IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v356y2017icp59-72.html
   My bibliography  Save this article

Simulating individual-based movement in dynamic environments

Author

Listed:
  • Watkins, Katherine Shepard
  • Rose, Kenneth A.

Abstract

The accuracy of spatially-explicit individual-based models (IBMs) often depends on the realistic simulation of the movement of organisms, which is especially challenging when movement cues (e.g., environmental conditions; prey and predator abundances) vary in time and space. A number of approaches or sub-models have been developed for simulating movement in IBMs. We evaluated four movement sub-models (restricted-area search, kinesis, event-based, and run and tumble) in a spatially-explicit cohort IBM in which the prey and predators were both dynamic (varying across cells and over time) and responsive to the dynamics of the cohort individuals. Movement, growth, and mortality were simulated every 25min for 30 12-h days (single generation) on a 2.7×2.7km2 grid with 625m2 cells, and egg production was calculated based on weight and survival of individuals at the end of 30days. We based the cohort model on small pelagic coastal fish, and the prey was based on zooplankton and the predators based on a typical piscivorous fish. Movement sub-models were calibrated with a genetic algorithm in dynamic and static versions of the prey and predator-defined environments. Prey and predator fields were fixed in the static environment; in the dynamic environment, prey density was reduced based on consumption and predators actively sought out cohort individuals. Static-trained sub-models were then tested in the dynamic environments and vice versa. The four movement sub-models were successfully trained and performed reasonably well in terms of egg production (a measure of individual fitness) when trained and tested in the same type of environment. However, the type of environment affected calibration success, and static-trained models did not perform well when tested in dynamic environments because cohort individuals moved in response to both prey and predator cues rather than primarily avoiding fixed-in-space high mortality cells. Use of movement sub-models in IBMs should carefully consider how the conditions assumed for calibration relates to the dynamic conditions the model will be used to address.

Suggested Citation

  • Watkins, Katherine Shepard & Rose, Kenneth A., 2017. "Simulating individual-based movement in dynamic environments," Ecological Modelling, Elsevier, vol. 356(C), pages 59-72.
  • Handle: RePEc:eee:ecomod:v:356:y:2017:i:c:p:59-72
    DOI: 10.1016/j.ecolmodel.2017.03.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380016307888
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2017.03.025?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. Watkins, Katherine Shepard & Rose, Kenneth A., 2013. "Evaluating the performance of individual-based animal movement models in novel environments," Ecological Modelling, Elsevier, vol. 250(C), pages 214-234.
    2. Okunishi, Takeshi & Yamanaka, Yasuhiro & Ito, Shin-ichi, 2009. "A simulation model for Japanese sardine (Sardinops melanostictus) migrations in the western North Pacific," Ecological Modelling, Elsevier, vol. 220(4), pages 462-479.
    3. Campbell, Matthew D. & Rose, Kenneth & Boswell, Kevin & Cowan, James, 2011. "Individual-based modeling of an artificial reef fish community: Effects of habitat quantity and degree of refuge," Ecological Modelling, Elsevier, vol. 222(23), pages 3895-3909.
    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. Watson, Joseph W & Boyd, Robin & Dutta, Ritabrata & Vasdekis, Georgios & Walker, Nicola D. & Roy, Shovonlal & Everitt, Richard & Hyder, Kieran & Sibly, Richard M, 2022. "Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass✰," Ecological Modelling, Elsevier, vol. 466(C).
    2. Morrice, Katherine J. & Baptista, António M. & Burke, Brian J., 2020. "Environmental and behavioral controls on juvenile Chinook salmon migration pathways in the Columbia River estuary," Ecological Modelling, Elsevier, vol. 427(C).
    3. Walker, Nicola D. & Boyd, Robin & Watson, Joseph & Kotz, Max & Radford, Zachary & Readdy, Lisa & Sibly, Richard & Roy, Shovonlal & Hyder, Kieran, 2020. "A spatially explicit individual-based model to support management of commercial and recreational fisheries for European sea bass Dicentrarchus labrax," Ecological Modelling, Elsevier, vol. 431(C).

    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. Politikos, Dimitrios V. & Huret, Martin & Petitgas, Pierre, 2015. "A coupled movement and bioenergetics model to explore the spawning migration of anchovy in the Bay of Biscay," Ecological Modelling, Elsevier, vol. 313(C), pages 212-222.
    2. Watkins, Katherine Shepard & Rose, Kenneth A., 2013. "Evaluating the performance of individual-based animal movement models in novel environments," Ecological Modelling, Elsevier, vol. 250(C), pages 214-234.
    3. McLane, Adam J. & Semeniuk, Christina & McDermid, Gregory J. & Marceau, Danielle J., 2011. "The role of agent-based models in wildlife ecology and management," Ecological Modelling, Elsevier, vol. 222(8), pages 1544-1556.
    4. Fulford, R.S. & Peterson, M.S. & Wu, W. & Grammer, P.O., 2014. "An ecological model of the habitat mosaic in estuarine nursery areas: Part II—Projecting effects of sea level rise on fish production," Ecological Modelling, Elsevier, vol. 273(C), pages 96-108.
    5. Roa-Ureta, Ruben H. & Santos, Miguel N. & Leitão, Francisco, 2019. "Modelling long-term fisheries data to resolve the attraction versus production dilemma of artificial reefs," Ecological Modelling, Elsevier, vol. 407(C), pages 1-1.
    6. Takeshi Okunishi & Shin-ichi Ito & Taketo Hashioka & Takashi Sakamoto & Naoki Yoshie & Hiroshi Sumata & Yumiko Yara & Naosuke Okada & Yasuhiro Yamanaka, 2012. "Impacts of climate change on growth, migration and recruitment success of Japanese sardine (Sardinops melanostictus) in the western North Pacific," Climatic Change, Springer, vol. 115(3), pages 485-503, December.
    7. Kakehi, Shigeho & Abo, Jun-ichi & Miyamoto, Hiroomi & Fuji, Taiki & Watanabe, Kazuyoshi & Yamashita, Hideyuki & Suyama, Satoshi, 2020. "Forecasting Pacific saury (Cololabis saira) fishing grounds off Japan using a migration model driven by an ocean circulation model," Ecological Modelling, Elsevier, vol. 431(C).
    8. Xu, Yi & Chai, Fei & Rose, Kenneth A. & Ñiquen C., Miguel & Chavez, Francisco P., 2013. "Environmental influences on the interannual variation and spatial distribution of Peruvian anchovy (Engraulis ringens) population dynamics from 1991 to 2007: A three-dimensional modeling study," Ecological Modelling, Elsevier, vol. 264(C), pages 64-82.
    9. Morrice, Katherine J. & Baptista, António M. & Burke, Brian J., 2020. "Environmental and behavioral controls on juvenile Chinook salmon migration pathways in the Columbia River estuary," Ecological Modelling, Elsevier, vol. 427(C).
    10. Hamza, Faseela & M, Anju & Valsala, Vinu & R, Smitha B., 2021. "A bioenergetics model for seasonal growth of Indian oil sardine (Sardinella longiceps) in the Indian west coast," Ecological Modelling, Elsevier, vol. 456(C).
    11. Athanasios Gkanasos & Stylianos Somarakis & Kostas Tsiaras & Dimitrios Kleftogiannis & Marianna Giannoulaki & Eudoxia Schismenou & Sarantis Sofianos & George Triantafyllou, 2019. "Development, application and evaluation of a 1-D full life cycle anchovy and sardine model for the North Aegean Sea (Eastern Mediterranean)," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-24, August.
    12. Pata, Patrick R. & Yñiguez, Aletta T. & Deauna, Josephine Dianne L. & De Guzman, Asuncion B. & Jimenez, Cesaria R. & Rosario, Roselle T. Borja-Del & Villanoy, Cesar L., 2021. "Insights into the environmental conditions contributing to variability in the larval recruitment of the tropical sardine Sardinella lemuru," Ecological Modelling, Elsevier, vol. 451(C).
    13. Chloe Bracis & Eliezer Gurarie & Bram Van Moorter & R Andrew Goodwin, 2015. "Memory Effects on Movement Behavior in Animal Foraging," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.

    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:356:y:2017:i:c:p:59-72. 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.