Oceanography (e.g. water temperatures, currents, productivity, etc) and climate dynamics have major influences on fish population dynamics and fisheries (Lehodey et al., 2006) in addition to any fishery impacts. Ocean-climate systems have been shown to strongly influence tuna fisheries in the Western and Central Pacific Ocean (WCPO) at various spatio-temporal scales and in different ways (Bour et al., 1981, Lehodey et al. 2003, Lehodey et al., 2006). Changes in oceanography may influence vertical and horizontal movements of tunas and other species, as well as eggs and larval survival. Individual tuna species display different preferences (e.g. preferred temperature) and thus will respond differently to changes in oceanography and climate (Fromentin and Fonteneau, 2001). While beyond the control of fishery managers, it is important to take into account the influence of oceanography and climate in order to better manage fisheries. Globally, tuna catches are highest in the western equatorial Pacific warm pool, a region characterized by low primary productivity and the warmest surface waters of the world’s oceans. However, the WCPO displays remarkable dynamics in oceanography mostly linked to climatic changes (such as El Niño Southern Oscillation, ENSO). In response, variations in tuna catches are reported at both regional and domestic scales both seasonally and inter-annually. The major oceanographic processes that impact on tuna distribution and abundance include in the WCPO are briefly discussed below.
1) Ocean processes that induce movement of water masses play on tuna distribution. Areas of divergence or convergence of currents are of major importance as they induce physical phenomena (upwellings, thermal fronts, eddies) that enhance local productivity and create zones of forage availability. These, in turn, attract and concentrate tuna. A better knowledge of these processes and their spatio-temporal variability remains a key issue for fishery management.
2) Tuna movement is linked to horizontal displacement of surface isotherms and vertical change in mixed layer depth that determine their surface habitat. In particular, east-west migration of the warm pool-cold tongue pelagic ecosystem, should be considered carefully by fisheries managers of the different countries. Analyses have demonstrated that inter annual variability in the environmental conditions linked to climatic oscillation (ENSO) is evident in the operation of the main tuna fisheries and the population dynamics of the tuna species. ENSO affects tuna fisheries through environmental changes in the warm pool-cold tongue system. During El Niño conditions, the distribution of purse-seine catch in the western and central Pacific is generally displaced eastwards, indicating a spatial shift in the distribution of tuna. There is an obvious impact for the Pacific Island Nations through variations in the level of tuna catches in their Exclusive Economics Zones and consequently on their economical revenue, according to the ENSO situation.
3) Contraction or extension of the warm pool also has a major impact on tuna recruitment which varies among species. For tropical species, such as skipjack and yellowfin, El Niño events would favour recruitment through extension of warm water spawning habitat, whereas La Niña events would restricted the favourable spawning areas and reduce the recruitment. For subequatorial species, such as South Pacific albacore, the opposite trends are found. These phenomenons may be taken into account to provide some indication of likely future catches within individual EEZs.
4) Global warming is also likely to affect regional tuna fisheries by raising average sea surface temperature to levels currently experienced during El Niño and by increasing year to year variability. Possible change in primary productivity in the tropical Pacific is also hypothesized. These factors would affect distribution, abundance and catchability of tuna fisheries, but further investigations are required to validate these assumptions.
More on oceanographic variability: Oceanographic variability (1 MB)