You are here

Harvard Forest >

Summer Research Project 2021

  • Title: Land Use and Carbon Flux Forecasting Sub-project 3: Flux Footprint Spatial Comparison of Co-located Towers
  • 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 over-arching 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 Three – Flux Footprint Spatial Comparison of Co-located Towers (1 student; Mentors: Tim Whitby and Bill Munger)

    At Harvard Forest, the Environmental Measurement Site (EMS) flux tower has been collecting carbon and water fluxes continuously since 1991. Since 2017, the newly erected NEON flux tower has also been collecting data only a few hundred meters from the EMS. Although the towers are very close together, the distance and different observation height will alter the forest area that influences air sampled by the towers. At the EMS tower, we observe that flux patterns depend on wind direction, because of past land use and natural variation in species composition. However, wind direction and typical weather are related so the impact of vegetation and weather cannot be separated. The primary goal of the summer student is to apply an established flux footprint analysis for both towers during their time of overlap, to quantify how variations in species composition, site history, and moisture contribute to differences in observed carbon, water, and energy fluxes.

    The student will build on an existing code base in R for the EMS tower and apply that to the NEON tower. Once the footprints are calculated the student would be able to quantify the spatial and temporal overlap as well as the correlation of actual flux measurements. To understand what may be driving the differences in net ecosystem exchange, (and the component photosynthesis and respiration fluxes), other GIS datasets can be extracted using the footprint boundaries. For example, land-use maps from sub-project one could be overlaid on the footprints. Using the ForestGEO survey of all trees above 1 cm diameter at breast height (which includes both towers and extends into the prevailing wind direction), tree species composition could be quantified at each time step and summarized at longer time intervals. Depending on the student’s interests, other remotely sensed data may be obtained to develop new study questions. The student on this sub-project would primarily meet with Tim Whitby at least three times a week to cover training and direction with general R programming and needed spatial data analysis packages. Co-mentor Dr. Bill Munger would attend less frequently to provide scientific guidance and broader project feedback. Although only one student will be responsible for this study, there will be many opportunities to collaborate and interact with other group members.

    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