Abstract
The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.
Highlights
The size of the monarch overwintering population has followed a general downward trend, with the lowest populations recorded in the last three censuses[5] (Fig. 1)
Our estimate of process noise is considerably higher than the range of values reported in the literature[16], to date no synthetic study has attempted to generate a range of plausible process noise values for insects in general or lepidopterans in particular
While monarchs are currently under consideration for listing as threatened under the Endangered Species Act (ESA), there is no existing convention for defining threatened or endangered status under the ESA based on a quantitative extinction risk analysis
Summary
The size of the monarch overwintering population has followed a general downward trend, with the lowest populations recorded in the last three censuses[5] (Fig. 1). Our modeling approach separately estimates process noise and both measurement errors, and affords the ability to generate quasi-extinction probabilities based on probabilistic estimates of (1) process error (independent of measurement errors), (2) estimated overwintering population size in the last census year (winter 2014/2015), and (3) the growth rate of the population. Because these estimates are probabilistic, we were able to translate uncertainty in these parameter estimates into probabilistic estimates of quasi-extinction risk over specific time horizons
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