CAREER: Advancing a macrosystems framework for climate-phenology coupling through integrated research and education

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

Phenology - the timing of recurring biological events - is nature’s calendar. Changes in timing of seasonal events such as leaf and flower emergence are among the most visible fingerprints of climate change. Such phenological changes, in turn, can affect climate by altering critical Earth system processes such as carbon uptake. Thus, climate and phenology are closely coupled, leading to a complex system with feedback loops. In this NSF CAREER project, a novel framework to quantify multiple processes in climate-phenology coupling will be developed to answer questions about how climate and phenology interact with each other across scales and among remote locations. This research on climate-phenology coupling will accrue significant societal benefits, such as facilitation of crop management and forecasting pollen outbreaks to mitigate airborne allergies in public health. This project will also implement an education plan at the University of California Santa Cruz, a Hispanic American-Serving Institution, to enhance climate change and data science education. Scientific outreach will be multiplicative and synergistic through student use of social media, transforming recipients of education into active educators of climate change. Building on the novel climate-phenology coupling framework, the project will construct a series of dynamical, statistical, and computational models to advance ecological forecasting in three ways. First, the strength of climate-phenology coupling will be systematically quantified over space and time on a global scale and interpreted in light of plant distributional shifts and human activities. Second, scaling, a fundamental challenge in macrosystems biology, will be tested with multi-scale datasets from the National Ecological Observatory Network (NEON). The identification and quantification of cross-scale interactions and emergence will be pivotal to developing highly predictive phenology models. Third, the understudied field of teleconnections will be explored through spatiotemporal analyses, which will promote next-generation phenology models leading to improved projections of future carbon, water, and energy fluxes. The project will also develop reproducible workflows to stream data from multiple sources and perform near-term ecological forecasting. Finally, climate-phenology knowledge and novel data science skills gained in the research plans will be used to strengthen a data science training program for university students and professionals, enhance experiential learning for secondary school students, and improve climate change education for the general public. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.