Assessing the precision of wild boar density estimations

Effective management of wild boar (Sus scrofa) populations has to be based on precise estimates local densities. The development an effective and cost-efficient technique cope with this need always represented a challenge for wildlife managers researchers. Drive counts, hunting bags, Random Encounter Model (REM) are among the most frequently used techniques, latter recently gaining wide recognition. We sought compare 3 methods in terms their suitability management, precision, effort required. Moreover, we evaluated uncertainty REM results when all sources error were considered. In our study, applied population Italian Apennines 2013. delta method assess total density basis errors associated parameters involved. Notably, tested showed consistent mean estimates, though none them reached fully satisfying levels precision purposes. Since low was mostly due high variability group-size parameter, propose simple technical improvements aimed at reducing parameter and, thus, REM. Although still further developed seems promising one both potential limited required by is particularly relevant current scenario, where funds often lacking number hunters acting as volunteers decreasing.