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Estimating wolf (Canis lupus) population size from number of packs and an individual based model

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  • Chapron, Guillaume
  • Wikenros, Camilla
  • Liberg, Olof
  • Wabakken, Petter
  • Flagstad, Øystein
  • Milleret, Cyril
  • Månsson, Johan
  • Svensson, Linn
  • Zimmermann, Barbara
  • Åkesson, Mikael
  • Sand, Håkan

Abstract

Estimating wildlife population size is fundamental for wildlife management and conservation. However, making monitoring of population size less resource demanding while still keeping a high monitoring accuracy and precision remains a recurrent challenge. One proposed alternative to count individuals is to instead focus on counting a segment of the population that is easier to monitor but at the same time well informative on total population size. We show how total population size can be estimated from group counts by using an individual-based population model in a social living species. We developed a wolf (Canis lupus) specific Individual Based Model and used Approximate Bayesian Computation (ABC) to fit this population model to the time series of annual number of packs, reproductions and pairs obtained from Scandinavian monitoring data. Model informative priors were obtained with data from collared individuals by the Scandinavian wolf research project. The fitted model was then used to estimate a conversion factor from number of packs to total number of individuals and to number of reproductions. There was a good fit between the retained simulations by ABC and the observed Scandinavian wolf population trajectory. The fitted simulations returned a conversion factor of 8.0 (95% CI=6.62–10.07) from number of packs to total population size and of 1.0 (95% CI=0.93–1.12) to number of reproductions in December. A sensitivity analysis revealed that the conversion factor from packs to total population size was positively correlated with pup survival and litter size and negatively correlated with subadult, vagrant and adult survivals. Using an individual based model allowed us to model the full complexity of demographic traits of a social-living species such as the wolf. The flexibility of the model also meant that the conversion factor could be estimated for any month during the year. Our approach to estimate total population size from counts of groups requires having a population model where both individuals and groups are explicitly described and can be applied to other wolf populations and group-living species where counting all individuals over a large area is unfeasible.

Suggested Citation

  • Chapron, Guillaume & Wikenros, Camilla & Liberg, Olof & Wabakken, Petter & Flagstad, Øystein & Milleret, Cyril & Månsson, Johan & Svensson, Linn & Zimmermann, Barbara & Åkesson, Mikael & Sand, Håkan, 2016. "Estimating wolf (Canis lupus) population size from number of packs and an individual based model," Ecological Modelling, Elsevier, vol. 339(C), pages 33-44.
    • Handle: RePEc:eee:ecomod:v:339:y:2016:i:c:p:33-44
    DOI: 10.1016/j.ecolmodel.2016.08.012
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    References listed on IDEAS

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    1. Mikael Sunnåker & Alberto Giovanni Busetto & Elina Numminen & Jukka Corander & Matthieu Foll & Christophe Dessimoz, 2013. "Approximate Bayesian Computation," PLOS Computational Biology, Public Library of Science, vol. 9(1), pages 1-10, January.
    2. van der Vaart, Elske & Beaumont, Mark A. & Johnston, Alice S.A. & Sibly, Richard M., 2015. "Calibration and evaluation of individual-based models using Approximate Bayesian Computation," Ecological Modelling, Elsevier, vol. 312(C), pages 182-190.
    3. Carter, Neil & Levin, Simon & Barlow, Adam & Grimm, Volker, 2015. "Modeling tiger population and territory dynamics using an agent-based approach," Ecological Modelling, Elsevier, vol. 312(C), pages 347-362.
    4. Lagarrigues, Guillaume & Jabot, Franck & Lafond, Valentine & Courbaud, Benoit, 2015. "Approximate Bayesian computation to recalibrate individual-based models with population data: Illustration with a forest simulation model," Ecological Modelling, Elsevier, vol. 306(C), pages 278-286.
    5. Marescot, Lucile & Gimenez, Olivier & Duchamp, Christophe & Marboutin, Eric & Chapron, Guillaume, 2012. "Reducing matrix population models with application to social animal species," Ecological Modelling, Elsevier, vol. 232(C), pages 91-96.
    6. Stenglein, Jennifer L. & Gilbert, Jonathan H. & Wydeven, Adrian P. & Van Deelen, Timothy R., 2015. "An individual-based model for southern Lake Superior wolves: A tool to explore the effect of human-caused mortality on a landscape of risk," Ecological Modelling, Elsevier, vol. 302(C), pages 13-24.
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    1. Van Buskirk, Amanda N. & Rosenberry, Christopher S. & Wallingford, Bret D. & Domoto, Emily Just & McDill, Marc E. & Drohan, Patrick J. & Diefenbach, Duane R., 2021. "Modeling how to achieve localized areas of reduced white-tailed deer density," Ecological Modelling, Elsevier, vol. 442(C).
    2. Bauduin, Sarah & Grente, Oksana & Santostasi, Nina Luisa & Ciucci, Paolo & Duchamp, Christophe & Gimenez, Olivier, 2020. "An individual-based model to explore the impacts of lesser-known social dynamics on wolf populations," Ecological Modelling, Elsevier, vol. 433(C).

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