Estimating population size in space and time is essential for applied ecology and wildlife management purposes; however, making accurate and precise estimates at large scales is highly challenging. An example is the European badger (Meles meles), a widespread and abundant mammal in Ireland. Due to their role in the epidemiology of bovine tuberculosis, the species has been culled in agriculturally dominant landscapes with the intention of reducing spillback infection to local cattle populations. Despite several studies using different approaches having estimated badger populations at different time points and scales, there remains considerable uncertainty regarding the current population and its future trajectory. To explore this uncertainty, we use published data and expert opinion to estimate a snapshot of probable badger population size using a Monte Carlo approach, incorporating variation in three key components: social group numbers, group size, and culling efficacy. Using this approach, we estimate what the badger population in Ireland would be with/without culling, assuming a steady-state population at carrying capacity, and discuss the limitations of our current understanding. The mean estimate for the badger population size was 63,188 (5–95th percentile, 48,037–79,315). Population estimates were sensitive to the assumption of mean group size across landscape type. Assuming a cessation of culling (in favour of vaccination, for example) in agricultural areas, the mean estimated population size was 92,096 (5–95th percentile, 67,188–118,881). Despite significant research being conducted on badgers, estimates on population size at a national level in Ireland are only approximate, which is reflected in the large uncertainty in the estimates from this study and inconsistencies between recording of data parameters in previous studies. Focusing on carefully estimating group size, factors impacting its variation, in addition to understanding the dynamics of repopulation post-culling, could be a fruitful component to concentrate on to improve the precision of future estimates.

在空间和时间上估计种群规模对于应用生态学和野生动物管理目的至关重要；然而，在大规模范围内进行准确和精确的估计非常具有挑战性。一个例子是欧洲獾（Meles meles)，一种在爱尔兰分布广泛且数量丰富的哺乳动物。由于它们在牛结核病流行病学中的作用，该物种已在农业占主导地位的景观中被淘汰，目的是减少对当地牛群的溢出感染。尽管有几项研究使用不同的方法估计了不同时间点和尺度的獾种群，但关于当前种群及其未来轨迹仍然存在相当大的不确定性。为了探索这种不确定性，我们使用已发布的数据和专家意见，使用蒙特卡罗方法估计可能的獾种群规模的快照，结合三个关键组成部分的变化：社会群体数量、群体规模和剔除效率。使用这种方法，我们估计爱尔兰的獾种群数量有/没有剔除，假设承载能力为稳态人口，并讨论我们目前理解的局限性。獾种群规模的平均估计值为 63,188（第 5-95 个百分位数，48,037-79,315）。人口估计对跨景观类型的平均群体规模的假设很敏感。假设农业地区停止扑杀（例如，有利于接种疫苗），平均估计人口规模为 92,096（第 5-95 个百分位，67,188-118,881）。尽管对獾进行了大量研究，但对爱尔兰国家级人口规模的估计只是近似值，这反映在本研究估计的巨大不确定性以及先前研究中记录的数据参数之间的不一致上。专注于仔细估计群体规模，影响其变化的因素，