Assessing the effects of different management scenarios on the conservation of small island vulture populations

Abstract

SummaryAlthough the population of Griffon Vulture Gyps fulvus is significantly increasing in Europe, in Italy the species is still on the Red List as ‘Critically Endangered’, with the last natural population persisting on the island of Sardinia. Several episodes of poisoning hampered the success of conservation actions implemented in the years 1987–1995. In 2005 there were estimated to be only 31–32 territorial pairs, with the population occupying the territories of Alghero and Bosa. We used a long-term dataset of reproductive records from the Sardinian Griffon Vulture populations to run a population viability analysis (PVA) to evaluate the extinction risk using the Vortex simulation software. The model estimated the probability of extinction over the next five generations (estimated generation time: 11 years, simulation time used: 55 years) as 96.4% for the Alghero population, and near-zero for the Bosa population. We used sensitivity analyses to understand how uncertainty about parameter values affect model outcomes. Population projections were evaluated under different management scenarios tackling the main threats (poisoning and human disturbance) and implementing conservation actions (supplementary feeding and restocking). Our results showed that population size is a critical factor in affecting the projections of population dynamics of Griffon Vultures. Sensitivity analyses highlighted the importance of poisoning events to population persistence and showed that juvenile and adult mortality rates had a secondary impact on population viability. The only conservation measure effective in significantly increasing stochastic growth rates in the Alghero population, whose initial population was set at five individuals, was the complete removal of poisoning events. When targeting the Bosa population (initial population size 94 individuals), supplementary feeding, mitigation of the risk of poisoning episodes, restocking, and mitigation of human disturbance in the reproductive sites significantly increased stochastic growth rate. A cost-effectiveness analysis should be performed to prioritise interventions.