title: Data-poor management of African lion hunting using a relative index of abundance.
abstract: Sustainable management of terrestrial hunting requires managers to set quotas restricting offtake. This often takes place in the absence of reliable information on the population size, and as a consequence, quotas are set in an arbitrary fashion, leading to population decline and revenue loss. In this investigation, we show how an indirect measure of abundance can be used to set quotas in a sustainable manner, even in the absence of information on population size. Focusing on lion hunting in Africa, we developed a simple algorithm to convert changes in the number of safari days required to kill a lion into a quota for the following year. This was tested against a simulation model of population dynamics, accounting for uncertainties in demography, observation, and implementation. Results showed it to reliably set sustainable quotas despite these uncertainties, providing a robust foundation for the conservation of hunted species.
authors.affiliation: Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, United Kingdom.
authors.forename: Charles T T
authors.initials: CT
authors.lastname: Edwards
authors.forename: Nils
authors.initials: N
authors.lastname: Bunnefeld
authors.forename: Guy A
authors.initials: GA
authors.lastname: Balme
authors.forename: E J
authors.initials: EJ
authors.lastname: Milner-Gulland
mesh_terms: D000349:Africa; D000465:Algorithms; D000818:Animals; D003247:Conservation of Natural Resources / Q000379:methods*; D003625:Data Collection; D008045:Lions; D011156:Population Density; D011157:Population Dynamics
keywords: control rule; management strategy evaluation; matrix model; operating model