带有捕食作用的随机CKTW模型维持物种多样性的研究
Maintenance of Species Diversity by Stochastic CKTW Models with Predation
DOI: 10.12677/PM.2023.136187, PDF,    国家自然科学基金支持
作者: 王思林, 张沐涵, 王 琳:长春工业大学数学与统计学院,吉林 长春
关键词: 随机CKTW模型随机模拟算法香农熵物种多样性Stochastic CKTW Model Stochastic Simulation Algorithm Shannon Entropy Species Diversity
摘要: 在海洋生态系统中,消耗细菌种群数量的因素包括原生动物的非选择性捕食与噬菌体的裂解。本文在具有共同进化机制的随机CKTW模型基础上,引入原生动物非选择性捕食作用,建立基于个体水平的带有非选择性捕食作用的随机CKTW模型。利用随机模拟算法对种群数量有限的随机模型进行数值模拟,捕捉到丧失物种多样性的三种灭绝路径与维持物种多样性的现象,并通过模拟实验计算出这些现象发生的概率。这里使用的随机模拟算法为Gillespie算法。最后以香农熵作为物种多样性的评价指标,对两类随机模型的物种多样性进行对比分析,说明共同进化可以在一定程度上维持物种多样性。
Abstract: In Marine ecosystems, factors that deplete bacterial populations include non-selective predation by protozoa and phage lysis. In this paper, based on the stochastic CKTW model with coevolutionary mechanism, we introduce the non-selective predation of protozoa and establish the stochastic CKTW model with non-selective predation based on individual level. The stochastic simulation algorithm was used to simulate the stochastic model with limited population to capture the three extinction paths that lost species diversity and the phenomena that maintained species diversity, and the probability of occurrence is calculated by a large number of simulation experiments. The stochastic simulation algorithm used here is Gillespie algorithm. Finally, Shannon entropy was used as the evaluation index of species diversity, and the species diversity of the two stochastic models was compared and analyzed, indicating that coevolution could maintain species diversity to a certain extent.
文章引用:王思林, 张沐涵, 王琳. 带有捕食作用的随机CKTW模型维持物种多样性的研究[J]. 理论数学, 2023, 13(6): 1841-1850. https://doi.org/10.12677/PM.2023.136187

参考文献

[1] Hutchinson, G. (1961) The Paradox of Plankton. American Naturalist, 95, 137-145. [Google Scholar] [CrossRef
[2] Roy, S. and Chattopadhyay, J. (2007) Towards a Resolution of the Paradox of the Plankton: A Brief Overview of the Proposed Mechanisms. Ecological Complexity, 4, 26-33. [Google Scholar] [CrossRef
[3] Chesson, P. (2000) Mechanisms of Maintenance of Species Diversity. Annual Review of Ecology and Systematics, 31, 343-366. [Google Scholar] [CrossRef
[4] Scheffer, M., Rinaldi, S., Huisman, J. and Weissing, F.J. (2003) Why Plankton Communities Have No Equilibrium: Solutions to the Paradox. Hydrobiologia, 491, 9-18. [Google Scholar] [CrossRef
[5] Vetsigian, K., Jajoo, R., Kishony, R. and Eisen, J.A. (2011) Structure and Evolution of Streptomyces Interaction Networks in Soil and in Silico. PLoS Biology, 9, e1001184. [Google Scholar] [CrossRef] [PubMed]
[6] Thingstad, T.F., HagstrÖm, Å. and Rassoulzadegan, F. (1997) Accumulation of Degradable DOC in Surface Waters: Is It Caused by a Malfunctioning Microbialloop? Limnology & Oceanography, 42, 398-404. [Google Scholar] [CrossRef
[7] Thingstad, T. (2000) Elements of a Theory for the Mechanisms Controlling Abundance, Diversity and Biogeochemical Role of Lytic Bacterial Viruses in Aquatic Systems. Limnology and Oceanography, 45, 1320-1328. [Google Scholar] [CrossRef
[8] Ovaskainen, O. and Meerson, B. (2010) Stochastic Models of Population Extinction. Trends in Ecology & Evolution, 25, 643-652. [Google Scholar] [CrossRef] [PubMed]
[9] Omer, G. and Baruch, M. (2012) Multiple Extinction Routes in Stochastic Population Models. Physical Review E, 85, Article ID: 021140. [Google Scholar] [CrossRef
[10] Xue, C. and Goldenfeld, N. (2017) Coevolution Maintains Di-versity in the Stochastic “Kill the Winner” Model. Physical Review Letters, 119, Article ID: 268101. [Google Scholar] [CrossRef
[11] Shih, H.-Y. and Goldenfeld, N. (2014) Path-integral Cal-culation for the Emergence of Rapid Evolution from Demographic Stochasticity. Physical Review E, Statistical, Non-linear, and Soft Matter Physics, 90, Article ID: 050702. [Google Scholar] [CrossRef
[12] Bohannan, B. and Lenski, R.E. (1997) Effect of Resource En-richment on a Chemostat Community of Bacteria and Bacteriophage. Ecology, 78, 2303-2315. [Google Scholar] [CrossRef
[13] Yoshida, T., et al. (2007) Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions. PLoS Biology, 5, 235-235. [Google Scholar] [CrossRef] [PubMed]
[14] Doebeli, M., Jaque, E.C. and Ispolatov, Y. (2021) Boom-Bust Population Dynamics Increase Diversity in Evolving Competitive Communities. Communications Biology, 4, 2-9. [Google Scholar] [CrossRef] [PubMed]
[15] Buckingham, L.J. and Ashby, B. (2022) Coevolutionary Theory of Hosts and Parasites. Journal of Evolutionary Biology, 35, 205-224. [Google Scholar] [CrossRef] [PubMed]
[16] Thingstad, T.F. and Lignell, R. (1997) Theoretical Models for the Control of Bacterial Growth Rate, Abundance, Diversity and Carbon Demand. Aquatic Microbial Ecology, 13, 19-27. [Google Scholar] [CrossRef
[17] Winter, C., Bouvier, T., Weinbauer, M.G., et al. (2010) Trade-Offs be-tween Competition and Defense Specialists among Unicellular Planktonic Organisms: The “Killing the Winner” Hy-pothesis Revisited. Microbiology and Molecular Biology Reviews: MMBR, 74, 42-57. [Google Scholar] [CrossRef
[18] Gillespie, D.T. (1976) A General Method for Numerically Simu-lating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics, 22, 403-434. [Google Scholar] [CrossRef
[19] Weinan, E., Li, T.J., et al. (2019) Applied Stochastic Analysis. American Mathematical Society, Providence.