Emergent complexity in marine ecosystem models: When does emergence arise as models increase in complexity?

气候变化仍然是对现有海洋社区和人类利用海洋获取食物和其他服务的生存威胁。海洋生物群易受气温上升、海洋酸化和污染等其他人为压力的影响。数值模拟是预测这些因素在气候变化下将如何影响海洋生物的唯一工具。目前的模式是否符合目的？涌现属性是在自然界中观察到的连贯结构、模式、关系和物质通量，可以通过足够复杂的模型再现。然而，复杂的模型需要更多的计算资源。提交给第五次耦合模型相互比较项目的大多数模型都有相对简单的海洋生物地球化学模型，这些模型不能够产生在功能齐全的模型中看到的许多新出现的特性，尚不清楚海洋生态系统中缺乏这些新出现的特性是否会影响未来的预测。该项目旨在研究简单模型中缺乏自然属性是否会影响模型表现自然海洋生态系统行为的能力。研究方法和培训：该项目的中心是模型复杂性如何导致自然行为的出现，调查以下自然属性：-深海是世界上最大的碳库，海洋细菌可能是大气碳减少的重要贡献者。细菌行为对深海碳库有什么影响？浮游植物是海洋食物链的基础，令人难以置信的多样性，并产生大气中一半的氧气。更简单的生态系统模型是否能够产生足够准确的浮游植物介导通量的表示？浮游动物同时是食草动物、捕食者和猎物。它们群落模式的改变对浮游动物群落、浮游植物群落和碳循环有什么影响？这些问题最初将使用一维GOTM-ERSEM水柱模型进行研究，允许快速原型。最初，该模型将模拟西英吉利海峡L4站点的条件，然后测试将扩展到其他几个一维站点。一旦准备好多个一维候选模拟，学生将开始以下三维模拟之一：全球1度NEMO-ERSEM或大西洋边缘模型，其中包括东北大西洋和北海。

Climate change remains an existential threat to established marine communities and human exploitation of the oceans for food and other services. Marine biota are vulnerable to rising temperatures, ocean acidification and other anthropogenic pressures such as pollution. Numerical simulations are the only tools available to predict how these factors will influence marine life under climate change. Are the current models fit for purpose?Emergent properties are coherent structures, patterns, relationships and material fluxes that are observed in nature and can be reproduced by a sufficiently complex model. However, complex models require more computational resources. Most of the models submitted to the fifth coupled model inter-comparison project (CMIP5) had relatively simple marine biogeochemical models, which would not be capable of producing many of the emergent properties seen in a fully featured model.It is not clear whether the absence of these emergent properties in the marine ecosystem impacts future projections. This project addresses whether the absence of emergent properties in simpler models impacts the models' ability to represent natural marine ecosystem behaviour.Research methodology and training:This project centres on how model complexity leads to emergence of natural behaviour, investigating the following emergent properties:- The deep ocean is the world's largest carbon reservoir, and marine bacteria may be a significant contributor to the drawdown of atmospheric carbon. What impact does bacterial behaviour have on the deep ocean carbon reservoir?- Phytoplankton are the base of the marine food chain, incredibly diverse and produce half the oxygen in the atmosphere. Are simpler ecosystem models able to produce a sufficiently accurate representation of phytoplankton mediated fluxes?- Zooplankton are simultaneously grazers, predators and prey. What impact do changes to the model of their community have on the zooplankton community, the phytoplankton community and the carbon cycle?These questions will initially be investigated using a one dimensional GOTM-ERSEM water column model, allowing rapid prototyping. Initially, the model would simulate conditions at the L4 site in the Western English Channel, then testing would expand to several other 1D sites. Once multiple 1D candidate simulations have been prepared, the student would start one of the following three dimensional simulations: either the global 1 degree NEMO-ERSEM or the Atlantic Margin Model, which covers the North East Atlantic and North Sea.