11:00 〜 13:00
[AOS12-P05] 生物エネルギー・個体群動態結合モデルの開発：マサバ太平洋系群を例として
キーワード：マサバ、生物エネルギーモデル、個体群動態モデル、北西太平洋
The chub mackerel (Scomber japonicus) is a small pelagic fish that widely distribute in temperate zones. In their early life stages, they mainly feed on zooplankton like other small pelagic fish species, but as they grow, they become to show characteristics of piscivore to predate on other small pelagic fish species especially for Japanese anchovy. It is known that, in the waters around Japan, fish species alternation phenomenon occurs in which chub mackerel, anchovy, and sardine are replaced as the main fisheries landing. In order to clarify the mechanism of the fish species alternation, it is necessary to understand the interspecies relationship between chub mackerel and anchovy. As the first step, this study coupled a fish growth bioenergetics model with a population dynamics model to express the stock fluctuation. A bioenergetics / population dynamics coupling model will be constructed for the chub mackerel and anchovy, and then the interspecific relationship between the predator chub mackerel and the prey anchovy will be incorporated, and the effect of interspecific relationship between the two species to the fish species alternation will be focused. In order to realize sustainable resource management under the influence of global climate change, it is indispensable to elucidate the mechanism of the fish species alternation, which is a large-scale resource change.
We first modeled the growth and abundance of chub mackerel inhabiting the eastern part of Japan. The parameters of the bioenergetics model were determined based on previous literatures. Some biological parameters have not been figured out for chub mackerel and were determined using results of studies for other mackerel species. In addition, half-saturation constant, which reflects the prey density dependence of consumption, was adjusted within a certain range to reproduce realistic body weight compared with the observed data. As for simplicity, general migration route of chub mackerel was prescribed, and the experienced temperature and pray condition were derived from satellite observations.
The body weight and body length obtained by model calculation became close to the observed data for all the life stages of chub mackerel by adjusting the half saturation constants under the climatological environmental forcing. The energy intake by feeding and the energy consumption associated with respiratory metabolism in the bioenergetics model showed seasonal variation responding to temperature and prey climatological seasonal variabilities. With historical forcing from 1998 to 2018, the modeled population and biomass showed similar tendency with the observed data: both showed increase after 2010. We are analyzing the mechanism how environmental factors are controlling the growth and population fluctuations in the model and the details will be reported at the meeting.
We first modeled the growth and abundance of chub mackerel inhabiting the eastern part of Japan. The parameters of the bioenergetics model were determined based on previous literatures. Some biological parameters have not been figured out for chub mackerel and were determined using results of studies for other mackerel species. In addition, half-saturation constant, which reflects the prey density dependence of consumption, was adjusted within a certain range to reproduce realistic body weight compared with the observed data. As for simplicity, general migration route of chub mackerel was prescribed, and the experienced temperature and pray condition were derived from satellite observations.
The body weight and body length obtained by model calculation became close to the observed data for all the life stages of chub mackerel by adjusting the half saturation constants under the climatological environmental forcing. The energy intake by feeding and the energy consumption associated with respiratory metabolism in the bioenergetics model showed seasonal variation responding to temperature and prey climatological seasonal variabilities. With historical forcing from 1998 to 2018, the modeled population and biomass showed similar tendency with the observed data: both showed increase after 2010. We are analyzing the mechanism how environmental factors are controlling the growth and population fluctuations in the model and the details will be reported at the meeting.