This project will bring together the use of simulation models and spatial analyses to better understand physical, biological, and social processes on the New England landscape. There can be either one or two landscape ecology subprojects, each with two to three mentors. The projects will be computer based and mostly indoors.
SUBPROJECT 1 - Modeling Changes in New England Forest Land Cover and Use.
Co-Mentors: Joshua Plisinski, Lucy Lee
Project Description: New England is one of the most heavily forested regions in the United States. These forests are undergoing rapid changes to their extent with loss due to clearing for residential and commercial development as well as clearing for wind and solar energy production. The remaining forest is also undergoing changes in use with shifting timber harvest patterns due to changes in regional economics, land ownership, and environmental regulation. At the same time, a wide variety of conservation organizations are protecting forests from harvest and development, however their selection of land for conservation is often different and sometimes competing with criteria such as increased timber production, increased carbon sequestration, specific species habitat preservation, and provision of recreational opportunities. In addition, human-induced natural disturbances add uncertainty to carbon dynamics and forest management-based climate change mitigation.
In the Thompson Lab, we study these long-term and broad-scale changes in forest ecosystems, with an emphasis on quantifying how land use – including harvest, conversion, and land protection – affects forest ecosystem processes and services.
This subproject will provide an opportunity to gain familiarity with long-term forest records and spatial datasets, and the tools used to map and model these processes. The project will rely heavily on spatial analysis with ArcGIS Pro, modeling with Dinamica EGO or LANDIS, and automating workflows with R and/or Python, to create maps and data visualizations.
Desired skills: Strong organizational, data management, and problem solving skills; Experience with ArcGIS Pro or other GIS; Experience with or willingness to learn R and/or Python; Interest in landscape ecology and/or forest conservation/policy.
SUBPROJECT 2 - Estimating Temperate Forest Edge Biomass from Satellite Remote Sensing
Co-Mentors: Nik Bates-Haus, Danelle Laflower
Project Description: New England’s temperate forests are heavily fragmented, with approximately 25% being within 30m of a non-forest edge. Temperate forest edges have been shown to be ecologically distinct from forest interiors, exhibiting large increases in growth, aboveground biomass accumulation, and net carbon (C) storage, and without evidence of increased tree mortality due to increased stress. When estimating forest biomass from remote sensing data, existing methods are sensitive to “mixed pixels” at forest edges, where a single pixel contains both forest and non-forest land cover. Since so much of New England’s forest is edge-adjacent, this mixed-pixel influence has the potential to significantly bias overall estimates of regional forest biomass and C storage.
In the Thompson Lab, we study forest C storage and the impacts of patterns of land use on it. In this project, we will use existing forest edge plots within the Harvard Forest to calculate the magnitude of the mixed-pixel effect on estimates of aboveground biomass. Estimating aboveground biomass from remote sensing data uses a combination of canopy height measurement (e.g. airborne LiDAR), satellite remote imagery (e.g. LANDSAT), and biomass equations, all of which are available for these existing plots. We will supplement these data with field measurement of tree diameter to determine the bias introduced by the mixed-pixel effect.
This subproject will provide the opportunity to gain familiarity with forest field measurement, remote sensing data, and spatial analysis, and the tools to gather and process these data. The project will rely heavily on R and the RSpatial collection of packages for geospatial information processing in R. Although the project will be largely computer based, there is a field component to visit nearby forest edge plots and survey aboveground biomass.
Desired skills: Strong organizational, data management, and problem solving skills; Experience with R; familiarity with geospatial information and geospatial information processing; Experience with or willingness to learn R; Interest in landscape ecology and/or forest conservation/policy.
(#1) Lee, L. G., Pasquarella, V. J., Glass, B., Morreale, L. L., Chung, N., Gao, X., Thompson, J. R. 2025. A comparison shopper’s guide to forest datasets. Landscape Ecology 40: 216.
(#1) Thompson, J. R., Laflower, D. M., Plisinski, J. S., MacLean, M. G., Chu, H., Carpenter, D., Antos, K., Cooper, S., Gaertner, K., Judge, M., Mittelman, M., Ryor, J., Van Doren, W. 2025. Forest Carbon Study: The Impact of Alternative Land-use Scenarios on Terrestrial Carbon Storage and Sequestration in Massachusetts.
(#1) Thompson, J. R., Kalinin, A., Lee, L. G., Pasquarella, V. J., Plisinski, J., and Sims, K. R. E. 2024. Do working forest easements work for conservation? Environmental Research Letters 19(11): 114033. https://doi.org/10.1088/1748-9326/ad7ed9
(#2) Smith, I.A., Hutyra, L.R., Reinmann, A.B., Marrs, J.K., Thompson, J.R., 2018. Piecing together the fragments: elucidating edge effects on forest carbon dynamics. Frontiers in Ecology and the Environment 16, 213–221. https://doi.org/10.1002/fee.1793
(#2) Harris, N.L., Gibbs, D.A., Baccini, A., Birdsey, R.A., de Bruin, S., Farina, M., Fatoyinbo, L., Hansen, M.C., Herold, M., Houghton, R.A., Potapov, P.V., Suarez, D.R., Roman-Cuesta, R.M., Saatchi, S.S., Slay, C.M., Turubanova, S.A., Tyukavina, A., 2021. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Chang. 11, 234–240. https://doi.org/10.1038/s41558-020-00976-6
(#2) Thompson, J. R., Laflower, D. M., Plisinski, J. S., MacLean, M. G., Chu, H., Carpenter, D., Antos, K., Cooper, S., Gaertner, K., Judge, M., Mittelman, M., Ryor, J., Van Doren, W. 2025. Forest Carbon Study: The Impact of Alternative Land-use Scenarios on Terrestrial Carbon Storage and Sequestration in Massachusetts.