Collaborative Proposal: MRA: Using NEON data to elucidate the ecological effects of global environmental change on phenology across time and space

Global environmental change is causing shifts in species’ phenologies (the timing of ecological processes) and rates of acclimation (physiological adjustments to environmental change), the physiological precursors to phenological shifts. These shifts are important because they can create 'mismatches' in the performance and timing of interacting species, such as predators and prey, hosts and parasites, competitors, and plants and pollinators, which can adversely affect biodiversity and the services that ecosystems provide to humans.

Despite extensive data on the phenology and acclimation of individual species, no general framework exists that can predict how phenological responses of species – and by extension species interactions – will respond to environmental change. To address this knowledge gap and provide broader impacts to society, a research team has been assembled with expertise in global change and thermal biology, ecoinformatics, mathematical and statistical modeling, and geographic information systems.

The broader impacts of the project include: training the next generation of STEM undergraduates and graduate students across diverse ethnic backgrounds and genders, a graduate course on large scales and ‘big data’ in biology, and new databases for posterity that will guide conservation and monitoring for species invasions and infectious diseases.

From a scientific perspective, this team proposes to i) expand phenological datasets, ii) gather data from the literature on environmental change effects on species interactions, iii) develop a quantitative global framework for predicting the direction and magnitude of effects on individual species’ phenologies and species interactions based on latitude, climate, and organismal traits, and iv) validate present-day predictions of the model by working with at least 13 existing National Ecological Observatory Network (NEON) datasets. The specific objectives are to: 1) assemble a database of time series describing phenological shifts, local climatic drivers, latitude and elevation, and organismal body sizes; 2) develop a mathematical framework for predicting the phenological responses of species to environmental change, by quantifying how phylogeny, body size, habitat, latitude, phenological trait, and environment (temperature and precipitation) affect phenology; 3) use NEON data to validate this framework by testing whether it can accurately predict the phenological responses of individual species to variability in present-day climate, from local to continental scales; 4) use NEON data to evaluate the ability of this framework to predict how variability in present-day climate will affect the strength and outcome of species interactions and ecosystem functions; and 5) once validated, couple the framework to local environmental change projections to predict species and locations around the globe that will be particularly sensitive to changing environments.

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.