Abstract
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.
Highlights
Estimating population size and density accurately and precisely is critical for applied ecology studies and wildlife management and monitoring (Krebs 1985; Seber 1986)
The uncertainty in the badger population size in Ireland based on the Monte Carlo simulation is presented in Table 3 where the mean population estimate was 92,096 (5–95th percentile, 67,188–118,881)
The histogram of the simulated population sizes across the 100,000 stochastic iterations is presented in Fig. 1 and highlights that there is a high degree of uncertainty in the projected estimate given the input parameters
Summary
Estimating population size and density accurately and precisely is critical for applied ecology studies and wildlife management and monitoring (Krebs 1985; Seber 1986). Population estimates have been derived using direct and indirect methods, including counting setts (burrows), using field signs, mark-recapture, mark-resight, direct observation, genetic methods, removal studies, and species distributional models (Sleeman et al 2009; Byrne et al 2012b; Tuyttens et al 2001; Tuyttens et al 2001; Sadlier et al 2004; Scheppers et al 2007; Byrne et al 2014a, b; Byrne et al 2019; Jacquier et al 2021) Despite such interest and data gathering, there is still significant uncertainty associated with the population size of badgers at large scales (Byrne et al 2014a, b; Judge et al 2014; Jacquier et al 2021) and, in particular, in Ireland, where the badger population has been depressed by the culling of badgers in agricultural areas where cattle herds have broken down with bTB (O’Keeffe, 2006)
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