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Decision Methods for Forest Resource Management
Decision Methods for Forest Resource Management focuses on decision making for forests that are managed for both ecological and economic objectives. The essential modern decision methods used in the scientific management of forests are described using basic algebra, computer spreadsheets, and numerous examples and applications. Balanced treatment is given throughout the book to the ecological and economic impacts of alternative management decisions in both even-aged and uneven-aged forests. In-depth coverage of both ecological and economic issues Hands-on examples with Excel spreadsheets; electronic versions available on the authors' website Many related exercises with solutions Instructor's Manual available upon request
Buongiorno Italia! Course Book (new Edition)
BBC course for beginners.
The Global Forest Products Model
The Global Forest Products Model (GFPM) book provides a complete introduction to this widely applied computer model. The GFPM is a dynamic economic equilibrium model that is used to predict production, consumption, trade, and prices of 14 major forest products in 180 interacting countries. The book thoroughly documents the methods, data, and computer software of the model, and demonstrates the model's usefulness in addressing international economic and environmental issues. The Global Forest Products Model is written by an international multi-disciplinary team and is ideal for graduate students and professionals in forestry, natural resource economics, and related fields. It explains trends ...
Outlook to 2060 for World Forests and Forest Industries
Four RPA scenarios corresponding with scenarios from the Third and Fourth Assessments of the Intergovernmental Panel on Climate Change were simulated with the Global Forest Products Model to project forest area, volume, products demand and supply, international trade, prices, and value added up to 2060 for Africa, Asia, Europe, North America, Oceania, South America, and selected countries. Scenario A1B presents a 5.5-fold increase in world fuelwood use that leads to high prices of fuelwood and industrial roundwood, driven by especially strong demand in Asia for large imports from South America and Europe. World roundwood consumption reaches 11.2 billion m3 in 2060, exceeding the increment of...
Global forest sector outlook 2050: Assessing future demand and sources of timber for a sustainable economy
The global threats to climate, biodiversity and a healthy environment are mainly caused by the excessive use of non-renewable materials. The Food and Agriculture Organization of the United Nations (FAO), in collaboration with the International Tropical Timber Organization (ITTO) and Unique Consultancy, elaborated a Global Forest Sector Outlook 2050 to assess the capacity of wood supply to support a sustainable bioeconomy. The report presents a business-as-usual scenario, based on the Global Forest Products Model (GFPM), and a bioeconomy scenario based on the impact of increased consumption of two wood products consolidated in the market: mass timber and manmade cellulose fiber. The publication assesses the market outlook for demand for primary processed wood products, demand and supply of industrial roundwood, wood energy, and forest employment and investments. From a deman-driven perspective, it discusses the actual forest resource base and production needs to supply future demand by factoring in the use of wood residues and enhanced productivity in the forest sector, as well as the influence of megatrends and policy objectives.
Predictor Sort Sampling, Tight T's, and the Analysis of Covariance
In recent years wood strength researchers have begun to replace experimental unit allocation via random sampling with allocation via sorts based on nondestructive measurements of strength predictors such as modulus of elasticity and specific gravity. Although this procedure has the potential of greatly increasing experimental sensitivity, as currently implemented it can easily reduce sensitivity. In this paper we discuss the problem and we present solutions. Given the existence of nondestructive measurements of strength predictors, our methods can be used to reduce sample sizes. We have written a public domain computer program that implements the methods.
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