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Summer Research Project 2021

  • Title: Land Use and Carbon Flux Forecasting Sub-project 2: Near-term Forecasting of Carbon and Water Fluxes
  • Group Project Leader: Sydne Record
  • Mentors: Michael Dietze; Alexis Helgeson; Sparkle Malone; J. William Munger; Sydne Record; Timothy Whitby
  • Collaborators: Paige Kouba; Andrew Latimer
  • Project Description:

    This is part of the group project, 'Land Use and Carbon Flux Forecasting,' which has the following overarching intellectual theme:

    The exchange of water and carbon dioxide between the atmosphere and the land is akin to earth’s terrestrial ecosystems breathing rate and lung capacity. An important measure of ecosystem function is the exchange of mass and energy, which can be determined with the eddy-covariance method. This method observes the flux of carbon and water between terrestrial ecosystems and the atmosphere at half-hourly timesteps. This information allows us to understand photosynthesis, respiration, and transpiration, their sensitivities to ongoing climate and land use change, and greenhouse gas budgets for carbon accounting and natural climate solutions. Forecasts of carbon uptake and release, water use, and soil moisture can provide insights into future production of food, fiber, timber and carbon credits along with the influence water stress has on these processes. Furthermore, iterative, near-term forecasts of these fluxes can spur scientific insights and provide information more relevant to sustainability decision-making (Dietze et al. 2017). This project will explore how the incorporation of land use data influence the predictive ability of near-term forecasts of carbon uptake and water release at several sites that are part of the National Ecological Observatory Network (NEON; Jones et al. In press). The students involved in this project will gain a familiarity with near-term ecological forecasting and learn or expand upon skills in environmental data science (i.e., programming in R, working with spatial data layers using geographic information software [GIS]). We seek six students to work on three sub-projects to gain exposure to different methodologies. We will have weekly team meetings using video conferencing to keep all project members up to date on progress and to expose students to the nature of long-distance collaborative work across a distributed scientific network. Students are encouraged to ask and pursue independent research questions of their own (which could be the basis for a senior thesis or other undergraduate research paper).

    Sub-project Two – Near-term Forecasting of Carbon and Water Fluxes (3 students; Mentors: Mike Dietze, Sparkle Malone, Alexis Helgeson)

    For the past couple of years, we have been running daily forecasts of carbon and water fluxes at Harvard Forest and several other Ameriflux sites ( These forecasts have an hourly resolution and 16-35 day duration, and thus for any point in time we compare observations to predictions made 1 to 16+ days in advance, with the aim of better understanding the predictability of the carbon and water cycles in general, and our ability to anticipate stress in particular, as well as to test model assumptions and hypotheses. This summer our primary goals are (A) to extend our forecast system to additional NEON sites and (B) building on the analyses coming out of subproject 1, to test if we can improve our flux forecasts by accounting for the spatial pattern of vegetation and land-use in the eddy-covariance tower footprint. To calibrate the forecast models to new sites we will determine the Light-use efficiency (LUE) of NEON sites. Light-use efficiency is influenced by environmental stress factors that reduce the photosynthetic capacity of plants in an ecosystem at a given time. Changes in photosynthetic capacity can be caused by stresses imposed by water or nutrient limitations; other factors, such as disturbances and suboptimal temperatures, can also reduce photosynthetic capacities even after the actual stress event has ended. This summer we will (A) determine the maximum photosynthetic rates for our research sites and (B) evaluate how and why LUE changes over time at NEON sites. We will prioritize NEON sites that are part of the Ecological Forecasting Initiative’s NEON forecast challenge, allowing students to participate in this international research competition. If time permits, we will consider ways to add additional NEON data constraints to the forecast system (e.g., soil respiration). Our near-term forecasts will enable us to explore the varying capacities of ecosystems to capture and sequester carbon.

    There will be three students selected for this sub-project. Students will meet with their mentors (Dr. Sparkle Malone, Dr. Mike Dietze, and Alexis Helgeson) at least three times per week. Much of the work for this project will involve learning, working with, and building upon an existing forecasting workflow implemented within the PEcAn community cyberinfrastructure (, Fer et al 2020), which is implemented primarily in R. This will include, but is not limited to, generalizing the existing pipeline to more sites and to multiple land-use classes within a site, spatial analyses to determine how to integrate land-use heterogeneity into forecasts, and analyzes comparing forecasts to a wide range of observations to assess predictability and test the hypotheses embedded in process-based ecosystem models.

    The students working on this project must:
    1. Be willing to spend many hours on the computer analyzing data;
    2. Be willing to coordinate meetings with and call by phone or video conferencing sub-project team members (and for sub-project 1 willingness to reach out to contacts for reconstructing site histories);
    3. Have, or be willing to develop, a basic understanding of ArcGIS (subproject 1), and R for graphical and statistical analysis;
    4. Be willing to coordinate and contribute to weekly video conferencing meetings with the collaborative team.

  • Readings:

    Dietze, M.C., Fox, A., Beck-Johnson, L.M., Betancourt, J.L., Hooten, M.B., Jarnevich, C.S., Keitt, T.H., Kenney, M.A., Laney, C.M., Larsen, L.G. and Loescher, H.W., 2018. Iterative near-term ecological forecasting: Needs, opportunities, and challenges. Proceedings of the National Academy of Sciences, 115(7), pp.1424-1432.

    Fer I, AK Gardella, AN Shiklomanov, SP Serbin, MG De Kauwe, A Raiho, MR Johnston, A Desai, T Viskari, T Quaife, DS LeBauer, EM Cowdery, R Kooper, JB Fisher, B Poulter, MJ Duveneck, FM Hoffman, W Parton, J Mantooth, EE Campbell, KD Haynes, K Schaefer, KR Wilcox, MC Dietze, Beyond Modeling: A Roadmap to Community Cyberinfrastructure for Ecological Data-Model Integration. Global Change Biology doi:10.1111/gcb.15409
    Foster, D.R., Swanson, F., Aber, J., Burke, I., Brokaw, N., Tilman, D., and Knapp, A. 2003. The importance of land-use legacies to ecology and conservation. Bioscience, 53(1):77-88.

    Jones, J.A., P.M. Groffman , J. Blair, F.W. Davis , H. Dugan, E.E. Euskirchen, S.D. Frey, T.K. Harms, E. Hinckley, M. Kosmala, S. Loberg, S. Malone, K. Novick, S. Record, A.V. Rocha, B.L. Ruddell, E.H. Stanley, C. Sturtevant, A. Thorpe, T. White, W.R. Wieder, L. Zhai, and K. Zhu. In press. Synergies among environmental science research and monitoring networks: 2 A research agenda. Earth Futures.

    Malone, S. L., Staudhammer, C. L., Oberbauer, S. F., & Olivas, P. (2014). El Nino Southern Oscillation (ENSO) enhances CO2 exchange rates in freshwater marsh ecosystems in the Florida Everglades. PloS One.

    Urbanski, S., C. Barford, S. Wofsy, C. Kucharik, E. Pyle, J. Budney, K. McKain, D. Fitzjarrald, M. Czikowsky, and J. W. Munger. 2007. Factors controlling CO2 exchange on timescales from hourly to decadal at Harvard Forest. Journal of Geophysical Research: Biogeosciences 112:1–25.

  • Research Category: Historical and Retrospective Studies, Group Projects, Forest-Atmosphere Exchange, Ecological Informatics and Modelling