IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-38329-4.html
   My bibliography  Save this article

Mechanistic models project bird invasions with accuracy

Author

Listed:
  • Diederik Strubbe

    (Ghent University
    University of Copenhagen)

  • Laura Jiménez

    (University of Hawai’i at Mānoa
    Universidad de Chile)

  • A. Márcia Barbosa

    (Alameda do Monte da Virgem)

  • Amy J. S. Davis

    (Ghent University
    University of Konstanz)

  • Luc Lens

    (Ghent University)

  • Carsten Rahbek

    (University of Copenhagen)

Abstract

Invasive species pose a major threat to biodiversity and inflict massive economic costs. Effective management of bio-invasions depends on reliable predictions of areas at risk of invasion, as they allow early invader detection and rapid responses. Yet, considerable uncertainty remains as to how to predict best potential invasive distribution ranges. Using a set of mainly (sub)tropical birds introduced to Europe, we show that the true extent of the geographical area at risk of invasion can accurately be determined by using ecophysiological mechanistic models that quantify species’ fundamental thermal niches. Potential invasive ranges are primarily constrained by functional traits related to body allometry and body temperature, metabolic rates, and feather insulation. Given their capacity to identify tolerable climates outside of contemporary realized species niches, mechanistic predictions are well suited for informing effective policy and management aimed at preventing the escalating impacts of invasive species.

Suggested Citation

  • Diederik Strubbe & Laura Jiménez & A. Márcia Barbosa & Amy J. S. Davis & Luc Lens & Carsten Rahbek, 2023. "Mechanistic models project bird invasions with accuracy," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38329-4
    DOI: 10.1038/s41467-023-38329-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-38329-4
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-38329-4?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
    ---><---

    References listed on IDEAS

    as
    1. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
    2. Owens, Hannah L. & Campbell, Lindsay P. & Dornak, L. Lynnette & Saupe, Erin E. & Barve, Narayani & Soberón, Jorge & Ingenloff, Kate & Lira-Noriega, Andrés & Hensz, Christopher M. & Myers, Corinne E. &, 2013. "Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas," Ecological Modelling, Elsevier, vol. 263(C), pages 10-18.
    3. Jiménez, Laura & Soberón, Jorge & Christen, J. Andrés & Soto, Desireé, 2019. "On the problem of modeling a fundamental niche from occurrence data," Ecological Modelling, Elsevier, vol. 397(C), pages 74-83.
    4. Mathias Czaika & Hein Haas, 2014. "The Globalization of Migration: Has the World Become More Migratory?," International Migration Review, Wiley Blackwell, vol. 48(2), pages 283-323, June.
    5. Trevor H. Booth, 2017. "Assessing species climatic requirements beyond the realized niche: some lessons mainly from tree species distribution modelling," Climatic Change, Springer, vol. 145(3), pages 259-271, December.
    6. Barve, Narayani & Barve, Vijay & Jiménez-Valverde, Alberto & Lira-Noriega, Andrés & Maher, Sean P. & Peterson, A. Townsend & Soberón, Jorge & Villalobos, Fabricio, 2011. "The crucial role of the accessible area in ecological niche modeling and species distribution modeling," Ecological Modelling, Elsevier, vol. 222(11), pages 1810-1819.
    7. C. Diagne & B. Leroy & Rodolphe Gozlan & A.-C. Vaissière & C. Assailly & L. Nuninger & David A Roiz & Frédéric Jourdain & I. Jarić & F. Courchamp, 2020. "InvaCost, a public database of the economic costs of biological invasions worldwide," Post-Print hal-03085161, HAL.
    8. Miguel Fernández & Healy Hamilton, 2015. "Ecological Niche Transferability Using Invasive Species as a Case Study," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    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. Lavaud, Romain & La Peyre, Megan K & Couvillion, Brady & Beseres Pollack, Jennifer & Brown, Vincent & Palmer, Terence A & Keim, Barry, 2024. "Predicting restoration and aquaculture potential of eastern oysters through an eco-physiological mechanistic model," Ecological Modelling, Elsevier, vol. 489(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. Jiménez, L. & Soberón, J., 2022. "Estimating the fundamental niche: Accounting for the uneven availability of existing climates in the calibration area," Ecological Modelling, Elsevier, vol. 464(C).
    2. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    3. Jiménez, Laura & Soberón, Jorge & Christen, J. Andrés & Soto, Desireé, 2019. "On the problem of modeling a fundamental niche from occurrence data," Ecological Modelling, Elsevier, vol. 397(C), pages 74-83.
    4. Marianna V. P. Simões & Hanieh Saeedi & Marlon E. Cobos & Angelika Brandt, 2021. "Environmental matching reveals non-uniform range-shift patterns in benthic marine Crustacea," Climatic Change, Springer, vol. 168(3), pages 1-20, October.
    5. David A. Prieto-Torres & Luis A. Sánchez-González & Marco F. Ortiz-Ramírez & Jorge E. Ramírez-Albores & Erick A. García-Trejo & Adolfo G. Navarro-Sigüenza, 2021. "Climate warming affects spatio-temporal biodiversity patterns of a highly vulnerable Neotropical avifauna," Climatic Change, Springer, vol. 165(3), pages 1-20, April.
    6. Fourcade, Yoan, 2021. "Fine-tuning niche models matters in invasion ecology. A lesson from the land planarian Obama nungara," Ecological Modelling, Elsevier, vol. 457(C).
    7. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    8. Wolke Tobón-Niedfeldt & Alicia Mastretta-Yanes & Tania Urquiza-Haas & Bárbara Goettsch & Angela P. Cuervo-Robayo & Esmeralda Urquiza-Haas & M. Andrea Orjuela-R & Francisca Acevedo Gasman & Oswaldo Oli, 2022. "Incorporating evolutionary and threat processes into crop wild relatives conservation," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    9. Ramos, Rodrigo Soares & Kumar, Lalit & Shabani, Farzin & Picanço, Marcelo Coutinho, 2019. "Risk of spread of tomato yellow leaf curl virus (TYLCV) in tomato crops under various climate change scenarios," Agricultural Systems, Elsevier, vol. 173(C), pages 524-535.
    10. Hanen Khaldi & Vicente Prado-Gascó, 2021. "Bibliometric maps and co-word analysis of the literature on international cooperation on migration," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1845-1869, October.
    11. Cristine Rauber & Francisco Cribari-Neto & Fábio M. Bayer, 2020. "Improved testing inferences for beta regressions with parametric mean link function," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 687-717, December.
    12. Ochoa-Ochoa, Leticia M. & Flores-Villela, Oscar A. & Bezaury-Creel, Juan E., 2016. "Using one vs. many, sensitivity and uncertainty analyses of species distribution models with focus on conservation area networks," Ecological Modelling, Elsevier, vol. 320(C), pages 372-382.
    13. John J. Kineman & Krupanidhi Srirama & Jennifer Wilby & Bruce T. Milne, 2017. "Elements of a Holistic Theory to Meet the Sustainability Challenge," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(5), pages 553-563, September.
    14. Kathryn M. Irvine & T. J. Rodhouse & Ilai N. Keren, 2016. "Extending Ordinal Regression with a Latent Zero-Augmented Beta Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(4), pages 619-640, December.
    15. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    16. Neli Demireva & Fabio Quassoli, 2019. "The Lived Experiences of Migration: An Introduction," Social Inclusion, Cogitatio Press, vol. 7(4), pages 1-6.
    17. Carlos Yañez-Arenas & A Townsend Peterson & Pierre Mokondoko & Octavio Rojas-Soto & Enrique Martínez-Meyer, 2014. "The Use of Ecological Niche Modeling to Infer Potential Risk Areas of Snakebite in the Mexican State of Veracruz," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
    18. Siyang Luo & Qianting Kong & Zijun Ke & Liqin Huang & Meihua Yu & Yiyi Zhu & Ying Xu, 2020. "Residential Mobility Decreases the Perception of Social Norm Violations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(3), pages 961-986, April.
    19. Ronal Reddy, 2021. "Reasons for changes of passenger perceptions of low cost carriers identified on social media - a case study on Jetstar Airways - A literature review," Technium Social Sciences Journal, Technium Science, vol. 19(1), pages 520-534, May.
    20. Arpit Deomurari & Ajay Sharma & Dipankar Ghose & Randeep Singh, 2023. "Potential Range Map Dataset of Indian Birds," Data, MDPI, vol. 8(9), pages 1-11, September.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38329-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.