The Forest Business concentration is a 35-credit-hour, coursework-only M.S. with a comprehensive examination.
Degree Requirements
- 35 total graduate credit hours
- 12 credit hours in mandatory courses
- 23 credit hours of electives selected in consultation with the student’s major professor and/or graduate committee
- 12 graduate credit hours of electives must be in FORS or FWF courses
- At least 28 of the 35 graduate credit hours must be earned in courses numbered at or above the 500 level
- Successful completion of a final oral examination
Current Required Courses
- AREC 512 – Advanced Agribusiness Finance (3 credit hours)
- FORS 511 (3 credit hours)
- FORS 525 – Financial Accounting in Forestry (3 credit hours)
- FORS 595 (3 credit hours)
Students then use electives to develop a curriculum appropriate to their professional interests and chosen area.
Featured Forest Business Courses
FORS 521 – Economics and Finance for the Forest Products Industry
Provides advanced knowledge of economics, finance, and engineering economics methods applied to the wood products industry. Topics include financial accounting, capital budgeting, risk analysis, sustainability, carbon finance, and firm valuation, with case studies drawn from forestry, lumber, and bioenergy sectors.
FORS 522 – Timberland and Ecosystem Services Investment Principles
Examines timberland and ecosystem services as emerging asset classes within natural resource finance. Students explore the economic and financial principles underlying timberland investment and the valuation of ecosystem services such as carbon sequestration, water quality, and biodiversity conservation. Emphasis is placed on institutional timberland ownership models, investment performance evaluation, risk-return analysis, and integration of ecosystem services into timberland portfolios.
FORS 525 – Financial Accounting in Forestry
Covers principles of accounting, financial analysis of forest products company operations, timber taxation, and strategies involving forest assets in estate planning.
FORS 530 – Advanced Forest Resource Management
Addresses the analysis of forest management problems in public and private organizations. Topics include classical forest regulation; linear and goal programming applied to resource management problems; advanced forest investment analysis; decision-making methods for primary forest management activities; and methods for incorporating non-timber values into forest management operations.
Build an Interdisciplinary Program
One of the strengths of the Forest Business M.S. is the ability to combine forestry with graduate coursework from other disciplines. Your specific program of study will be developed by you, your faculty advisor, and graduate committee based on your specific goals. Below is a list of possible courses available to forest business students.
Forestry and Natural Resources
- FORS 521 – Economics and Finance for the Forest Products Industry
- FORS 522 – Timberland and Ecosystem Services Investment Principles
- FORS 530 – Advanced Forest Management
- FORS 531 – Advanced Biocomposite Materials
- SNR 525 – Applied Natural Resource Statistics
- SNR 530 – Introduction to Geographic Information Systems (GIS) for Natural Resources
- SNR 610 – Data Modeling and Visualization Using R
Agricultural and Resource Economics
- AREC 420 – International Trade and Marketing
- AREC 503 – Managerial Economics
- AREC 505 – Microeconomic Analysis
- AREC 525 – Optimization Methods for Agricultural and Resource Economics
- AREC 542 – Agriculture and Resource Simulation and Forecasting Analysis
- AREC 550 – Microeconomic Applications to Agricultural and Resource Markets
Geography and Spatial Analysis
- GEOG 512 – Environmental Modeling and Geospatial Analysis
- GEOG 513 – Advanced Remote Sensing
- GEOG 517 – Database Design for Spatial Data Science
- GEOG 518 – GIS Project Management
Industrial Engineering
- IE 516 – Statistical Methods in Industrial Engineering
- IE 522 – Optimization Methods in Industrial Engineering
- IE 565 – Applied Data Science
- IE 566 – Optimization for Big Data
Computer Science
- COSC 522 – Machine Learning
- COSC 523 – Artificial Intelligence
- COSC 526 – Data Engineering
Students interested in the Data Science area may incorporate appropriate graduate coursework in business analytics and related quantitative fields.
Course availability, delivery format, prerequisites, and applicability to an individual student’s program should be confirmed with the School of Natural Resources.
