IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v370y2018icp14-21.html
   My bibliography  Save this article

Dome-shaped transition between positive and negative interactions maintains higher persistence and biomass in more complex ecological networks

Author

Listed:
  • Yan, Chuan
  • Zhang, Zhibin

Abstract

Positive relationship between diversity and biomass was often observed by empirical experiments at the community level, but the effects of species interactions on community total biomass have been rarely explored from a network perspective. Weak interaction and specific non-monotonic interactions have been proposed to be stabilizing mechanisms in maintaining persistence in more complex ecosystems, but it is unclear how they contribute to the high level of biomass or productivity of these systems. In this study, we examined the effects of various interactions, specifically dome-shaped (shifting from positive to negative effect with increase of density) and satiated interactions, on biomass and biomass flow with the increase of complexity in theoretical networks. Our results indicated that, as compared to linear or satiated interactions, dome-shaped interactions maintained both higher persistence and biomass or biomass flow in more complex networks, but resulted in larger variations of species biomass. However, variation of network biomass was much smaller than that of species biomass. Our results suggest that species interaction shifting between mutualism at low density and competition or predation at high density could be a driving force for maintaining high levels of persistence, diversity, biomass and biomass flow in natural ecosystems.

Suggested Citation

  • Yan, Chuan & Zhang, Zhibin, 2018. "Dome-shaped transition between positive and negative interactions maintains higher persistence and biomass in more complex ecological networks," Ecological Modelling, Elsevier, vol. 370(C), pages 14-21.
    • Handle: RePEc:eee:ecomod:v:370:y:2018:i:c:p:14-21
    DOI: 10.1016/j.ecolmodel.2018.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380018300139
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2018.01.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Zhibin & Yan, Chuan & Krebs, Charles J. & Stenseth, Nils Chr., 2015. "Ecological non-monotonicity and its effects on complexity and stability of populations, communities and ecosystems," Ecological Modelling, Elsevier, vol. 312(C), pages 374-384.
    2. Soetaert, Karline & Petzoldt, Thomas & Setzer, R. Woodrow, 2010. "Solving Differential Equations in R: Package deSolve," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i09).
    3. Stefano Allesina & Si Tang, 2012. "Stability criteria for complex ecosystems," Nature, Nature, vol. 483(7388), pages 205-208, March.
    4. Michel Loreau & Andy Hector, 2001. "Partitioning selection and complementarity in biodiversity experiments," Nature, Nature, vol. 412(6842), pages 72-76, July.
    5. Kevin McCann & Alan Hastings & Gary R. Huxel, 1998. "Weak trophic interactions and the balance of nature," Nature, Nature, vol. 395(6704), pages 794-798, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chun-Wei Chang & Takeshi Miki & Hao Ye & Sami Souissi & Rita Adrian & Orlane Anneville & Helen Agasild & Syuhei Ban & Yaron Be’eri-Shlevin & Yin-Ru Chiang & Heidrun Feuchtmayr & Gideon Gal & Satoshi I, 2022. "Causal networks of phytoplankton diversity and biomass are modulated by environmental context," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Torres-Alruiz, Maria Daniela & Rodríguez, Diego J., 2013. "A topo-dynamical perspective to evaluate indirect interactions in trophic webs: New indexes," Ecological Modelling, Elsevier, vol. 250(C), pages 363-369.
    3. Chang, Feng-Hsun & Ke, Po-Ju & Cardinale, Bradley, 2020. "Weak intra-guild predation facilitates consumer coexistence but does not guarantee higher consumer density," Ecological Modelling, Elsevier, vol. 424(C).
    4. Zhang, Zhibin & Yan, Chuan & Krebs, Charles J. & Stenseth, Nils Chr., 2015. "Ecological non-monotonicity and its effects on complexity and stability of populations, communities and ecosystems," Ecological Modelling, Elsevier, vol. 312(C), pages 374-384.
    5. Yuguang Yang & Katharine Z. Coyte & Kevin R. Foster & Aming Li, 2023. "Reactivity of complex communities can be more important than stability," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. González, Cecilia, 2023. "Evolution of the concept of ecological integrity and its study through networks," Ecological Modelling, Elsevier, vol. 476(C).
    7. Yan, Chuan & Zhang, Zhibin, 2016. "Interspecific interaction strength influences population density more than carrying capacity in more complex ecological networks," Ecological Modelling, Elsevier, vol. 332(C), pages 1-7.
    8. Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2020. "Crop diversity, household welfare and consumption smoothing under risk: Evidence from rural Uganda," World Development, Elsevier, vol. 125(C).
    9. Clenet, Maxime & El Ferchichi, Hafedh & Najim, Jamal, 2022. "Equilibrium in a large Lotka–Volterra system with pairwise correlated interactions," Stochastic Processes and their Applications, Elsevier, vol. 153(C), pages 423-444.
    10. Li, Fei & Kang, Hao & Xu, Jingfeng, 2022. "Financial stability and network complexity: A random matrix approach," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 177-185.
    11. Asrat, Sinafikeh & Yesuf, Mahmud & Carlsson, Fredrik & Wale, Edilegnaw, 2009. "Farmers’ Preferences for Crop Variety Traits: Lessons for On-Farm Conservation and Technology Adoption," RFF Working Paper Series dp-09-15-efd, Resources for the Future.
    12. Pachepsky, Elizaveta & Bown, James L. & Eberst, Alistair & Bausenwein, Ursula & Millard, Peter & Squire, Geoff R. & Crawford, John W., 2007. "Consequences of intraspecific variation for the structure and function of ecological communities Part 2: Linking diversity and function," Ecological Modelling, Elsevier, vol. 207(2), pages 277-285.
    13. Bastazini, Vinicius Augusto Galvão & Debastiani, Vanderlei & Cappelatti, Laura & Guimarães, Paulo & Pillar, Valério D., 2022. "The role of evolutionary modes for trait-based cascades in mutualistic networks," Ecological Modelling, Elsevier, vol. 470(C).
    14. Fatima-Zahra Jaouimaa & Daniel Dempsey & Suzanne Van Osch & Stephen Kinsella & Kevin Burke & Jason Wyse & James Sweeney, 2021. "An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-25, December.
    15. Dai, Chuanjun & Zhao, Min & Chen, Lansun, 2012. "Complex dynamic behavior of three-species ecological model with impulse perturbations and seasonal disturbances," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 84(C), pages 83-97.
    16. Di Falco, Salvatore & Bezabih, Mintewab & Yesuf, Mahmud, 2010. "Seeds for livelihood: Crop biodiversity and food production in Ethiopia," Ecological Economics, Elsevier, vol. 69(8), pages 1695-1702, June.
    17. George Van Voorn & Geerten Hengeveld & Jan Verhagen, 2020. "An agent based model representation to assess resilience and efficiency of food supply chains," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-27, November.
    18. Overstall, Antony M. & Woods, David C. & Martin, Kieran J., 2019. "Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 126-142.
    19. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).
    20. Dina in ‘t Zandt & Zuzana Kolaříková & Tomáš Cajthaml & Zuzana Münzbergová, 2023. "Plant community stability is associated with a decoupling of prokaryote and fungal soil networks," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:370:y:2018:i:c:p:14-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.