The Indian oil sardine (Sardinella longiceps) fishery was observed with wide stock fluctuation. Ecological parameters, mainly temperature and prey density, had a profound influence on the growth of S. longiceps and hence the production. In this study, a fish bioenergetics model, coupled with a lower trophic level model, was developed to reproduce the seasonality in the growth of S. longiceps. For this, we have used an Indian Ocean adaptation of an intermediate complex ecosystem model called North Pacific Ecological Modeling for Understanding Regional Oceanography (NEMURO) for marine productivity simulations. The model has 11-component ecosystem variables such as two types of phytoplankton (small and large including flagellates and diatoms), three types of zoo-planktons (small, large, and predatory, which includes ciliates, copepods, and euphausiids), particulate and dissolved organic matter, opal, cycling of nitrate, ammonia, and silicate. The prey densities derived from the NEMURO were input to the sardine bioenergetics model. The coupled model reproduced the appropriate growth rate and wet-weight of S. longiceps in its seasonal cycle in four major fishery regions such as Kochi, Goa, Ratnagiri, and Mumbai as verifiable from the available observation. In Kochi, the mean wet weight was 72.0 ± 12.8 g (June to September), 65.4 ± 5.3 g (October to November), 82.4 ± 2.7 g (December to February), and 66.7 ± 3.8 g (March to May). Goa and Ratnagiri have moderate weights with mean wet weight as 73.6 ± 10.6 g (June to September), 87.4 ± 3.2 g (October to November), 95.5 ± 4.3 g (December to February), and 76.2 ± 6.8 g (March to May). In the Mumbai region, maximum weight is simulated with mean wet weight as 97.4 ± 13.3 g (June to September), 102.1 ± 1.6 g (October to November), 104.8 ± 1.3 g (December to February), and 101.6 ± 1.2 g (March to May). Sensitivity analysis revealed the importance of temperature and consumption in the growth of sardine. Detailed model validation with available observations is presented.

观察到印度油沙丁鱼（Sardinella longiceps）渔业的种群波动很大。生态参数，主要是温度和猎物密度，对长头鱼的生长产生深远的影响，进而影响产量。在这项研究中，开发了一个鱼类生物能量学模型，再加上一个低营养级模型，以重现S. longiceps生长的季节性. 为此，我们使用了印度洋适应的中间复杂生态系统模型，称为理解区域海洋学的北太平洋生态模型 (NEMURO)，用于海洋生产力模拟。该模型具有 11 个组成部分的生态系统变量，例如两种类型的浮游植物（小型和大型，包括鞭毛藻和硅藻），三种类型的浮游动物（小型、大型和捕食性，包括纤毛虫、桡足类和磷虾）、颗粒和溶解有机物、蛋白石、硝酸盐、氨和硅酸盐的循环。来自 NEMURO 的猎物密度被输入到沙丁鱼生物能量学模型中。耦合模型再现了长头肌的适当生长速度和湿重在四个主要渔业区（如高知、果阿、拉特纳吉里和孟买）的季节性周期中，从现有的观察中可以证实。在高知，平均湿重为 72.0±12.8 克（6 月至 9 月）、65.4±5.3 克（10 月至 11 月）、82.4±2.7 克（12 月至 2 月）和 66.7±3.8 克（3 月至 5 月）。Goa 和 Ratnagiri 体重适中，平均湿重为 73.6 ± 10.6 g（6 月至 9 月）、87.4 ± 3.2 g（10 月至 11 月）、95.5 ± 4.3 g（12 月至 2 月）和 76.2 ± 6.8 g（3 月至 5 月） ）。在孟买地区，最大重量模拟为平均湿重为 97.4 ± 13.3 g（6 月至 9 月）、102.1 ± 1.6 g（10 月至 11 月）、104.8 ± 1.3 g（12 月至 2 月）和 101.6 ± 1.2 g（ 3 月至 5 月）。敏感性分析揭示了温度和消耗量对沙丁鱼生长的重要性。