IDEAS home Printed from https://ideas.repec.org/a/plo/pbio00/2005987.html
   My bibliography  Save this article

Dissecting the null model for biological invasions: A meta-analysis of the propagule pressure effect

Author

Listed:
  • Phillip Cassey
  • Steven Delean
  • Julie L Lockwood
  • Jason S Sadowski
  • Tim M Blackburn

Abstract

A consistent determinant of the establishment success of alien species appears to be the number of individuals that are introduced to found a population (propagule pressure), yet variation in the form of this relationship has been largely unexplored. Here, we present the first quantitative systematic review of this form, using Bayesian meta-analytical methods. The relationship between propagule pressure and establishment success has been evaluated for a broad range of taxa and life histories, including invertebrates, herbaceous plants and long-lived trees, and terrestrial and aquatic vertebrates. We found a positive mean effect of propagule pressure on establishment success to be a feature of every hypothesis we tested. However, establishment success most critically depended on propagule pressures in the range of 10–100 individuals. Heterogeneity in effect size was associated primarily with different analytical approaches, with some evidence of larger effect sizes in animal rather than plant introductions. Conversely, no variation was accounted for in any analysis by the scale of study (field to global) or methodology (observational, experimental, or proxy) used. Our analyses reveal remarkable consistency in the form of the relationship between propagule pressure and alien population establishment success.Author summary: Alien species are a major contributor to human-induced global environmental change. The probability of whether or not an alien species will successfully establish in a novel environment is often related to the number of times a species is introduced and the number of individuals that are introduced each time, collectively termed ‘propagule pressure’. Despite this evidence, we don’t yet know whether this is a universal characteristic of species invasions, and the role of propagule pressure continues to be questioned. Here, we present a quantitative meta-analysis of the relationship between propagule pressure and establishment success across a broad range of species and geographies. We found that propagule pressure was consistently and positively associated with the establishment success of alien species. We conclude that propagule pressure is indeed the most consistent and strongest determinant of alien species establishment. No other factors suggested to explain establishment success can claim such universal support. Our results underpin a clear policy and management target for slowing invasion rates by reducing propagule pressure—ideally to single figures or zero—regardless of any other feature of the invasion.

Suggested Citation

  • Phillip Cassey & Steven Delean & Julie L Lockwood & Jason S Sadowski & Tim M Blackburn, 2018. "Dissecting the null model for biological invasions: A meta-analysis of the propagule pressure effect," PLOS Biology, Public Library of Science, vol. 16(4), pages 1-15, April.
  • Handle: RePEc:plo:pbio00:2005987
    DOI: 10.1371/journal.pbio.2005987
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2005987
    Download Restriction: no

    File URL: https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.2005987&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pbio.2005987?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. Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
    2. Corey J. A. Bradshaw & Boris Leroy & Céline Bellard & David Roiz & Céline Albert & Alice Fournier & Morgane Barbet-Massin & Jean-Michel Salles & Frédéric Simard & Franck Courchamp, 2016. "Massive yet grossly underestimated global costs of invasive insects," Nature Communications, Nature, vol. 7(1), pages 1-8, December.
    3. Regan Early & Bethany A. Bradley & Jeffrey S. Dukes & Joshua J. Lawler & Julian D. Olden & Dana M. Blumenthal & Patrick Gonzalez & Edwin D. Grosholz & Ines Ibañez & Luke P. Miller & Cascade J. B. Sort, 2016. "Global threats from invasive alien species in the twenty-first century and national response capacities," Nature Communications, Nature, vol. 7(1), pages 1-9, 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. Yiming Li & Tim M. Blackburn & Zexu Luo & Tianjian Song & Freyja Watters & Wenhao Li & Teng Deng & Zhenhua Luo & Yuanyi Li & Jiacong Du & Meiling Niu & Jun Zhang & Jinyu Zhang & Jiaxue Yang & Siqi Wan, 2023. "Quantifying global colonization pressures of alien vertebrates from wildlife trade," Nature Communications, Nature, vol. 14(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. Qi Cai & Yushi Cai & Yali Wen, 2018. "Spatially Differentiated Trends between Forest Pest-Induced Losses and Measures for Their Control in China," Sustainability, MDPI, vol. 11(1), pages 1-16, December.
    2. Manon Bonnet & Gérald Guédon & Marc Pondaven & Sandro Bertolino & Damien Padiolleau & Vanessa Pénisson & Francine Gastinel & Fabien Angot & Pierre-Cyril Renaud & Antonin Frémy & Olivier Pays, 2021. "Aquatic invasive alien rodents in Western France: Where do we stand today after decades of control?," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
    3. Francis,David C. & Kubinec ,Robert, 2022. "Beyond Political Connections : A Measurement Model Approach to Estimating Firm-levelPolitical Influence in 41 Economies," Policy Research Working Paper Series 10119, The World Bank.
    4. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    5. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    6. Heinrich, Torsten & Yang, Jangho & Dai, Shuanping, 2020. "Growth, development, and structural change at the firm-level: The example of the PR China," MPRA Paper 105011, University Library of Munich, Germany.
    7. van Kesteren Erik-Jan & Bergkamp Tom, 2023. "Bayesian analysis of Formula One race results: disentangling driver skill and constructor advantage," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(4), pages 273-293, December.
    8. Xin Xu & Yang Lu & Yupeng Zhou & Zhiguo Fu & Yanjie Fu & Minghao Yin, 2021. "An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks," Mathematics, MDPI, vol. 9(15), pages 1-14, July.
    9. Xiaoyue Xi & Simon E. F. Spencer & Matthew Hall & M. Kate Grabowski & Joseph Kagaayi & Oliver Ratmann & Rakai Health Sciences Program and PANGEA‐HIV, 2022. "Inferring the sources of HIV infection in Africa from deep‐sequence data with semi‐parametric Bayesian Poisson flow models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 517-540, June.
    10. Kuschnig, Nikolas, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Paper Series 318, WU Vienna University of Economics and Business.
    11. Deniz Aksoy & David Carlson, 2022. "Electoral support and militants’ targeting strategies," Journal of Peace Research, Peace Research Institute Oslo, vol. 59(2), pages 229-241, March.
    12. Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024. "Fitting item response theory models using deep learning computational frameworks," OSF Preprints tjxab, Center for Open Science.
    13. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.
    14. D. Fouskakis & G. Petrakos & I. Rotous, 2020. "A Bayesian longitudinal model for quantifying students’ preferences regarding teaching quality indicators," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 255-270, August.
    15. Joseph B. Bak-Coleman & Ian Kennedy & Morgan Wack & Andrew Beers & Joseph S. Schafer & Emma S. Spiro & Kate Starbird & Jevin D. West, 2022. "Combining interventions to reduce the spread of viral misinformation," Nature Human Behaviour, Nature, vol. 6(10), pages 1372-1380, October.
    16. Chiadmi, Ines & Traoré, Sidnoma Abdoul Aziz & Salles, Jean-Michel, 2020. "Asian tiger mosquito far from home: Assessing the impact of invasive mosquitoes on the French Mediterranean littoral," Ecological Economics, Elsevier, vol. 178(C).
    17. Jonas Moss & Riccardo De Bin, 2023. "Modelling publication bias and p‐hacking," Biometrics, The International Biometric Society, vol. 79(1), pages 319-331, March.
    18. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    19. Alka Chaudhary & Mriganka Shekhar Sarkar & Bhupendra Singh Adhikari & Gopal Singh Rawat, 2021. "Ageratina adenophora and Lantana camara in Kailash Sacred Landscape, India: Current distribution and future climatic scenarios through modeling," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-15, May.
    20. David M. Phillippo & Sofia Dias & A. E. Ades & Mark Belger & Alan Brnabic & Alexander Schacht & Daniel Saure & Zbigniew Kadziola & Nicky J. Welton, 2020. "Multilevel network meta‐regression for population‐adjusted treatment comparisons," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1189-1210, June.

    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:plo:pbio00:2005987. 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: plosbiology (email available below). General contact details of provider: https://journals.plos.org/plosbiology/ .

    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.