Abdul-Razak Salifu, Qian P Li, Zhengchao Wu, Fulin Sun, Lin Guo
Here, we develop a bioenergetic model for epipelagic tuna based on the Von Bertalanffy Growth Function to explain the divergent responses of the Length-Weight Relationship (LWR) in Yellowfin and Skipjack tunas to varying sea surface temperature (SST) and chlorophyll-a (SSChl).
Yellowfin tuna (Thunnus albacares) and skipjack tuna (Katsuwonus pelamis) are among the most heavily exploited pelagic species, with combined annual catches exceeding 4.6 million tons. However, how regional environmental conditions affect tuna growth across different areas remains poorly understood. Here, we develop a bioenergetic model for epipelagic tuna based on the Von Bertalanffy Growth Function to explain the divergent responses of the Length-Weight Relationship (LWR) in Yellowfin and Skipjack tunas to varying sea surface temperature (SST) and chlorophyll-a (SSChl). We found the LWR scaling factor (b) decreased with rising SSChl in the South China Sea (SCS), the Eastern Indian Ocean (EIO), and the South Atlantic near Brazil (SAB) but increased in the North Bone Bay (NBB), the South Bone Bay (SBB), and the Indonesian Sea (IS). We also found a positive response of b to SST across most of our study regions, yet showed a significant negative response in the SBB. A bioenergetic model analysis revealed that these patterns are driven by ontogeny and prey composition. The anomalous positive SST effect in the SBB is explained by the region's much larger Yellowfins (with asymptotic maximal length of L∞ = 207 cm and asymptotic maximal weight W∞ = 176 kg) compared to the average size (L∞ = 144.7 cm, W∞ = 53.89 kg) over various study sites. The SSChl dichotomy reflects the diversity in the dominant prey of the study sites, with a negative correlation indicating bottom-up control via planktonic prey, while a positive correlation, as seen in the NBB/SBB, signals a trophic cascade where tuna prey on intermediate trophic levels, decoupling their condition from direct primary production. This framework enables robust projections of tuna populations under future climate change.