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Summer Research Project 2024

• Title: Using Landscape Ecology Tools to Understand Socio-Ecological Systems
• Group Project Leader: Jonathan Thompson
• Mentors: Xiaojie Gao; Danelle Laflower; Lucy Lee; Joshua Plisinski
• Collaborators: Mayra Rodriguez Gonzalez; Shersingh Joseph Tumber-Dávila
• Project Description:

  This project will bring together the use of simulation models and spatial analyses to better understand physical, biological, and social processes in the real world. The landscape ecology subprojects will explore (a) how development of ground-mounted solar arrays impacts the New England landscape, and (b) the impacts that nature based climate solutions and improved forest management strategies have on New England forest carbon. All projects are largely computer based and indoors.
  
  Subproject 1: Analyzing ground mounted solar array development in Massachusetts
  Co-Mentors: Joshua S. Plisinski; Lucy Lee
  
  Ground-mounted solar panel arrays are an important tool to decarbonize the electricity grid and mitigate climate change. There are approximately 10,000 acres of solar arrays in Massachusetts, with 60,000-100,000 more acres thought to be needed to achieve legislatively mandated clean energy goals. While ground-mounted solar development is expanding rapidly, there are many unanswered questions about its impacts on lands with conservation or ecological values, forest fragmentation, and human communities. This sub-project will utilize cutting edge solar maps to understand patterns of ground-mounted solar siting in Massachusetts as they relate to land cover and use, ecological data, or indicators of social/economic marginalization. The specific research question(s) will be defined collaboratively based on the successful candidate’s interests and skills. The successful candidate will learn how to conduct spatial analysis and make maps using ArcGIS Pro and analyze and visualize data using R. Depending on skill and interest, the successful candidate may learn to model land cover change scenarios or map solar with Google Earth Engine.
  
  Desired skills: Strong organizational and problem solving skills; Familiarity with or willingness to learn GIS; familiarity with or willingness to learn R; Interest in landscape ecology, land conservation, and/or energy systems; Interest in environmental policy or planning.
  Helpful but not required: Familiarity with Python (coding language)
  
  Subproject 2: Modeling climate change impacts on forest carbon storage
  Co-Mentors: Danelle Laflower, Xiaojie Gao
  
  Climate change has significantly altered the dynamics of forests such as seasonality and photosynthesis, thereby affecting forest carbon sequestration and storage. Understanding the dynamics of forests in response to climate change is thus critical for managing forests, making conservation policies, and developing nature-based climate solutions. For this study, the student will investigate changes in climate during the last several decades and use simulation models to quantify the corresponding impacts on forest carbon storage. Model validation will be conducted at Harvard Forest where abundant data are available, and model simulation will be based on future climate scenarios. The goal will be to improve our understanding of how climate change has affected, and will affect, long-term forest dynamics and carbon storage.
  
  This subproject will provide an opportunity to become familiar with forest simulation models, to develop R scripts to interact with these models, to learn GIS tools for R, and to practice open science.
  
  Desired Skills: Interest in forest ecosystems and simulation models; Good computational and programming skills and experience with (or willingness to learn) R.

• Readings:

  Hernandez, R.R., Hoffacker, M.K., Murphy-Mariscal M.L., Wu, G.C., and Allen, M.F. 2015. Solar energy development impacts on land cover change and protected areas. Proceedings of the National Academy of Science 112(44): 13579-13584.
  
  Thompson, J. R., Simons-Legaard, E., Legaard, K., Domingo, J. B. 2016. A LANDIS-II extension for incorporating land use and other disturbances. Environmental Modelling & Software 75: 202-205.
  
  Kaarakka, L., Cornett, M., Domke, G., Ontl, T. and Dee, L.E., 2021. Improved forest management as a natural climate solution: A review. Ecological Solutions and Evidence, 2(3), p.e12090.

• Research Category: Regional Studies, Ecological Informatics and Modelling, Conservation and Management