Ocean microbes in the petascale age: towards the billion-particle model

“全球海洋占全球初级生产力的50%左右，因此在全球碳平衡和生物地球化学循环中发挥着关键作用。海洋也是全世界人口的主要食物来源。微生物构成了这两种生态系统功能的基础，预测海洋微生物之间复杂的相互作用以及这些相互作用的结果仍然是气候和环境研究中的重大挑战之一[1,2]。由于海洋处于不断运动中，微生物生命和海洋生态系统涉及许多固有的拉格朗日过程，这些过程可以使用基于个体的模型（ibm）进行建模。与传统生态建模中使用的基于种群的方法相比，这些模型可以利用大量虚拟粒子解决拉格朗日运动驱动下微生物之间接触的精细尺度过程和复杂非线性。该项目所针对的关键生物学挑战将是将种群内和生命周期变化、快速适应/适应和微生物-微生物竞争/入侵动力学纳入拉格朗日运动IBM模型，以预测气候强迫的气候温度和洋流变化如何改变生态系统动力学。另一个有希望的途径是模拟海洋微生物物种与更高营养水平物种（如浮游动物、鱼类）的相互作用，以预测不完全混合条件和强空间变异性/斑块对食物链种群动态的影响。该项目中定量/计算创新的关键目标将是解决当前拉格朗日模型受到大量粒子所需的高计算需求严重限制的问题，这反过来又限制了预测能力。该学生将利用帝国理工学院设计的oceanpackages（包裹）软件，结合同样由ICL开发的生物性状数据库中的微生物生理学真实数据来解决这个问题。oceanpackages框架允许通过简单的高级语言以编程方式定义单个代理的行为，从而快速创建复杂的运动驱动的生态系统模型，同时通过现代计算技术（如即时（JIT）编译）利用高性能计算（HPC）资源的力量。结果将是开发一个模型，其中包含现实海洋微生物IBM所需的大量粒子-数十亿粒子，与模拟开放海洋中真实的微生物-微生物相互作用有关。现实生态行为的参数化和模型微生物的变化将通过生物性状数据来实现，这些数据涵盖了数百个物种和数千个微生物生理学的实验测量以及与微生物-微生物生活史和相互作用结果相关的其他性状。参考文献：[1]Allen等。地球系统应用的海洋生态系统模型：MarQUEST经验。海洋系统学报，2009 bbb10 Doney。海洋生物地球化学建模面临的主要挑战。全球生物地球化学循环，1999”

"The world's oceans are responsible for about 50% of the global primary productivity and therefore play a key role in the global carbon balance and bio-geochemical cycles. The oceans are also a major source of food for human populations worldwide. Microbes form the basis for both these ecosystem functions, and predicting the complex interactions between marine microbes as well as the outcomes of these interactions remains one of the grand challenges in climate and environmental research [1, 2]. Because the ocean is in constant motion, microbial life and the marine ecosystem involve many inherently Lagrangian processes that can be modelled using individual-based models (IBMs). These models, in contrast to traditional population-based methods used in ecological modelling, can resolve fine-scale processes and complex nonlinearities underlying Lagrangian movement-driven contact between microbes using large numbers of virtual particles. The key biological challenge targeted by this project will be to incorporate intra-population and life-cycle variability, rapid acclimation/adaptation and microbe-microbe competition/invasion dynamics, into the Lagrangian movement IBM model to predict how climate-forced changes in climatic temperature and oceanic currents may alter ecosystem dynamics. One promising additional avenue would be to model interactions of marine microbial species with species at higher trophic levels (e.g., zooplankton, fish) to predict effects of incomplete mixing conditions and strong spatial variability/patchiness on population dynamics in food chains.The key target for quantitative/computational innovation in this project will be to tackle the problem that current Lagrangian models are severely limited by the high computational demand arising from the large numbers of particles required, which in turn limits predictive capabilities. The student will tackle this problem by building upon the OceanPARCELS (Parcels) software designed at Imperial College London combined with real data on microbial physiology from the BioTraits database also developed at ICL. The OceanPARCELS framework allows rapid creation of complex movement-driven ecosystem models by programmatically defining the behaviour of individual agents in a simple high-level language, while utilising the power of high performance computing (HPC) resources through modern computational techniques, such as the Just-in-Time (JIT) compilation. The result will be development of a model with the vast numbers of particles required for a realistic oceanic microbial IBM --- billions of particles, relevant to modelling real microbe-microbe interactions in the open ocean. The parameterisation of realistic ecological behaviour and variation of the model microbes will be achieved through the BioTraits data, which covers hundreds of species and thousands of experimental measurements of microbial physiology and other traits relevant to microbe-microbe life history and interaction outcomes. References: [1] Allen et al. Marine ecosystem models for earth systems applications:The MarQUEST experience. Journal of Marine Systems, 2009[2] Doney. Major challenges confronting marine biogeochemical modeling. Global Biogeochemical Cycles, 1999"