论文标题

SPRAT:基于人口平衡方程的空间解释海洋生态系统模型

SPRAT: A Spatially-Explicit Marine Ecosystem Model Based on Population Balance Equations

论文作者

Johanson, Arne N., Oschlies, Andreas, Hasselbring, Wilhelm, Hasselbring, Wilhelm, Worm, Boris

论文摘要

为了通过基于生态系统的方法成功管理海洋渔业,考虑不断变化的环境条件,对鱼类种群开发的长期预测是必要的。这些预测可以由端到端的生态系统模型提供,该模型将现有的物理和生物地球化学海洋模型与新开发的空间说明的鱼类库存模型相结合。通常,基于个人模型(IBM)和基于对流扩散反应(ADR)方程的模型用于鱼类库存模型。在本文中,我们提出了一种新型的鱼类库存模型,称为Sprat,用于基于人口平衡方程(PBE)的端到\ hyp {}结合IBMS和ADR模型的优势,同时避免其主要缺点的同时,结合了IBMS和ADR模型的优势。 Sprat通过从个人的角度描述模型的生态系统过程来实现这一目标,同时仍基于部分微分方程。我们将SPRAT模型应用于1990年代从以COD为主的到鲱鱼主导的生态系统上观察到的有据可查的政权转移。模型模拟能够将观察到的多嗜动力学与捕捞压力和水温的记录变化进行调和,然后是捕食者捕集的逆转,可能阻碍了枯竭的鳕鱼库存的回收率。我们得出的结论是,我们的模型可用于产生有关空间相互作用的鱼类种群的新假设和测试想法,以及它们对环境和渔业强迫的共同反应。

To successfully manage marine fisheries using an ecosystem-based approach, long-term predictions of fish stock development considering changing environmental conditions are necessary. Such predictions can be provided by end-to-end ecosystem models, which couple existing physical and biogeochemical ocean models with newly developed spatially-explicit fish stock models. Typically, Individual-Based Models (IBMs) and models based on Advection-Diffusion-Reaction (ADR) equations are employed for the fish stock models. In this paper, we present a novel fish stock model called SPRAT for end-to\hyp{}end ecosystem modeling based on Population Balance Equations (PBEs) that combines the advantages of IBMs and ADR models while avoiding their main drawbacks. SPRAT accomplishes this by describing the modeled ecosystem processes from the perspective of individuals while still being based on partial differential equations. We apply the SPRAT model to explore a well-documented regime shift observed on the eastern Scotian Shelf in the 1990s from a cod-dominated to a herring-dominated ecosystem. Model simulations are able to reconcile the observed multitrophic dynamics with documented changes in both fishing pressure and water temperature, followed by a predator-prey reversal that may have impeded recovery of depleted cod stocks. We conclude that our model can be used to generate new hypotheses and test ideas about spatially interacting fish populations, and their joint responses to both environmental and fisheries forcing.

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