The environmental sciences have progressively found themselves thrust from their humble roots in natural history into the role of detecting, quantifying, and predicting the interactions between humankind and our natural environment. We face a future where there is clear and growing demand for quantitative ecological forecasts with accurate assessments of uncertainty at the local, national, and global level. One of the primary goals of our work is to produce ecological forecasts by combining innovative ecological models with cutting-edge statistical and computational techniques and integrating diverse sources of data across many spatial and temporal scales. Forecasting is not merely an exercise in modern information technology, but requires tackling a number of basic research questions. At the forefront of these is the need to go beyond studying individual sites in isolation in order to understand the generalities across ecological systems. Basic science questions are what ultimately that drive our research: how do species coexist?; what are the relative contributions of biotic interactions, abiotic factors, and disturbance in structuring ecosystems?; and to what extent are ecosystem dynamics predictable versus determined by individual history and chance events? We are interested in understanding the universal constraints on vegetation dynamics through the integration of cross-site studies and focused field campaigns with cutting-edge models and modern statistical techniques. Overall our research is focused on the interacting roles of environmental heterogeneity, disturbance, and climate change in structuring vegetation dynamics.
Current projects are split between those focused on climate change responses versus those on novel biofuel crops. Both share many of the same questions about carbon fluxes and impacts on ecosystems services and biodiversity, and both use many of the same tools. The longest running work in the lab has focused on forest dynamics in the eastern and central U.S. at the stand, landscape, and regional scales, while the newest project in the Alaskan tundra looks at vegetation-fire-climate feedbacks. In our biofuels work we look at the suitability of different woody and perennial grass biofuel crops, their vulnerability to climate variability, their impacts on carbon storage and the water cycle, and the potential land use/land cover changes of biofuel expansion. Past projects have also involved work in Costa Rica, Australia, and the Pacific Northwest.
LeBauer, D.S., D. Wang, K.T. Richter, C.C. Davidson, M.C. Dietze. Feedbacks between measurements and ecosystem models. Ecological Monographs in press
NEON: Prof. Dietze has been named as the Boston University's NEON representative
The Dietze lab has relocated to Boston University. We are now part of the Earth and Environmental Science Department
Keenan et al. (NACP synthesis). 2012. Evaluation of terrestrial biosphere model performance for land-atmosphere CO2 exchange on inter-annual time scales: Results from the North American Carbon Program interim site synthesis Global Change Biology doi: 10.1111/j.1365-2486.2012.02678.x pdf
Richardson et al. (NACP synthesis). 2012. Terrestrial biosphere models need better representation of vegetation phenology: Results from the North American Carbon Program Interim Synthesis. Global Change Biology 18, 566–584, doi: 10.1111/j.1365-2486.2011.02562.x pdf
Wang, D., M.W. Maughan, J. Sun, X. Feng, F. Miguez, D.K. Lee, M.C. Dietze. 2012 Impacts of nitrogen allocation on growth and photosynthesis of Miscanthus (Miscanthus x giganteus) Global Change Biology Bioenergy in press
Hicke et al. (NACP synthesis). 2012. The effects of biotic disturbances on the North American carbon cycle. Global Change Biology 18:7-34. pdf
Dietze et. al. (NACP synthesis). 2011. Identifying the time scales that dominate model error: A North American synthesis of the spectral properties of ecosystem models. JGR-Biogeosciences 116, G04029, doi:10.1029/2011JG001661 pdf
Dietze, M., P. Moorcroft. 2011. Tree mortality in the eastern and central U.S.: Patterns and drivers. Global Change Biology 17(11): 3312-3326. pdf