An analysis of the impact of historical spatial patterns of forest harvesting practices for carbon management.

This project examines the influence of patterns of historical management of forests on current carbon-management actions, and what these limits mean for carbon management more broadly. The forestry industry is increasingly looking towards carbon management and markets to both create income, and to sustainably manage its lands. Regenerating historical harvests are prime opportunities for carbon management, similar to selling carbon offsets to other industries.

However, the legacy of historical management patterns that were governed by a different set of objectives can limit where carbon-focused future management occurs. The impact of this mismatch between historical objectives and current and future goals is presently unknown. This project couples satellite imagery and ground data with an integrated ecological management model that quantifies how historical management, environmental variability, and natural disturbance influences the spatial variation, vulnerabilities, and valuation of carbon.

Graduate students will work with local, private industry partners to receive business-level knowledge of carbon markets as well as be mentored in STEM research. The PIs will also develop teaching modules for K-12 education.

Scientist’s understanding of the role of historical spatial patterns of forest management and disturbance in limiting or enhancing future carbon management is inadequate. This lack of understanding severely constrains the ability to plan forestry management at both the private and public sectors as spatial variability in exposure to both natural and human-caused disturbances is significant.

This project uses a high-resolution computer model to quantify how historical management, environmental variability, and disturbance constrains and influences the spatial variation, vulnerabilities, and valuation of carbon. The researchers will construct a broad-scale quantification of disturbance patterning and incorporate that into the open-source, LANDIS-II framework.

From this work scientists will develop scenarios of future carbon sequestration and valuation that are more or less constrained by the footprint of past management. The overarching goal of this project is to determine to what extent the ability to manage for carbon is limited, or improved, by the spatial legacy of past actions. Understanding how historical patterns of management constrain those opportunities is critical to assessing future carbon potential.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.