This project aims to develop and apply a tree growth model in order to strengthen the recovery of climate signals (temperature and moisture) recorded in the width of tree-ring. This tree growth model has the potential to improve large-scale climate reconstructions and will be useful for understanding and ameliorating systematic differences between instrumental and tree-ring climate reconstructions. The growth model is based on the Liebig's law of the minimum which describes how tree growth is dictated by the most limiting factor (e.g. sunlight, nutrients, moisture). The researchers will: 1) conduct a comprehensive analysis of 4,213 tree-ring sites from the International Tree Ring Data Bank to understand how Liebig's Law influences within-stand variability; and 2) characterize the ways that Liebig's Law influences the distribution of climate signal across trees in both a model and observational context. The goal of this project is to develop reconstruction techniques for inverting growth for temperature or precipitation in the presence of local limitations on growth. These reconstruction techniques have the potential to result in substantially improved reconstructions of local and regional climate variability.
The potential Broader Impacts include new methodologies to use tree growth and tree-ring proxies for climate reconstructions. A dendroclimatology field-based class to first-year students at San Francisco State University (a designated Minority Serving Institution by the Department of Education) will be developed, with the goal of recruiting minority and economically disadvantaged students to the Earth Sciences. The project will support the education and training of two graduate students. The researchers will incorporate concepts and results from this project in their respective classes and outreach activities.
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.
