Matthew Potts, Professor

Closed (1) Natural Pathways for Carbon Removal in Forest Ecosystems

Applications for fall 2021 are now closed for this project.

Addressing climate change will require more than reducing greenhouse gas emissions. It will require removing carbon from the atmosphere and durably storing it. Natural pathways for carbon removal, e.g. storing carbon in soils, forests, and wetlands, are likely to be the only way to achieve large scale carbon removal in the short term. This URAP explores how to best catalyze durable carbon removal in forested systems and how this can be done in a just and equitable manner.

Specifically, this project will focus on forest carbon offsets, which represent a rapidly growing, ill-defined field. Forest carbon offset credits are generated against a baseline which represents counterfactual carbon storage without offset revenue. In theory, this baseline represents “common forest practice” in the region. However, the protocols used to establish baselines are simplistic and likely produce over-crediting, which ultimately leads to greater carbon emissions. The accuracy of methods used in these projects has important implications for forest management and climate change.

Undergraduates interested in this project will aid in both protocol- and project-level analysis of existing forest carbon offset projects on the voluntary market. URAP students will play a central role in the data collection and analysis for this project. Further, interested students will have the opportunity to co-develop parts of the analysis with the PI. This analysis may include evaluating FIA data, collating carbon project data, geospatial data analysis, and literature review, among other activities.

The expected learning outcomes are broad and will be reflective of the student's interest. Students will improve their skills in data management, forest data analytics, forest ecology and management, literature review, and interdisciplinary analysis. Further, students will develop area knowledge of forest carbon accounting and carbon offsets, both of which are high-growth, high-impact research areas. , Ph.D. candidate

Qualifications: We are looking for motivated and independent undergraduate students with a broad background in the environmental sciences. Previous experience with forest ecology, forest management and/or carbon offsets is a plus. All students should have excellent reading, writing, and organizational skills and those interested in quantitative analyses ideally have a background in programming (e.g. R) and/or geospatial skills (e.g. Google Earth Engine).

Weekly Hours: to be negotiated

Related website: https://nature.berkeley.edu/pottslab/





Closed (4) Managing for Warmer Winters: Analyzing the effects of forest canopy age on snow retention

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

Snowpack accounts for much of California's water source and storage, providing water supply into the summer drought. We expect a climate change induced increase in warmer winters, so proactive management for snowpack retention should be a priority for the state. Previous studies have shown that forest canopy gaps—such as those caused by intact fire regimes and commercial harvests are much more effective at retaining snow compared to the forest matrix, but there are no studies that explore how long canopy caps remain effective reservoirs of snow. This study uses group selection harvests from 1975-2018 as proxies for different-aged canopy gaps to determine a gap age that maximizes snow retention. Ultimately, the goal is to find a gap-based silvicultural system and management solution that optimizes snow retention across the landscape to increase resilience and water security against climate change.

Data collection for this project is collected by use of 30 time-lapse cameras each monitoring a height pole placed in all of the selected group-selection units. The cameras will take four photos each day. Undergraduate researchers will be in charge of processing the data to determine and record daily snow-depth measurements. The graduate student will be in charge of collecting and uploading the images so that work will remain remote, safe, and accessible. While image processing may be manual, we gladly welcome students who are interested in creating an algorithm that can help automate the process and increase efficiency. Further opportunities or suggestions open to discussion and collaboration.

This study will require two winter seasons' worth of data. It is likely that the data collection method will be altered and improved for the second season. If interested, the undergraduate researcher may have opportunities to be involved in designing the data collection methods next winter. The undergraduate student may also be responsible for conducting literature reviews on snow data collection, long-wave radiation in the canopy, forest hydrology, and spatial variability within canopy gaps.

Day-to-day supervisor for this project: Sabrina Chui, Graduate Student

Qualifications: We are looking for eager, hardworking students interested in snow, forest management, forest hydrology, or exploring new realms of natural resource management. We welcome undergraduate students from a wide array of disciplines, as we are willing to teach anybody the skills they need for this position. The student should have strong reading and organizational skills. Preferred but not required: Students who have some programming skills, previous experience creating image processing algorithms, ability to read dense academic papers.

Weekly Hours: to be negotiated