Assessment of the historical, present and future states of marine ecosystem and the effects of human exploitation and climate variation have on the state of ecosystems are necessary to implement an ecosystem-based fishery management system. In particular, understanding how tuna, tuna-like populations and by-catch species respond to environment variation and anthropogenic changes (fishing pressure) is a major challenge for developing this approach. Modeling should be focused on comprehending the mechanisms linking the biological and physical components of marine ecosystems and exploring the responses of populations at higher trophic levels to different types of physical forcing, biological interactions, exploitation and they potential synergies.
Link to the Web SEAPODYM Access
SEAPODYM user manual (1.07 MB)
Tuna - SPC factsheet (3.8 MB)
Around the world, in search of new tools for the ecosystem based management approach, several models have been developed taking a more complex approach to incorporate different types of interactions, including multispecies models with biological interactions, such as multispecies virtual population analysis (Sparre, 1991; Livingston and Jurado-Molina, 2000; Tsou and Collie, 2001) and multispecies statistical model (Jurado-Molina et al. 2005; Jurado-Molina et al., 2006), multispecies models with technological interactions (Siegel et al., 1979), and full ecosystem models, ECOSYM and ECOPATH (Christensen and Walters, 2004; Walters et al.,1997).
In particular, for the South Pacific Region, a spatial ecosystem and population dynamics model (SEAPODYM) has been continuously developed at the Secretariat of the Pacific Community to provide a general framework for the integration of biological and ecological knowledge of tuna species and other oceanic top predators and their responses to fishing pressure.
SEAPODYM is a 2D coupled physical-biological-fisheries model at ocean basin scale. SEAPODYM includes three main linked components: a nutrient-phytoplankton-zooplankton model, a forage sub-model and a tuna age-structured model. The forage and predators dynamics is driven by environmental forcing fields (temperature, currents, dissolved oxygen concentration and primary production) provided by a coupled biogeochemical-physical model. In the forage model, average values of temperature, currents and dissolved oxygen concentrations in three vertical layers are used to describe the biomass distributions of six functional mid-trophic prey groups for young and adult tuna.
These groups are characterized by their habitat and their vertical migration: the epipelagic, the mesopelagic, the bathypelagic, the migrant-mesopelagic, the migrant-bathypelagic and the highly migrant-bathypelagic. Tuna population dynamics is described with a spatial age-structured model where four stages were defined including larvae, juvenile, young and adult individuals; each of these stages were modeled differently depending on their age and type of displacement (diffusion and/or advection) along the Pacific Ocean.
The model uses a likelihood approach for goodness of fit, allowing finding the maximum likelihood estimates of the model parameters, based on observed catch at a given time and region and the observed size composition. The number of estimated parameters varies depending on the number of fisheries; in general is 20 + number of catchability coefficients (one for each fishery) + number of selectivity coefficients (one for each fishery). SEAPODYM has been applied to three Pacific tuna species: skipjack (Katsuwonus pelamis), bigeye (Thunnus obesus) and preliminary results are also available for albacore (Thunnus alalunga). The general SEAPODYM framework is shown below:
Figure 1. SEAPODYM general framework showing the main sub-model components and the information flow.
- Christensen, V and Walters, CJ. 2004. Ecopath with ecosim: methods, capabilities and limitations. Ecological Modelling, 172: 109-139.
- Jurado-Molina J, C Gatica and L A Cubillos. 2006. Incorporating cannibalism into an age-structured model for the Chilean hake. Fisheries research 82: 30-40.
- Jurado-Molina J., P. A. Livingston and J. N. Ianelli. 2005. Incorporating predation interactions to a statistical catch-at-age model for a predator-prey system in the eastern Bering Sea. Canadian Journal of Fisheries and Aquatic Sciences. 62(8): 1865-1873.
- Livingston, P A, and Jurado-Molina, J. 2000. A multispecies virtual population analysis of the eastern Bering Sea. ICES J. Mar. Sci. 57: 294-299.
- Sparre, P. 1991. Introduction to multispecies virtual population analysis. ICES Mar. Sci. Symp. 193: 12-21.
- Tsou T-S, Collie JS (2001) Estimating predation mortality in the Georges Bank fish community. Can. J. Fish. Aquat. Sci. 58: 908-922.
- Walters, C, Christensen, V, and Pauly, D. 1997. Structuring dynamic models of exploited ecosystems from trophic mass balance assessments. Reviews in Fish Biology and Fisheries, 7:139-172.