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Extinction risk depends strongly on factors contributing to stochasticity

Author

Listed:
  • Brett A. Melbourne

    (University of Colorado, Boulder, Colorado 80309, USA)

  • Alan Hastings

    (University of California, Davis, California 95616, USA)

Abstract

Increased risk of extinction The risk that a natural population can become extinct is a fundamental biological process, and is central to our understanding of biodiversity and evolution. But Brett Melbourne and Alan Hastings contend that existing mathematical models of extinction risk ascribe variability in population numbers to the wrong processes. In work that combines a new mathematical theory with experimental data, they show that different kinds of random-ness in the life of an animal combine in such a way that the risk of extinction is many times higher than previously thought possible, and that estimated risks of extinction for endangered species need to be raised.

Suggested Citation

  • Brett A. Melbourne & Alan Hastings, 2008. "Extinction risk depends strongly on factors contributing to stochasticity," Nature, Nature, vol. 454(7200), pages 100-103, July.
    • Handle: RePEc:nat:nature:v:454:y:2008:i:7200:d:10.1038_nature06922
    DOI: 10.1038/nature06922
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    Cited by:

    1. Vuilleumier, Séverine & Possingham, Hugh P., 2012. "Interacting populations in heterogeneous environments," Ecological Modelling, Elsevier, vol. 228(C), pages 96-105.
    2. Méndez, Vicenç & Llopis, Isaac & Campos, Daniel & Horsthemke, Werner, 2010. "Extinction conditions for isolated populations affected by environmental stochasticity," Theoretical Population Biology, Elsevier, vol. 77(4), pages 250-256.
    3. Liu, He & Dai, Chuanjun & Yu, Hengguo & Guo, Qing & Li, Jianbing & Hao, Aimin & Kikuchi, Jun & Zhao, Min, 2023. "Dynamics of a stochastic non-autonomous phytoplankton–zooplankton system involving toxin-producing phytoplankton and impulsive perturbations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 368-386.
    4. Ponciano, José M. & Taper, Mark L. & Dennis, Brian, 2018. "Ecological change points: The strength of density dependence and the loss of history," Theoretical Population Biology, Elsevier, vol. 121(C), pages 45-59.
    5. Donovan, Pierce & Springborn, Michael, 2022. "Balancing conservation and commerce: A shadow value viability approach for governing bycatch," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).
    6. Garnier, Aurelie & Darmency, Henri & Tricault, Yann & Chèvre, Anne-Marie & Lecomte, Jane, 2014. "A stochastic cellular model with uncertainty analysis to assess the risk of transgene invasion after crop-wild hybridization: Oilseed rape and wild radish as a case study," Ecological Modelling, Elsevier, vol. 276(C), pages 85-94.
    7. Sloggy, Matthew R. & Kling, David M. & Plantinga, Andrew J., 2020. "Measure twice, cut once: Optimal inventory and harvest under volume uncertainty and stochastic price dynamics," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    8. Vilenkin, Boris & Chikatunov, Vladimir I. & Pavlíček, Tomáš, 2009. "The pattern of species turnover resulting from stochastic population dynamics: The model and field data," Ecological Modelling, Elsevier, vol. 220(5), pages 657-661.
    9. Eleanor S Devenish-Nelson & Philip A Stephens & Stephen Harris & Carl Soulsbury & Shane A Richards, 2013. "Does Litter Size Variation Affect Models of Terrestrial Carnivore Extinction Risk and Management?," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    10. Charles Sims & David Finnoff & Alan Hastings & Jacob Hochard, 2017. "Listing and Delisting Thresholds under the Endangered Species Act," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 549-570.
    11. Jacob LaRiviere & David Kling & James N Sanchirico & Charles Sims & Michael Springborn, 2018. "The Treatment of Uncertainty and Learning in the Economics of Natural Resource and Environmental Management," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 92-112.
    12. Izquierdo, Salvador & Dopazo, César & Fueyo, Norberto, 2010. "Supply-cost curves for geographically distributed renewable-energy resources," Energy Policy, Elsevier, vol. 38(1), pages 667-672, January.
    13. Eriksson, A. & Elías-Wolff, F. & Mehlig, B., 2013. "Metapopulation dynamics on the brink of extinction," Theoretical Population Biology, Elsevier, vol. 83(C), pages 101-122.
    14. Ponciano, José Miguel, 2018. "A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes," Theoretical Population Biology, Elsevier, vol. 122(C), pages 128-136.
    15. Zhao, Yu & Yuan, Sanling, 2016. "Stability in distribution of a stochastic hybrid competitive Lotka–Volterra model with Lévy jumps," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 98-109.
    16. Steiner, Ulrich K. & Tuljapurkar, Shripad, 2020. "Drivers of diversity in individual life courses: Sensitivity of the population entropy of a Markov chain," Theoretical Population Biology, Elsevier, vol. 133(C), pages 159-167.
    17. Nothaaß, Dorian & Taubert, Franziska & Huth, Andreas & Clark, Adam Thomas, 2023. "Modelling species invasion using a metapopulation model with variable mortality and stochastic birth-death processes," Ecological Modelling, Elsevier, vol. 481(C).
    18. Chen, Aimin & Wang, Pei & Zhou, Tianshou & Tian, Tianhai, 2022. "Balance of positive and negative regulation for trade-off between efficiency and resilience of high-dimensional networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    19. Anna Kuparinen & Robert B O'Hara & Juha Merilä, 2008. "Probabilistic Models for Continuous Ontogenetic Transition Processes," PLOS ONE, Public Library of Science, vol. 3(11), pages 1-7, November.
    20. Erickson, Richard A. & Cox, Stephen B. & Oates, Jessica L. & Anderson, Todd A. & Salice, Christopher J. & Long, Kevin R., 2014. "A Daphnia population model that considers pesticide exposure and demographic stochasticity," Ecological Modelling, Elsevier, vol. 275(C), pages 37-47.
    21. Gledhill, Michelle & Van Kirk, Robert W., 2011. "Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)," Ecological Modelling, Elsevier, vol. 222(19), pages 3587-3597.

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