Integrating social and ecological dimensions for the conservation of the Monarch butterfly using systems dynamics and choice modeling

Currently, human activity is the primary driver of global biodiversity loss, so researchers, managers, and decision-makers need to recognize the link between nature and society. Conservation strategies must be analyzed holistically as complex adaptive systems (CAS) for effective conservation strategies. This thesis integrates biological and social sciences to help conservationists improve their planning toolbox, using a case study of the Monarch butterfly (Danaus plexippus), an iconic and imperilled migratory butterfly in North America. More specifically, it examines the importance of recognizing when a conservation issue is a social-ecological CAS and considering the dynamism between the system's social and ecological aspects, potentially determining the success or failure of conservation efforts. Firstly, this thesis explored the social domain by describing general preferences for international conservation strategies for Monarch butterfly conservation to determine heterogeneity in public preferences for strategic-level features of a recovery strategy. In addition, it demonstrates how program success projections affect people's willingness to support conservation efforts. This analysis used a discrete choice experiment and latent class analysis to achieve its objectives. Then, the Monarch ecological domain was analyzed by developing a full-migration temperature-dependent demographic model and testing the hypothesis that the number of milkweed stems currently recommended to reach a Monarch's minimum viable population falls short of its actual requirements. A Bayesian-driven estimation of the actual additional yearly number of milkweed stems needed is presented. In the final data chapter, both domains analyzed in previous sections are combined into a social-ecological model to study an NGO's implications to not account for a donor's dynamic willingness to pay for Monarch conservation. This model also estimates the optimal donations an NGO should ask for to reach their conservation goal. CAS are chaotic and unpredictable by nature, making them challenging for resource managers. Nevertheless, with human presence influencing most of our world, learning to deal with their nonlinearities and uncertainties is crucial. This thesis provides tools in that direction, hoping that future researchers and practitioners can use them to understand CAS better and improve conservation actions.