Date of Award
Summer 8-31-2025
Level of Access Assigned by Author
Open-Access Thesis
Degree Name
Master of Forest Resources (MFR)
Department
Forest Resources
First Committee Advisor
Michael Premer
Second Committee Member
Aaron Weiskittel
Third Committee Member
Laura Kenefic
Additional Committee Members
Robert Seymour
Abstract
In an era of climate uncertainty, Maine's forests face the potential for significant ecological and economic challenges. Climate change is expected to alter forest composition and structure, particularly impacting black spruce (BS; Picea mariana), red spruce (RS; Picea rubens), and white spruce (WS; Picea glauca), species critical for timber production, biodiversity, and ecosystem services in the region. This research explores both the shifting habitat suitability of spruce under future climate conditions and the role of silvicultural strategies in sustaining productive spruce forests. The first component of this study assessed and mapped the contemporary and projected future suitable habitat of BS, RS, and WS in Maine, using fine-scale (21.8 m resolution) spatial models informed by field, climate, topographic, and soil data. The objectives of this study were to (1) quantify species-site relationships using contemporary data; (2) assess shifts in suitable habitat of spruce under future climate projections; and (3) generate predictive contemporary and future species suitable habitat maps to inform long-term forest management and conservation planning. The work revealed that species-site relationships vary considerably across Maine, with topographic and edaphic factors significantly influencing species presence. Results under future climate scenarios for 2050 and 2100 indicated substantial reductions in suitable habitat, highlighting the need for adaptive forest management strategies. High-resolution habitat models generated through this research help identify potential climate refugia and can guide long-term conservation planning. The second component focused on silvicultural approaches to sustaining spruce productivity through species mixing. Conducted at the Penobscot Experimental Forest, this analysis examined structural and productivity dynamics of mixtures and monocultures of BS, RS, WS, and Norway spruce (NS; Picea abies). To achieve this goal, the following objectives were addressed: (1) determine whether species in mixtures overyield in volume when compared to single-species stands and how the growing space is being occupied (vertical), and (2) test how microsite variations in soil and topographic features influence stand volume (m³ ha⁻¹). Treatment BS-NS overyielded, whereas no mixture treatments transgressive overyielded in comparison to the best-performing monoculture. These findings suggest that specific mixed-species planted stands could enhance resilience and productivity in a changing climate. This study furthers the understanding of the environmental and climatic conditions associated with the presence of various spruce species in Maine, while also shedding light on the performance of commonly planted species in mixed-species planted stands. Together, the chapters provide a framework to: (1) identify refugia locations for additional species of conservation concern (e.g., eastern hemlock); (2) map the suitable habitat of tree species using fine-resolution data; (3) assess the structural and productivity dynamics of various species mixtures in planted settings; and (4) evaluate the habitat suitability of species introduced for assisted migration. These findings underscore the importance of site-specific management and the potential for mixed-species planted stands to enhance climate resilience. In conclusion, integrating predictive ecological modeling with quantitative silviculture offers a powerful tool for developing adaptive, climate-informed forest management strategies tailored to Maine's diverse and changing landscapes.
Recommended Citation
Carter, Ashley, "Enhancing Spruce Forest Management in Maine: Digital Habitat Suitability Modeling and Structural-Productivity Dynamics of Species Mixtures" (2025). Electronic Theses and Dissertations. 4221.
https://digitalcommons.library.umaine.edu/etd/4221