13.2. The Model
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biomass to go. Unfortunately, parameterizing these models has proven difficult. Many researchers have attempted to differentiate, expand, or elaborate upon any number of versions of the dynamic pool model so that the
entire fishery can be analyzed in a single function (see (Pitcher and Hart
1982) for a nice review) . We have avoided this method and opted for a
more realistic and explicit approach.
In developing our model , we held the following ten assumptions.
1) The energy allocation rates and proportions for Nile perch can be described using mass-balance theory as is described below (see Kitchell et
al. 1997).
2) Nile perch do not show selectivity towards any susceptible prey type, but
rather consume prey in relation to the prey 's relative densities in the
community. Although selectivity may play a significant role in determining the diet of Nile perch, their trophic plasticity appears to dominate their feeding behavior (Hughes 1986; Ogutu-Ohwayo 1990).
3) There is no time-lag between changes in Nile perch diet and changes in
their prey community. It has been suggested that Nile perch show selectivity for haplochromines (Ogari and Dadzie 1988; Ogutu-Ohwayo
1990; Ogutu-Ohwayo 1994) (which would cause a lag in the functional
response of Nile perch), but these claims have yet to be substantiated.
4) Nile perch are not significantly preyed upon by any of the otherfisbes in
Lake Victoria . Although this assumption is highly questionable, we do not
have bioenergetic models of the other predators from Lake Victoria. Thus,
their feeding effects cannot be included in this version of the model.
5) The reproductive potential ofNileperch can be calculated as a function
oftotal mature perch biomass (Hughes 1992; Ogutu-Ohwayo 1988). Unfortunately, the stock recruitment dynamics of Nile perch are poorly understood, and thus assumptions 5 and 6 cannot be addressed in this
version of the model.
6) Over intermediate densities ofNileperch, the relation between stock and
recruitment is linear. See at 5.
7) Nile perch will not migrate to any great extent until total prey populations decrease to very low levels, or some other environmental change
occurs. The migratory patterns of Nile perch are not well studied. We
hope that future research will allow spatially explicit versions of the
model to be developed.
8) Any given area ofthe lake has a total carrying capacity for itsprey populations, limiting the absolute magnitude ofenergy which can accumulate. Dynamic models of the Nile perch prey species have not been developed. Instead , we use simple differential equations that share a
common total carrying capacity.
9) When free from predation by Nile perch, the baplocbromine cichlid
community will dominate the lake (Fryer and Iles 1972; Lowe-McConnell
1995).
261
biomass to go. Unfortunately, parameterizing these models has proven difficult. Many researchers have attempted to differentiate, expand, or elaborate upon any number of versions of the dynamic pool model so that the
entire fishery can be analyzed in a single function (see (Pitcher and Hart
1982) for a nice review) . We have avoided this method and opted for a
more realistic and explicit approach.
In developing our model , we held the following ten assumptions.
1) The energy allocation rates and proportions for Nile perch can be described using mass-balance theory as is described below (see Kitchell et
al. 1997).
2) Nile perch do not show selectivity towards any susceptible prey type, but
rather consume prey in relation to the prey 's relative densities in the
community. Although selectivity may play a significant role in determining the diet of Nile perch, their trophic plasticity appears to dominate their feeding behavior (Hughes 1986; Ogutu-Ohwayo 1990).
3) There is no time-lag between changes in Nile perch diet and changes in
their prey community. It has been suggested that Nile perch show selectivity for haplochromines (Ogari and Dadzie 1988; Ogutu-Ohwayo
1990; Ogutu-Ohwayo 1994) (which would cause a lag in the functional
response of Nile perch), but these claims have yet to be substantiated.
4) Nile perch are not significantly preyed upon by any of the otherfisbes in
Lake Victoria . Although this assumption is highly questionable, we do not
have bioenergetic models of the other predators from Lake Victoria. Thus,
their feeding effects cannot be included in this version of the model.
5) The reproductive potential ofNileperch can be calculated as a function
oftotal mature perch biomass (Hughes 1992; Ogutu-Ohwayo 1988). Unfortunately, the stock recruitment dynamics of Nile perch are poorly understood, and thus assumptions 5 and 6 cannot be addressed in this
version of the model.
6) Over intermediate densities ofNileperch, the relation between stock and
recruitment is linear. See at 5.
7) Nile perch will not migrate to any great extent until total prey populations decrease to very low levels, or some other environmental change
occurs. The migratory patterns of Nile perch are not well studied. We
hope that future research will allow spatially explicit versions of the
model to be developed.
8) Any given area ofthe lake has a total carrying capacity for itsprey populations, limiting the absolute magnitude ofenergy which can accumulate. Dynamic models of the Nile perch prey species have not been developed. Instead , we use simple differential equations that share a
common total carrying capacity.
9) When free from predation by Nile perch, the baplocbromine cichlid
community will dominate the lake (Fryer and Iles 1972; Lowe-McConnell
1995).