90
5. Impact of Fishing Pressure on Mean Length of Fish
SMOOTHSHORT_SHARE = SMTH3(SHARE_SHORT,20)
TOTAL_LONG_POP = LONG_YEAR_O_l + LONG_YEAR_l_2 +
LONG_YEAR_2_3
TOTAL_MED_POP = MED_YEAR_O_l + MED_YEAR_l_2 +
MED_YEAR_2_3
TOTAL_POP = TOTAL_SHORT_POP + TOTAL_MED_POP +
TOTAL_LONG_POP
TOTAL_SHORT_POP = SHORT_YEAR_O_l + SHORT YEAR_l_2 +
SHORT_YEAR_2_3
5.2. Arrays in the Population Cohort Model
Whether we are dealing with short, medium or long fish in the population
cohort model of the previous section, the structure of the model is, in
essence , identical for all of them. We can capitalize on this observation and
make our model more compact because STELLA's array features enable us
to do so. To make use of the array features, sketch out the stocks and flows
that underlie our model as shown in Figure 5.13. These stocks and flows will
ultimately represent the subpopulations of short, medium, and long fish.
Next, double-click on the YEAR 0 1 stock and click in the box "Array" at the
upper left portion of the dialog box. This will specify your model as a one-,
or two-dimensional array. A one-dimensional (I-D) array can be thought of
as a single row of stocks, flows, and converters (Figure 5.14). In our case,
each row corresponds to a model of each of the three subpopulations.
A two-dimensional (2-D) array has multiple rows and columns of stocks
that are connected with each other with movement in two dimensions . In
our model , we could interpret each column as an age cohort, and in this
way represent the dynamics of the three-subpopulation, three-age cohort
model of Section 5.1 as a 2-D array. But for now , let's keep to the 1-D array
representation of the dynamics in Section 5.1.
YEAR 0 1
AGE 0 1
YEAR 1 2
AGE 1 2
YEAR 2 3 DEATHS 2 3
FIGURE 5.13
5. Impact of Fishing Pressure on Mean Length of Fish
SMOOTHSHORT_SHARE = SMTH3(SHARE_SHORT,20)
TOTAL_LONG_POP = LONG_YEAR_O_l + LONG_YEAR_l_2 +
LONG_YEAR_2_3
TOTAL_MED_POP = MED_YEAR_O_l + MED_YEAR_l_2 +
MED_YEAR_2_3
TOTAL_POP = TOTAL_SHORT_POP + TOTAL_MED_POP +
TOTAL_LONG_POP
TOTAL_SHORT_POP = SHORT_YEAR_O_l + SHORT YEAR_l_2 +
SHORT_YEAR_2_3
5.2. Arrays in the Population Cohort Model
Whether we are dealing with short, medium or long fish in the population
cohort model of the previous section, the structure of the model is, in
essence , identical for all of them. We can capitalize on this observation and
make our model more compact because STELLA's array features enable us
to do so. To make use of the array features, sketch out the stocks and flows
that underlie our model as shown in Figure 5.13. These stocks and flows will
ultimately represent the subpopulations of short, medium, and long fish.
Next, double-click on the YEAR 0 1 stock and click in the box "Array" at the
upper left portion of the dialog box. This will specify your model as a one-,
or two-dimensional array. A one-dimensional (I-D) array can be thought of
as a single row of stocks, flows, and converters (Figure 5.14). In our case,
each row corresponds to a model of each of the three subpopulations.
A two-dimensional (2-D) array has multiple rows and columns of stocks
that are connected with each other with movement in two dimensions . In
our model , we could interpret each column as an age cohort, and in this
way represent the dynamics of the three-subpopulation, three-age cohort
model of Section 5.1 as a 2-D array. But for now , let's keep to the 1-D array
representation of the dynamics in Section 5.1.
YEAR 0 1
AGE 0 1
YEAR 1 2
AGE 1 2
YEAR 2 3 DEATHS 2 3
FIGURE 5.13