Collaborative Proposal: MSB-ECA: A multi-scale framework to quantify and forecast population changes and associated uncertainties

Georgetown University, Washington DC

Investigators

Abstract

Monarch butterflies (Danaus plexippus) have rapidly declined across North America over the last 19 years from environmental change, although the exact causes are under intensive study. Understanding and forecasting species changes in monarch butterflies at regional and continental scales is challenging because both local- and broad-scale environmental dynamics affect their changes. This project will develop a modeling framework which recognizes that butterfly abundance patterns reflect not only butterfly responses to their environments at fine scales (e.g., local weather), but also to broad-scale factors (e.g., distributions of suitable habitat). The specific goal is to determine the relative effects of climate and land-use on a model migratory species, the monarch butterfly and then forecast population changes at multiple scales under future climate and resource availability scenarios. This project will integrate continental-scale data from multiple regional and national butterfly monitoring programs and climate and land-use databases, spanning their entire migratory cycle, across all seasons, over 20 years. The modeling approach will explicitly quantify uncertainties from both population-environment relationships and future climate projections to evaluate how conservation actions may reverse population declines. This work meets a significant challenge that has long-hindered large-scale ecological research: the integration of biological processes at multi-scales using different data types coupled with predictive environmental models. The data integration modeling framework incorporates mechanism into broad-scale models, representing the best possible approach for many real-world macrosystems in which the development of wholly mechanistic models is not tractable due to data limitations and/or difficulties describing the details of every relevant process. Additionally, predications about the size and distribution of future populations can be made with a quantifiable level of confidence in those estimates. The modeling framework developed in this project will help determine how different regions and periods of a species annual cycle contribute to population trends, leading to more accurate estimations at broad spatial scales, and targeted data collection, modeling, and conservation efforts. The results will contribute broadly to scientific advancement in this field because of the transferability of the modeling framework to other cross-continental species where it is similarly difficult to track and predict population abundance and trends. The project will also offer a rigorous analysis of the factors causing declines of a high profile species and how effective specific conservation and restoration acts could be under changing climate conditions. The research team will collaborate with the Monarch Joint Venture, a multi-institutional partnership, to promote science and conservation of monarchs and disseminate results to the general public through their existing online resources and newsletters.