Estimates of maximum annual population growth rates (rm) of mammals and their application in wildlife management

P>1. The maximum annual population growth rate (r(m)) is a critical parameter in many models of wildlife dynamics and management. An important application of r(m) is the estimation of the maximum proportion of a population that can be removed to stop population growth (p). 2. When r(m) cannot be estimated in the field, one option is to estimate it from demographic data. We evaluate the use of the relationship between r(m) and female age at first reproduction (alpha), which is independent of phylogeny, to estimate r(m). We first demonstrate that the relationship between field and demographic estimates of r(m) is unbiased. We then show that the relationship provides an unbiased and simple method to estimate r(m) using data for 64 mammal species. We also show that p declines exponentially as alpha increases. 3. We use the fitted relationship to estimate annual r(m) and p for 55 mammal species in Australia and New Zealand for which there are no field estimates of r(m). The estimates differ by species but have low precision (wide 95% credible intervals CIs). Our estimate of r(m) for the Tasmanian devil Sarcophilus harrisii is high (0 center dot 6, 95% CI: 0 center dot 05-2 center dot 39) and suggests devils would become extinct if > 0 center dot 34 of the population is removed annually (e.g. by facial tumour disease). Our estimate of r(m) (0 center dot 77, 95% CI: 0 center dot 71-1 center dot 05) for brushtail possum Trichosurus vulpecula is much greater than published estimates and highlights the need for further field estimates of r(m) for the species in New Zealand. 4. Synthesis and applications. Since r(m) has not been estimated in the field for the majority of mammal species, our approach enables estimates with credible intervals for this important parameter to be obtained for any species for which female age at first reproduction is known. However, the estimates have wide 95% CIs. The estimated r(m,) and associated uncertainty can then be used in population and management models, perhaps most importantly to estimate the proportion that if removed annually would drive the population to extinction. Our approach can be used for taxa other than mammals.