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Thogmartin W, Diffendorfer JE, Lopez-Hoffman L, Oberhauser K, Pleasants J, Semmens BX, Semmens D, Taylor OR, Wiederholt R.2017. Density estimates of monarch butterflies overwintering in central Mexico. PeerJ Preprints5:e2832v1https://doi.org/10.7287/peerj.preprints.2832v1
Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha-1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ~27.9 million butterflies ha-1 (95% CI: 2.4–80.7 million ha-1); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha-1). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern U.S. plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations.