IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v415y2020ics0304380019303667.html
   My bibliography  Save this article

Converging approaches for modeling the dispersal of propagules in air and sea

Author

Listed:
  • Lett, Christophe
  • Barrier, Nicolas
  • Bahlali, Meissam

Abstract

Terrestrial plants seeds, spores and pollen are often dispersed by wind. Likewise, most eggs and larvae of marine organisms are dispersed by oceanic currents. It was historically believed that the spatial scale at which dispersal occurs was orders of magnitude smaller for plants than for fish. However, recent empirical estimates of seed and larval dispersal suggest that these dispersal scales are more alike than previously thought. The modeling approaches used to simulate aerial and aquatic dispersal are also converging. Similar biophysical models are developed, in which outputs of Eulerian models simulating the main physical forcing mechanism (wind or currents) are used as inputs to Lagrangian models that include biological components (such as seed terminal velocity or larval vertical migration). These biophysical models are then used to simulate trajectories of the biological entities (seeds, larvae) in three dimensions. We reflect on these converging trends by first putting them into an historical perspective, and then by comparing the physical and biological processes represented in marine larva vs. terrestrial seed dispersal models, the data used for the models output corroboration, and the tools available to perform simulations. We conclude that this convergence offers the opportunity to bridge the gap between two scientific communities which are currently largely disconnected. More broadly, we also see our comparison across systems as a useful way to strengthen the links between aquatic and terrestrial ecology by sharing knowledge, methods, tools, and concepts.

Suggested Citation

  • Lett, Christophe & Barrier, Nicolas & Bahlali, Meissam, 2020. "Converging approaches for modeling the dispersal of propagules in air and sea," Ecological Modelling, Elsevier, vol. 415(C).
  • Handle: RePEc:eee:ecomod:v:415:y:2020:i:c:s0304380019303667
    DOI: 10.1016/j.ecolmodel.2019.108858
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380019303667
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2019.108858?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. Thomas, Christopher J. & Lambrechts, Jonathan & Wolanski, Eric & Traag, Vincent A. & Blondel, Vincent D. & Deleersnijder, Eric & Hanert, Emmanuel, 2014. "Numerical modelling and graph theory tools to study ecological connectivity in the Great Barrier Reef," Ecological Modelling, Elsevier, vol. 272(C), pages 160-174.
    2. Augusiak, Jacqueline & Van den Brink, Paul J. & Grimm, Volker, 2014. "Merging validation and evaluation of ecological models to ‘evaludation’: A review of terminology and a practical approach," Ecological Modelling, Elsevier, vol. 280(C), pages 117-128.
    3. Trakhtenbrot, A. & Katul, G.G. & Nathan, R., 2014. "Mechanistic modeling of seed dispersal by wind over hilly terrain," Ecological Modelling, Elsevier, vol. 274(C), pages 29-40.
    4. Ran Nathan & Gabriel G. Katul & Henry S. Horn & Suvi M. Thomas & Ram Oren & Roni Avissar & Stephen W. Pacala & Simon A. Levin, 2002. "Mechanisms of long-distance dispersal of seeds by wind," Nature, Nature, vol. 418(6896), pages 409-413, July.
    5. Maria Klein & Sara Teixeira & Jorge Assis & Ester A Serrão & Emanuel J Gonçalves & Rita Borges, 2016. "High Interannual Variability in Connectivity and Genetic Pool of a Temperate Clingfish Matches Oceanographic Transport Predictions," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-21, December.
    6. Willis, Jay, 2011. "Modelling swimming aquatic animals in hydrodynamic models," Ecological Modelling, Elsevier, vol. 222(23), pages 3869-3887.
    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. Térence Legrand & Anne Chenuil & Enrico Ser-Giacomi & Sophie Arnaud-Haond & Nicolas Bierne & Vincent Rossi, 2022. "Spatial coalescent connectivity through multi-generation dispersal modelling predicts gene flow across marine phyla," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

    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. Grimm, Volker & Berger, Uta, 2016. "Robustness analysis: Deconstructing computational models for ecological theory and applications," Ecological Modelling, Elsevier, vol. 326(C), pages 162-167.
    2. Ahmed Laatabi & Nicolas Marilleau & Tri Nguyen-Huu & Hassan Hbid & Mohamed Ait Babram, 2018. "ODD+2D: An ODD Based Protocol for Mapping Data to Empirical ABMs," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(2), pages 1-9.
    3. Xiaolan Wu & Xiaoyan Bu & Suocheng Dong & Yushuang Ma & Yan Ma & Yarong Ma & Yulian Liu & Haixian Wang & Xiaomin Wang & Jiarui Wang, 2023. "The Impact of Restoration and Protection Based on Sustainable Development Goals on Urban Wetland Health: A Case of Yinchuan Plain Urban Wetland Ecosystem, Ningxia, China," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    4. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    5. Honkaniemi, Juha & Ojansuu, Risto & Kasanen, Risto & Heliövaara, Kari, 2018. "Interaction of disturbance agents on Norway spruce: A mechanistic model of bark beetle dynamics integrated in simulation framework WINDROT," Ecological Modelling, Elsevier, vol. 388(C), pages 45-60.
    6. Kjelland, Michael E. & Piercy, Candice D. & Swannack, Todd M., 2017. "Beyond graphs and tables: Enhancing explanatory power of complex environmental simulations through 3D printed model output," Ecological Modelling, Elsevier, vol. 360(C), pages 244-251.
    7. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    8. MacPherson, Brian & Gras, Robin, 2016. "Individual-based ecological models: Adjunctive tools or experimental systems?," Ecological Modelling, Elsevier, vol. 323(C), pages 106-114.
    9. Singer, Alexander & Johst, Karin & Banitz, Thomas & Fowler, Mike S. & Groeneveld, Jürgen & Gutiérrez, Alvaro G. & Hartig, Florian & Krug, Rainer M. & Liess, Matthias & Matlack, Glenn & Meyer, Katrin M, 2016. "Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions?," Ecological Modelling, Elsevier, vol. 326(C), pages 63-74.
    10. Enock O. Menge & Michael J. Lawes, 2023. "Influence of Landscape Characteristics on Wind Dispersal Efficiency of Calotropis procera," Land, MDPI, vol. 12(3), pages 1-25, February.
    11. Quérou, Nicolas & Tomini, Agnes & Costello, Christopher, 2022. "Limited‐tenure concessions for collective goods," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    12. Trakhtenbrot, A. & Katul, G.G. & Nathan, R., 2014. "Mechanistic modeling of seed dispersal by wind over hilly terrain," Ecological Modelling, Elsevier, vol. 274(C), pages 29-40.
    13. Kuparinen, Anna & Schurr, Frank M., 2007. "A flexible modelling framework linking the spatio-temporal dynamics of plant genotypes and populations: Application to gene flow from transgenic forests," Ecological Modelling, Elsevier, vol. 202(3), pages 476-486.
    14. Crouse, Kristin N. & Desai, Nisarg P. & Cassidy, Kira A. & Stahler, Erin E. & Lehman, Clarence L. & Wilson, Michael L., 2022. "Larger territories reduce mortality risk for chimpanzees, wolves, and agents: Multiple lines of evidence in a model validation framework," Ecological Modelling, Elsevier, vol. 471(C).
    15. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    16. Kevin E Jablonski & Randall B Boone & Paul J Meiman, 2018. "An agent-based model of cattle grazing toxic Geyer's larkspur," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-22, March.
    17. Huber, Nica & Bugmann, Harald & Lafond, Valentine, 2018. "Global sensitivity analysis of a dynamic vegetation model: Model sensitivity depends on successional time, climate and competitive interactions," Ecological Modelling, Elsevier, vol. 368(C), pages 377-390.
    18. Costello, Christopher & Quérou, Nicolas & Tomini, Agnes, 2017. "Private eradication of mobile public bads," European Economic Review, Elsevier, vol. 94(C), pages 23-44.
    19. Reynolds, A.M., 2012. "Gusts within plant canopies are extreme value processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5059-5063.
    20. McLane, Adam J. & Semeniuk, Christina & McDermid, Gregory J. & Tomback, Diana F. & Lorenz, Teresa & Marceau, Danielle, 2017. "Energetic behavioural-strategy prioritization of Clark’s nutcrackers in whitebark pine communities: An agent-based modeling approach," Ecological Modelling, Elsevier, vol. 354(C), pages 123-139.

    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:415:y:2020:i:c:s0304380019303667. 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.