Environmental effects on recruitment and productivity of Japanese sardine Sardinops melanostictus and chub mackerel Scomber japonicus with recommendations for management

Abstract

We compared a wide range of environmental data with measures of recruitment and stock production for Japanese sardine Sardinops melanostictus and chub mackerel Scomber japonicus to examine factors potentially responsible for fishery regimes (periods of high or low recruitment and productivity). Environmental factors fall into two groups based on principal component analyses. The first principal component group was determined by the Pacific Decadal Oscillation Index and was dominated by variables associated with the Southern Oscillation Index and Kuroshio Sverdrup transport. The second was led by the Arctic Oscillation and dominated by variables associated with Kuroshio geostrophic transport. Instantaneous surplus production rates (ISPR) and log recruitment residuals (LNRR) changed within several years of environmental regime shifts and then stabilized due, we hypothesize, to rapid changes in carrying capacity and relaxation of density dependent effects. Like ISPR, LNRR appears more useful than fluctuation in commercial catch data for identifying the onset of fishery regime shifts. The extended Ricker models indicate spawning stock biomass and sea surface temperatures (SST) affect recruitment of sardine while spawning stock biomass, SST and sardine biomass affect recruitment of chub mackerel. Environmental conditions were favorable for sardine during 1969-87 and unfavorable during 1951-67 and after 1988. There were apparent shifts from favorable to unfavorable conditions for chub mackerel during 1976-77 and 1985-88, and from unfavorable to favorable during 1969-70 and 1988-92. Environmental effects on recruitment and surplus production are important but fishing effects are also influential. For example, chub mackerel may have shifted into a new favorable fishery regime in 1992 if fishing mortality had been lower. We suggest that managers consider to shift fishing effort in response to the changing stock productivity, and protect strong year classes by which we may detect new favorable regimes.

Changes in the abundance and spatial distribution of the Atlantic chub mackerel (<i>Scomber colias</i>) in the pelagic ecosystem and fisheries off Portugal

“…Temperature seems to play an important role in the recruitment success of both species of chub mackerel. Higher temperatures, often related to weak upwelling, are considered favourable to spawning and productivity of chub mackerel off South Africa (Crawford 1983), northwest Africa (Cury and Roy 1987), Japan (Yatsu et al 2005) and the California Current System (Parish and MacCall 1978). In some regions, booms and bursts of chub mackerel species at decadal scales were part of global changes often associated with environmental regime shifts affecting pelagic ecosystems (Castro-Hernández and Santana-Ortega 2000 and references therein).…”

Synchrony of Marine Fish Catches and Climate and Ocean Regime Shifts in the North Pacific Ocean

“…It is clear from evidence provided in a number of studies that climate profoundly affects fish production and that these effects are not random (Finney et al 2000;Hare and Mantua 2000;McFarlane et al 2000;Beamish and Noakes 2004;Beamish et al 2004b;Yatsu et al 2005;Lehodey et al 2006;Osgood 2008). It would be informative and useful to determine whether fisheries for major species responded to climate change in a similar fashion, as the future health of these fisheries has major economic and social impacts.…”

Modeling the Effect of Environmental Factors on the Ricker Stock-Recruitment Relationship for North Pacific Albacore Using Generalized Additive Models

“…Ricker models have been modified and widely applied in previous analyses of stock-recruitment relationships (Sakuramoto 2005;Yatsu et al 2005;Arregui et al 2006;Nishida et al 2007). Ricker models are based on the assumption that the mortality rate of juveniles depends on the initial cohort size.…”

“…Studies on environmental variations related to population abundance (Myers 1998) and recruitment success (e.g., Planque and Frédou 1999;Begg and Marteinsdottir 2002;Nishida et al 2007) have became much more common in recent years. Among those studies, sea temperature (Planque and Frédou 1999;Begg and Marteinsdottir 2002;Nishida et al 2007) and large-scale climatic oscillations (Yatsu et al 2005;Arregui et al 2006) were frequently investigated and discussed.…”

“…To examine the stock-environment-recruitment relationship properly, various models, such as linear regression models (Sparholt 1996), generalized additive models (GAM) (Daskalov 1999;Megrey et al 2005), principal component analysis (PCA) (Yatsu et al 2005), artificial neural networks (ANN) (Arregui et al 2006) etc. have been applied.…”