14.2. The Model
315
frequently exacerbate economic instability, as fishermen strive to maximize
value from catch in the face of an economically doubtful future (Rosenberg
et al. 1993). At the same time, government regulations have shown only
limited success in preventing the collapse both of commercially important
fish populations, and of ancillary industries (Holmes 1994).
Much of the eventual success or failure in addressing a fishery collapse
hinges not only on the management of multiple species in a single assemblage , but also on the collection and assimilation of adequate scientific and
economic data for management. Of similar importance is the communication of knowledge among scientists, policy makers and resource managers.
Improvement of the dialog among the various participants in the management of a multispecies fishery requires that the models used to organize
data and make projections can easily be manipulated by the stakeholders
involved to reflect their understanding and assumptions of the system's
dynamics.
In this chapter, we present an approach aimed at identifying the complex
interactions among exploited species and the implications of these interactions for the associated fisheries. This approach is illustrated with a simple,
dynamic computer model of a multispecies fishery. We develop a threespecies , two-region fishery model , the structure of which is sufficiently
transparent, we believe , to enable modifications and extensions under alternative management assumptions. We conclude the chapter with a set of
model results under alternative management assumptions, and offer some
general conclusions drawn from these results for the dynamics of a multispecies fishery and its conservation and management.
14.2. The Model
The model investigates the interaction of three species-Atlantic cod
(Gadus morbud), haddock (Melannogrammus aeglefinus), and pollock
(Pollachius virens)-within a groundfish assemblage and considers the impacts of different management measures on the composition of the assemblage. Each of the species is considered demersal at some stage in its existence, and all are subject to harvest by mobile fishing gear.
Distinctions are made between populations in different regions, to allow
for fish movement and, thus, temporary changes in population densities. A
spatial disaggregation of the Georges Bank fishery is necessary for at least
two reasons . First, it is recognized that fish at larval, juvenile and adult
stages of their life cycle move in oceans, potentially leading to uneven distributions in population densities within the confines of Georges Bank
(Bowman et al. 1987; Wigley & Serchuck 1992; Carr & Reed 1992). Uneven
population densities, in turn, affect population dynamics in different regions differently through density-dependent natural mortality. Second, fishermen respond to temporal or spatial variations in the distribution of target
315
frequently exacerbate economic instability, as fishermen strive to maximize
value from catch in the face of an economically doubtful future (Rosenberg
et al. 1993). At the same time, government regulations have shown only
limited success in preventing the collapse both of commercially important
fish populations, and of ancillary industries (Holmes 1994).
Much of the eventual success or failure in addressing a fishery collapse
hinges not only on the management of multiple species in a single assemblage , but also on the collection and assimilation of adequate scientific and
economic data for management. Of similar importance is the communication of knowledge among scientists, policy makers and resource managers.
Improvement of the dialog among the various participants in the management of a multispecies fishery requires that the models used to organize
data and make projections can easily be manipulated by the stakeholders
involved to reflect their understanding and assumptions of the system's
dynamics.
In this chapter, we present an approach aimed at identifying the complex
interactions among exploited species and the implications of these interactions for the associated fisheries. This approach is illustrated with a simple,
dynamic computer model of a multispecies fishery. We develop a threespecies , two-region fishery model , the structure of which is sufficiently
transparent, we believe , to enable modifications and extensions under alternative management assumptions. We conclude the chapter with a set of
model results under alternative management assumptions, and offer some
general conclusions drawn from these results for the dynamics of a multispecies fishery and its conservation and management.
14.2. The Model
The model investigates the interaction of three species-Atlantic cod
(Gadus morbud), haddock (Melannogrammus aeglefinus), and pollock
(Pollachius virens)-within a groundfish assemblage and considers the impacts of different management measures on the composition of the assemblage. Each of the species is considered demersal at some stage in its existence, and all are subject to harvest by mobile fishing gear.
Distinctions are made between populations in different regions, to allow
for fish movement and, thus, temporary changes in population densities. A
spatial disaggregation of the Georges Bank fishery is necessary for at least
two reasons . First, it is recognized that fish at larval, juvenile and adult
stages of their life cycle move in oceans, potentially leading to uneven distributions in population densities within the confines of Georges Bank
(Bowman et al. 1987; Wigley & Serchuck 1992; Carr & Reed 1992). Uneven
population densities, in turn, affect population dynamics in different regions differently through density-dependent natural mortality. Second, fishermen respond to temporal or spatial variations in the distribution of target