IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v312y2015icp374-384.html

Some searches may not work properly. We apologize for the inconvenience.

   My bibliography  Save this article

Ecological non-monotonicity and its effects on complexity and stability of populations, communities and ecosystems

Author

Listed:
  • Zhang, Zhibin
  • Yan, Chuan
  • Krebs, Charles J.
  • Stenseth, Nils Chr.

Abstract

In traditional ecological models, the effects of abiotic and biotic factors are often assumed to be monotonic, i.e. either positive, negative or neutral. However, there has been growing evidence that non-monotonic effects of environmental factors and both intra- and inter-specific interactions can significantly influence the dynamics and stability of populations, communities and ecosystems. In this paper, we present a review and synthesis on both theoretical and empirical studies on ecological non-monotonicity. There are various non-monotonic relations observed in populations, communities and ecosystems. The non-monotonic function of per capita population increase rate against intrinsic or extrinsic factors is a significant driving force in determining the complexity and stability of biological systems. There are several mechanisms such as the law of tolerance, adaptive behaviors, or opposing dual or pathway effects which may result in non-monotonic functions. Ecological non-monotonic functions are often closely related to spatial and temporal scale processes which may explain why ecosystems are often highly variable and unpredictable in both space and time. Recognizing ecological non-monotonicity would greatly change our conventional monotonic views on the effects of environmental factors and species interactions on ecosystems. We appeal for more effort to study ecological non-monotonicity and re-think our strategies to manage ecosystems under accelerated global change.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecomod:v:312:y:2015:i:c:p:374-384
    DOI: 10.1016/j.ecolmodel.2015.06.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380015002537
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2015.06.004?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. K. S. Chan & H. Tong, 1986. "On Estimating Thresholds In Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 179-190, May.
    2. Chao Wang & Xiaobo Wang & Dongwei Liu & Honghui Wu & Xiaotao Lü & Yunting Fang & Weixin Cheng & Wentao Luo & Ping Jiang & Jason Shi & Huaqun Yin & Jizhong Zhou & Xingguo Han & Edith Bai, 2014. "Aridity threshold in controlling ecosystem nitrogen cycling in arid and semi-arid grasslands," Nature Communications, Nature, vol. 5(1), pages 1-8, December.
    3. Anje-Margriet Neutel & Johan A. P. Heesterbeek & Johan van de Koppel & Guido Hoenderboom & An Vos & Coen Kaldeway & Frank Berendse & Peter C. de Ruiter, 2007. "Reconciling complexity with stability in naturally assembling food webs," Nature, Nature, vol. 449(7162), pages 599-602, October.
    4. E. L. Berlow, 1999. "Strong effects of weak interactions in ecological communities," Nature, Nature, vol. 398(6725), pages 330-334, March.
    5. Stefano Allesina & Si Tang, 2012. "Stability criteria for complex ecosystems," Nature, Nature, vol. 483(7388), pages 205-208, March.
    6. 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.
    7. Kyrre L. Kausrud & Atle Mysterud & Harald Steen & Jon Olav Vik & Eivind Østbye & Bernard Cazelles & Erik Framstad & Anne Maria Eikeset & Ivar Mysterud & Torstein Solhøy & Nils Chr. Stenseth, 2008. "Linking climate change to lemming cycles," Nature, Nature, vol. 456(7218), pages 93-97, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xiaojun & Li, Baohuan, 2024. "Information sharing promotes bacterial diversity in oligotrophic environment with low-dose X-ray radiation based on modeling and simulation of agent-based model," Ecological Modelling, Elsevier, vol. 488(C).
    2. Roy, Trina & Ghosh, Sinchan & Bhattacharya, Sabyasachi, 2022. "A new growth curve model portraying the stress response regulation of fish: Illustration through particle motion and real data," Ecological Modelling, Elsevier, vol. 470(C).
    3. 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.

    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. 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.
    2. Scotti, Marco & Bondavalli, Cristina & Bodini, Antonio, 2009. "Linking trophic positions and flow structure constraints in ecological networks: Energy transfer efficiency or topology effect?," Ecological Modelling, Elsevier, vol. 220(21), pages 3070-3080.
    3. 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.
    4. Wang, Shuran Cindy & Liu, Xueqin & Liu, Yong & Wang, Hongzhu, 2020. "Benthic-pelagic coupling in lake energetic food webs," Ecological Modelling, Elsevier, vol. 417(C).
    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. Jennifer M Fraterrigo & Aaron B Langille & James A Rusak, 2020. "Stochastic disturbance regimes alter patterns of ecosystem variability and recovery," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    8. Frossard, Victor & Rimet, Frédéric & Perga, Marie-Elodie, 2018. "Causal networks reveal the dominance of bottom-up interactions in large, deep lakes," Ecological Modelling, Elsevier, vol. 368(C), pages 136-146.
    9. 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.
    10. van Dijk, Dick & Hans Franses, Philip & Peter Boswijk, H., 2007. "Absorption of shocks in nonlinear autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4206-4226, May.
    11. Chunming Li & Jianshe Chen & Xiaolin Liao & Aaron P. Ramus & Christine Angelini & Lingli Liu & Brian R. Silliman & Mark D. Bertness & Qiang He, 2023. "Shorebirds-driven trophic cascade helps restore coastal wetland multifunctionality," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    12. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Liebscher, Eckhard, 2003. "Strong convergence of estimators in nonlinear autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 84(2), pages 247-261, February.
    14. Riera-Crichton, Daniel & Vegh, Carlos A. & Vuletin, Guillermo, 2015. "Procyclical and countercyclical fiscal multipliers: Evidence from OECD countries," Journal of International Money and Finance, Elsevier, vol. 52(C), pages 15-31.
    15. 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.
    16. 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.
    17. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    18. 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).
    19. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    20. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.

    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:312:y:2015:i:c:p:374-384. 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.