Use of a hybrid Circuitscape/Agent model to identify restoration and protection priorities for Monarch butterfly preservation

Background/Question/Methods

Conserving and managing migratory species is challenging due to the need to integrate multiple threats that may be nonuniformly distributed across the species’ range. Monarch butterfly populations, for example, are declining due to factors including habitat loss, pesticide use and climate change throughout their migratory range. However, translating this conceptual knowledge to a specific and effective habitat restoration or protection plan is difficult because impacts of local interventions depend on global characteristics of the migration domain. Safeguarding migrating populations can be greatly facilitated with a quantitative approach that relates local landcover to global migration pathways. Here, we introduce a computational migration model that spans the continental US using high-resolution land-cover and pesticide data. We assess the ability of this approach, which integrates a dual-scale circuitscape calculation with an agent-based model to identify and prioritize locations and factors that limit successful migration pathways.

Results/Conclusions

We find that the hybrid Circuitscape/Agent model can be used to prioritize regions where habitat restoration would have the greatest impact on improving Monarch Butterfly migration pathways. The method produces independent prioritization maps for differing factors (e.g. lack of milkweed, lack of forage.) Based on a set of empirically-derived assumptions, we present spatial results indicating how the quality of migration paths has changed over time and identify specific locations where interventions in land use would best improve the quality of migration pathways.