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Managing moose harvests by the seat of your pants

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  • Boyce, Mark S.
  • Baxter, Peter W.J.
  • Possingham, Hugh P.

Abstract

Moose populations are managed for sustainable yield balanced against costs caused by damage to forestry or agriculture and collisions with vehicles. Optimal harvests can be calculated based on a structured population model driven by data on abundance and the composition of bulls, cows, and calves obtained by aerial-survey monitoring during winter. Quotas are established by the respective government agency and licenses are issued to hunters to harvest an animal of specified age or sex during the following autumn. Because the cost of aerial monitoring is high, we use a Management Strategy Evaluation to evaluate the costs and benefits of periodic aerial surveys in the context of moose management. Our on-the-fly “seat of your pants†alternative to independent monitoring is management based solely on the kill of moose by hunters, which is usually sufficient to alert the manager to declines in moose abundance that warrant adjustments to harvest strategies. Harvests are relatively cheap to monitor; therefore, data can be obtained each year facilitating annual adjustments to quotas. Other sources of “cheap†monitoring data such as records of the number of moose seen by hunters while hunting also might be obtained, and may provide further useful insight into population abundance, structure and health. Because conservation dollars are usually limited, the high cost of aerial surveys is difficult to justify when alternative methods exist.

Suggested Citation

  • Boyce, Mark S. & Baxter, Peter W.J. & Possingham, Hugh P., 2012. "Managing moose harvests by the seat of your pants," Theoretical Population Biology, Elsevier, vol. 82(4), pages 340-347.
  • Handle: RePEc:eee:thpobi:v:82:y:2012:i:4:p:340-347
    DOI: 10.1016/j.tpb.2012.03.002
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    References listed on IDEAS

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    1. Olaussen, Jon Olaf & Skonhoft, Anders, 2011. "A cost-benefit analysis of moose harvesting in Scandinavia. A stage structured modelling approach," Resource and Energy Economics, Elsevier, vol. 33(3), pages 589-611, September.
    2. Hal Caswell, 2008. "Perturbation analysis of nonlinear matrix population models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 18(3), pages 59-116.
    3. T. H. Clutton-Brock & T. N. Coulson & E. J. Milner-Gulland & D. Thomson & H. M. Armstrong, 2002. "Sex differences in emigration and mortality affect optimal management of deer populations," Nature, Nature, vol. 415(6872), pages 633-637, February.
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    Cited by:

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    3. Lu, Yujie & Chang, Ruidong & Shabunko, Veronika & Lay Yee, Amy Tan, 2019. "The implementation of building-integrated photovoltaics in Singapore: drivers versus barriers," Energy, Elsevier, vol. 168(C), pages 400-408.

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