Most natural ecosystems contain animals feeding on many different types of food, but it is
difficult to predict what will be eaten when food availabilities change. We present a method
that estimates food preference over many study sites, even when number of food types vary
widely from site to site. Sampling variation is estimated using bootstrapping. We test the precision and accuracy of this method using computer simulations that show the effects of overall number of food types, number of sites, and proportion of missing prey items per site.
Accuracy is greater with fewer missing prey types, more prey types and more sites, and is
affected by the number of sites more than the number of prey types. We present a case
study using lion (Panthera leo) feeding data and show that preference vs prey size follows a
bell-curve. Using just two estimated parameters, this curve can be used as a general way to
describe predator feeding patterns. Our method can be used to: test hypotheses about what
factors affect prey selection, predict preferences in new sites, and estimate overall prey consumed in new sites.The Natural Sciences and Engineering Research Council of Canada and a Hugh Kelly Fellowship from Rhodes University, Grahamstown, SA.http://www.plosone.orgdm2022Mammal Research Institut