click on any line of the table to view a time series of the yearly relative historical effort selected for that simulation.

• Figure 1 shows a plot of the upper and lower effort values provided as parameter inputs to help guide model initialization (values also shown in table 1). Note that in this example values are only provided for some years. The graph shows how the MSEtool interpolates between the years for which values are provided in order to guide selection of viable fishing effort values for each simulations.

• Figure 2 shows the time series of historical fishing effort that was selected by the MSEtool during the model initialization phase. Each historical effort trajectory was selected based on the information provided about the upper and lower effort bounds as well as year-to-year variability in effort (Esd), as well as the biological and current depletion parameters.