School of Forest Resources

Rose Abramoff

Education:

Ph.D., Boston University

Certificate in Biogeoscience, Boston University

B.A., Amherst College

Before arriving to UMaine in 2025, I held staff or postdoctoral positions at Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, and Le Laboratoire des Science du Climate et de l’Environnement. 

My current focal areas are belowground carbon cycling, forest ecology, and climate feedbacks, but I have an expanding interest in climate impacts and decision science.

Research:

My research focuses on how climate change and human land use affect the land carbon cycle, particularly belowground components like plant roots and soil. We use field and laboratory measurements, large dataset synthesis, machine learning, and computer simulation modeling. I’ve worked in a variety of ecosystems, including the Arctic tundra, fire-prone Mediterranean forests, Eastern forests, and agricultural fields on topics related to climate change impacts, soil microbial modeling, plant-soil interactions, and carbon sequestration.

Courses:

SFR 521: Research Methods in Forest Resources (co-taught)

3 credits

Provides graduate students with the fundamental research skills needed to successfully prepare for their thesis research, as well as professional careers in scientific research. Students learn how to plan, write, and critique scientific research proposals. Instructions focuses on direct, hands-on learning by writing a proposal that can serve as a student’s graduate thesis research proposal. Students learn to pose relevant, interesting, and researchable questions; design testable hypotheses; develop research goals and objectives; and apply critical thinking skills to design appropriate research methods. Key elements of research planning include funding, project management, responsible conduct in research, and journal publications are covered. Graduate students taking this course will meet the University of Maine’s requirement for Responsible Conduct in Research training.

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SFR 6xx: Analysis of Ecological Data

3 credits

Ecological systems are shaped by dynamic interactions between their physical environment and living organisms, including humans. To make informed decisions about management, restoration, and mitigation, we need more than just qualitative understanding—we need to be able to test our hypotheses in a clear and quantitative way. This course will equip you with the statistical methods used to unravel the patterns and processes that govern ecological and Earth systems. You will develop strategies to address research questions using a variety of methods, including experimental design, analysis of variance, regression, mixed models, maximum likelihood, machine learning, and more. You will learn to use the statistical programming language R to analyze and visualize real-world data. Whether you are working with ecosystem functions, community dynamics, or global environmental change, this course will help you ask useful questions, design effective studies, and use statistical analyses to make meaningful contributions to your field.

Graduate Students:

I am hiring a MS student for Fall 2025 – apply here

Publications:

Link to Google Scholar

Link to ORCID