Macroscale vertical power-law distribution of bacteria in dark oceans can emerge from microscale bacteria-particle interactions

IF 1.9 4区 数学 Q2 BIOLOGY Journal of Theoretical Biology Pub Date : 2024-09-29 DOI:10.1016/j.jtbi.2024.111956
Takeshi Miki , Po-Ju Ke
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Abstract

Microbes in the dark oceans are a key determinant of remineralization of sinking carbon particles. However, most marine ecosystem models overlook how microbes aggregate on particles and the microscale interactions between particle-associated microbes, making it difficult to obtain mechanistic insights on their vertical power-law decay pattern. Here, we present a spatial population model where the attachment and detachment processes of bacterial cells depend on local density of particle-associated bacteria. We show that the power-law relationship can emerge when the non-random aggregated distribution of bacteria is considered without any depth-specific environmental parameters. Furthermore, the comparison between model behavior and empirical patterns in the Pacific and Southern Ocean indicated that temperature-dependent hydrolysis rate and nutrient-dependent sinking rate of particles are key parameters to explain the regional variations of the power-law exponent. The mechanistic approach developed here provides a pathway to link micro-scale interactions between individuals to macro-scale food chain structures and carbon cycle.
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暗色海洋中细菌的宏观垂直幂律分布可以从微观的细菌-粒子相互作用中产生。
暗色海洋中的微生物是决定下沉碳颗粒再矿化的关键因素。然而,大多数海洋生态系统模型都忽略了微生物如何聚集在颗粒上以及颗粒相关微生物之间的微观相互作用,因此很难从机理上了解它们的垂直幂律衰减模式。在这里,我们提出了一个空间种群模型,其中细菌细胞的附着和脱离过程取决于颗粒相关细菌的局部密度。我们的研究表明,当考虑细菌的非随机聚集分布而不考虑任何特定深度的环境参数时,幂律关系就会出现。此外,模型行为与太平洋和南大洋经验模式的比较表明,与温度相关的水解速率和与营养物质相关的颗粒沉降速率是解释幂律指数区域变化的关键参数。本文提出的机理方法为将个体间微观尺度的相互作用与宏观尺度的食物链结构和碳循环联系起来提供了一条途径。
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来源期刊
CiteScore
4.20
自引率
5.00%
发文量
218
审稿时长
51 days
期刊介绍: The Journal of Theoretical Biology is the leading forum for theoretical perspectives that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research, including: • Brain and Neuroscience • Cancer Growth and Treatment • Cell Biology • Developmental Biology • Ecology • Evolution • Immunology, • Infectious and non-infectious Diseases, • Mathematical, Computational, Biophysical and Statistical Modeling • Microbiology, Molecular Biology, and Biochemistry • Networks and Complex Systems • Physiology • Pharmacodynamics • Animal Behavior and Game Theory Acceptable papers are those that bear significant importance on the biology per se being presented, and not on the mathematical analysis. Papers that include some data or experimental material bearing on theory will be considered, including those that contain comparative study, statistical data analysis, mathematical proof, computer simulations, experiments, field observations, or even philosophical arguments, which are all methods to support or reject theoretical ideas. However, there should be a concerted effort to make papers intelligible to biologists in the chosen field.
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