Managing the Cayo Santiago rhesus macaque population: The role of density.

Cayo Santiago is the oldest continuously operating free-ranging rhesus monkey colony in the world. Population control of this colony has historically been carried out by periodic live capture and removal of animals. However, the effect of such a strategy on the size, growth rate, age structure, and sex ratio of the population has not been analyzed. This study reviews past removal data and uses a population projection model to simulate the effects of different removal schemes based on Cayo Santiago demographic data from 2000-2012. The model incorporates negative density-dependence in female fertility, as well as male and female survival rates, to determine the population-level effects of selective removal by age and sex. Modeling revealed that removal of sexually immature individuals has negligible effects on the population dynamics explaining why with an initial population of 1309 in 2000 and annual removals of immature monkeys a mean annual population growth rate of 12% and a final population size of ∼1,435 individuals by 2012 (∼0.009 animal/m(2) ) was observed. With no removals, the population is expected to exhibit dampened oscillations until reaching equilibrium at ∼1,690 individuals (∼0.0111 animal/m(2) ) in 2,100. In contrast, removal of adult females (≥4 yrs) would significantly reduce the population size, but would also promote an increase in population growth rate due to density feedback. A maximum annual production of 275 births is expected when 550 adult females are present in the population. Sensitivity analyses showed that removing females, in contrast to controlling their fertility through invasive treatments would contribute the most to changes in population growth rate. Given the density compensation on fertility, stabilizing the population would require removing ∼80% of the current population of adult females. This study highlights the importance of addressing the population-level density effects, as well as sensitivity analyses, to optimize management strategies.