Keeping an eye on the moose population: evaluating monitoring via hunter observations

Hunter‐based monitoring programs offer a cost‐effective approach to large‐scale wildlife monitoring, but their performance depends on sufficient observation effort and robust assessment of estimate precision. We evaluated the performance of ÄlgObs, Sweden's nationwide hunter‐based moose observation program, using data from six hunting seasons (2019/2020–2024/2025) across Moose management areas (MMA). We assessed the stability and precision of estimates for relative abundance (RA), proportion of bulls (POB), and observed recruitment rate (ORR) using bootstrap‐based precision analyses across increasing cumulative observation effort. For each MMA and year, we quantified the effort required to achieve predefined coefficients of variation (CV ≤ 0.05, 0.125, 0.25, 0.5) and examined when these thresholds were reached during the hunting season. Relative abundance estimates consistently achieved acceptable precision under practical effort levels, confirming ÄlgObs as an effective tool for tracking relative abundance at large spatial scales. Although the proportion of bulls and the observed recruitment rate exhibited high variability early in the season due to sparse sampling and small denominators, bootstrap analyses showed that total seasonal effort was generally sufficient to achieve stable estimates for these metrics in most MMA–year combinations. The timing of threshold attainment varied among regions and years, with many combinations reaching acceptable precision within the first month of the hunting season. Our results demonstrate that ÄlgObs provides precise estimates of relative abundance and, under the standard effort associated with the Swedish moose hunting season, can also yield sufficiently precise estimates of population structure in most regions. However, targeted complementary methods may be required in areas with consistently low participation. Overall, ÄlgObs represents an effective model for participatory wildlife monitoring, balancing a practical cost‐effective method with results scientifically relevant to the adaptive moose management. These analyses assess the stability and precision of ÄlgObs estimates but not their accuracy, which warrants further investigation.