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Estimating wild boar density in hunting areas by a probabilistic sampling of drive counts

Abstract

The evaluation of wild boar density in a hunting district can be performed by accurate drive counts of boars within the drive areas assigned to each hunting team. Because a complete driving of all the areas is prohibitive, only a subset is driven in a hunting occasion. Results are highly dependent on the subjective choice of these areas. In this study, an objective design-based approach is considered in which areas to be driven are randomly selected one per team in accordance with the one-per-stratum sampling scheme. Because the areas assigned to hunting teams are likely to be close to each other, the one-per-stratum sampling is likely to achieve samples of evenly spread areas. Then, the subsequent step is to choose the selection criterion for the areas and the estimation criterion for exploiting or not the information provided by area sizes. To this purpose, three sampling strategies are considered, together with methods to estimate their precision. These strategies are checked and compared by means of a simulation study performed on artificial populations constructed from the list of drive areas settled in the Province of Massa–Carrara (Italy) and partitioned among 39 hunting teams. Results from artificial populations give clear insights about the most suitable strategy to be used. Drive counts performed in this province in two hunting occasions during 2019 within 39 areas selected by one-per-stratum sampling are adopted as case studies.

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Acknowledgements

We are grateful to wild boar hunting teams of the Massa–Carrara province, who have entirely accepted the proposed scheme and carried out the data collection correctly. We also wish to thank the ATC MS13 hunting office and its president, Filippo Merlini, who shared the study and facilitated the relations with hunting teams.

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Correspondence to M. Zaccaroni.

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Handling Editor: Pierre R. L. Dutilleul

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Fattorini, L., Bongi, P., Monaco, A. et al. Estimating wild boar density in hunting areas by a probabilistic sampling of drive counts. Environ Ecol Stat 29, 393–413 (2022). https://doi.org/10.1007/s10651-021-00527-y

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  • DOI: https://doi.org/10.1007/s10651-021-00527-y

Keywords

  • Case study
  • Design-based inference
  • Horvitz–Thompson estimator
  • One-per-stratum sampling
  • Ratio estimator
  • Variance estimation
  • Simulation study