Open-ocean and deep-sea ecosystems can be difficult to model due to the challenges of incorporating important dynamics such as diel vertical migration and particle sinking, as well as the absence of long-term datasets for deep-sea taxa abundance, distribution, and physiological parameters. The data collection that followed the Deepwater Horizon Oil Spill provided the unique opportunity to model the oceanic Gulf of Mexico in a way that was not previously possible. Using new biomass datasets, we developed a depth-resolved food web model to better understand the trophic dynamics of the oceanic Gulf of Mexico. The model tracks vertical energy transfer in the water column between three depth zones: the epipelagic (0–200 m), mesopelagic (200–1000 m) and bathypelagic (>1000 m). This functionality allows us to demonstrate how changes in the biomass of specific functional groups, such as large jellyfish, non-copepod mesozooplankton, decapods, and strongly migrating mesopelagic fishes affect the food web within each depth zone. Non-copepod mesozooplankton and euphausiids were shown to have greater importance in energy transfer, particularly in meso‑ and bathypelagic depth zones, than other functional groups. Increasing large jellyfish biomass by 25 % resulted in decreases in biomass of most of the other forage functional groups, particularly mesopelagic fishes and small gelatinous carnivores, two groups that actively compete with and are consumed by large jellyfish. A simulated decrease in strongly migrating mesopelagic fish biomass of 25 % increased the biomass of functional groups presumed to be in competition with strongly migrating mesopelagic fishes, such as weak and non-migrating mesopelagic fishes. The static scenarios presented here lay the groundwork for interesting dynamic simulations with this modeling platform that will help determine how these impacts may affect the food web over time.

由于纳入昼夜垂直迁移和粒子下沉等重要动态的挑战，以及缺乏深海类群丰度、分布和分布的长期数据集，公海和深海生态系统可能难以建模。生理参数。深水地平线漏油事件后的数据收集提供了独特的机会，以以前不可能的方式对墨西哥湾进行建模。使用新的生物量数据集，我们开发了深度解析的食物网模型，以更好地了解墨西哥湾海洋的营养动态。该模型跟踪三个深度区域之间水柱的垂直能量传递：上层（0-200 m）、中层（200-1000 m）和深海（>1000 m）。这一功能使我们能够展示特定功能群（例如大型水母、非桡足类中生浮游生物、十足目动物和强烈洄游的中层鱼类）的生物量变化如何影响每个深度区域内的食物网。研究表明，与其他功能类群相比，非桡足类中生浮游生物和磷虾类在能量转移方面具有更大的重要性，特别是在中层和深海深度区域。大型水母生物量增加25%会导致大多数其他饲料功能类群的生物量减少，特别是中层鱼类和小型胶状食肉动物，这两个类群与大型水母积极竞争并被大型水母捕食。强洄游中层鱼类生物量模拟减少25%，增加了被认为与强洄游中层鱼类（例如弱和非洄游中层鱼类）竞争的功能群的生物量。这里介绍的静态场景为使用该建模平台进行有趣的动态模拟奠定了基础，这将有助于确定这些影响随着时间的推移如何影响食物网。