Environmental Conditions Are Important Influences on the Recruitment of North Pacific Albacore Tuna, Thunnus Alalunga

Abstract

Abstract. The effects of changing climate on numerous commercially and ecologically important fish species including the South Pacific albacore tuna, Thunnus alalunga have been documented over the past decades. The objective of this study was to explore and elucidate the relationship of environmental variables with the stock parameters of albacore tuna. The relationship of the North Pacific albacore tuna recruitment (R), female spawning stock biomass (SSB) and recruits per spawning biomass (RPS) from 1970 to 2012 with the environmental factors of sea surface temperature (SST), Pacific decadal oscillation (PDO) and El Niño southern oscillation (ENSO) was construed. SST and PDO were used as independent variables with SSB to construct stock reproduction models for R and RPS as they showed most significant relationship with the dependent variables. Model selections were based on Akaike Information Criterion (AIC) with the condition of significant parameter estimates at p<0.05. Models with single independent variables of SST, PDO and ENSO were also constructed to illuminate their individual effect on albacore R and RPS. From the results it can be stated that SST and PDO resulted in the most significant models for reproducing North Pacific albacore tuna R and RPS time series.

Multisatellite-Based Feeding Habitat Suitability Modeling of Albacore Tuna in the Southern Atlantic Ocean

“…Moreover, migration is triggered by food availability, which is mainly indicated by SSC and optimal SST [17,28,58,61]. Recent findings have demonstrated that SST and SSC play significant roles in most abundance models of albacore distribution [28,36,40,45]. The length distribution of albacore tuna (Figure 8) highlighted the potential of feeding grounds of immature albacore near the temperate to subtropical area, which is as a function of the SST front [36].…”

“…The albacore optimal habitat was detected in areas where SST and SSC were 16.5 • C-19.5 • C and 0.11-0.33 mg/m 3 , respectively. For oceans worldwide, preferential ranges for various biophysical environmental variables that affect albacore habitat and abundance have already been hypothesized [6,9,17,36,45,58]. The AMM-based HSI prediction maps for albacore characterized a substantial monthly suitable habitat variation that shifted northward from approximately 40 • S in April to approximately 18 • S in July to August.…”

“…A thermocline between 25 and 30 m vertical depth having temperatures of 14 and 17 • C in the deepest and shallowest area, respectively, might be a reason that tuna are located in a certain range of depth without their surface detection, as it inhabits a wide vertical range [36]. Moreover, albacore tuna swim diagonally or vertically to gain advantage over prey by warming their bodies, which might also be a good possible reason for albacore preferring habitats at different depths [45]. Nieto et al [11] described that albacore tuna preferred warm water to reduce heat loss and maintain body temperature; this is also related to thermocline depth and upwelling.…”

“…Assuming that environmental factors are the only variables influencing the habitat of South Atlantic albacore would be quite optimistic, however. In reality, despite the dynamicity of marine fisheries, climatic change, global warming, and various biotic and abiotic factors could alter tuna migration, food availability, catch rate, and stock indices, all of which are related to habitat [45,56,58,60,80]. Determining the precise mechanism(s) underlying suitable habitat is challenging; additionally, whether the interannual distribution shifts of species are mainly associated with other ocean-climate factors, prey abundance, or even another factor like fleet behavior [81] remains unclear.…”

“…In the context of sustainable fisheries management, the main objective of EBFM translates into guaranteeing the sustainability of harvests without compromising the shape and functioning of marine ecosystems [15]. Many studies have focused on fishery biology, population structure, distribution, and migration [33,37,[42][43][44], but few have investigated essential fish habitat, especially in the SAO [36,45]. Thus, developing a habitat model using multisatellite remotely sensed data is critical, as it might provide new insights into promoting EBFM in regional tuna fisheries management organizations [15].…”