The Report, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply (generally referred to as the Billion-Ton Study or 2005 BTS), was an estimate of “potential” biomass within the contiguous United States based on numerous assumptions about current and
future inventory and production capacity, availability, and technology. In the 2005 BTS, a strategic analysis was undertaken to determine if U.S. agriculture and forest resources have the capability to potentially produce at least one billion dry tons of biomass annually, in a sustainable manner—enough to displace approximately
30% of the country’s present petroleum consumption. To ensure reasonable confidence in the study results, an effort was made to use relatively conservative assumptions. However, for both agriculture and forestry, the resource potential was not restricted by price. That is, all identified biomass was potentially available, even though some potential feedstock would more than likely be too expensive to actually be economically available.
In addition to updating the 2005 study, this report attempts to address a number of its shortcomings

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U.S. Billion-ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry

This book attempts to make growth models more accessible to foresters and others interested in mixed forests, whether planted or natural. There is an increasing interest in,
 and controversy surrounding the use of mixed plantations and natural forests, and rational discussion and resolution of management options require reliable growth models linked to other
 information systems. It is my hope that this book will help researchers to build better models, and will help users to understand how the models work and thus to appreciate their strengths
 and weaknesses. During recent years, vast areas of natural forest, especially in the tropics, have been logged or converted to other uses. Well-meaning forest managers have often been
 over-optimistic in estimating forest growth and yields, and this has contributed to over-cutting in some forests. Growth models can provide objective forecasts, offering forest managers the
 information needed to maintain harvests within the sustainable capacity of the forest, and providing quantitative data for land use planners to make informed decisions on land use
 alternatives. In this way, I hope that this book will contribute to the conservation and sustainable management of natural forests in the tropics and elsewhere. This is not a "How to do it"
 manual with step-by-step instructions to build a growth model for mixed forests. Unfortunately, modelling these forests isn't that easy. There is no single "best" way to build a model for
 these forests. Rather, many approaches can be used, and the best one depends on the data available, the time and expertise available to build the model, the computing resources, and the
 inferences that are to be drawn from the model. So instead of writing a "cookbook" with one or two recipes, I review and illustrate some of the many approaches available, indicate the
 requirements of and output from each, and highlight their strengths and limitations. The book emphasizes empirical-statistical models rather than physiological-process type models, not
 because they are superior, but because they have proven utility and offer immediate benefits for forest management. A more comprehensive treatment of all the options is beyond the scope of
 this book, which is intended to serve as a ready reference manual for those building growth models for forest management. Because of my limited linguistic ability, the material covered is
 more-or-less restricted to English-language material. I have not attempted to review all the published work on growth modelling (it would be a huge task), but have tried to highlight
 examples that may be applicable to mixed forests in tropical areas. I hope that the language and terminology used in this book will be accessible to all readers, especially those for whom
 English is a second language. The glossary may help to clarify some terms, and those that have a specific technical meaning are printed in italics the first time they are used. Readers
 should consult the glossary to clarify the meaning of these words unless they are sure of the meaning. Exercises are given at the end of each chapter to reinforce points made in the
 chapter. These are simple exercises, deliberately chosen so that they can be completed quickly with pen and paper or PC and spreadsheet, but within these constraints, I have tried to keep
 them realistic. Some exercises (e.g. 9.1 and 10.3) require more specialized statistical analyses, but many commercial statistical packages (e.g. GLIM) are suitable. Where possible, these
 exercises draw on real data, but some data were simulated to create interesting exercises with few data. Whilst my approach places more responsibility on the reader to choose and develop a
 suitable modelling methodology, I hope it will help readers gain a better understanding of modelling, which should in turn lead to better models and more reliable predictions. And I hope
 that better models will provide better information, greater understanding, and better management of mixed forests.

https://espace.library.uq.edu.au/view/UQ:8211/ModellingForestG.pdf

Modelling Forest Growth and Yield: Applications to Mixed Tropical Forests

1. Introduction.- 2. Tree Form and Stem Taper.- 3. Tree-stem Volume Equations.- 4. Tree Weight and Biomass Estimation.- 5. Quantifying Tree Crowns.- 6. Growth Functions.- 7. Evaluating Site Quality.- 8. Quantifying Stand Density.- 9. Indices of Individual-tree Competition.- 10. Modeling Forest Stand Development.- 11. Whole-stand Models for Even-aged Stands.- 12. Diameter-distribution Models for Even-aged Stands.- 13. Size-class Models for Even-aged Stands.- 14. Individual-tree Models for Even-aged Stands.- 15. Growth and Yield Models for Uneven-aged Stands.- 16. Modeling Response to Silvicultural Treatments.- 17. Modeling Wood Characteristics.- 18. Model Implementation and Evaluation.-

Modeling Forest Trees and Stands

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新しい国際学術雑誌"Forest Ecology and Management"の発行

https://www.fs.fed.us/rm/pubs_other/rmrs_2010_stape_j001.pdf

The Brazil Eucalyptus Potential Productivity Project: Influence of water, nutrients and stand uniformity on wood production

Five families of competition indices were evaluated and compared on the basis of simple correlation with loblolly pine individual tree growth and multiple correlation with growth in the presence of...

A comparison of competition measures for predicting growth of loblolly pine trees

The application of near infrared (NIR) spectroscopy to the green wood of radial samples (simulated increment cores) and the development of calibrations for the prediction of wood properties are described. Twenty Pinus taeda L. (loblolly pine) radial strips were characterized in terms of air-dry density, microfibril angle (MFA), and stiffness. NIR spectra were obtained in 10-mm steps from the radial longitudinal and transverse faces of each sample and used to develop calibrations for each property. NIR spectra were collected when the wood was green (moisture content ranged from approximately 100% to 154%) and dried to approximately 7% moisture content. Relationships between measured and NIR estimates for green wood were good; coefficients of determination (R2) ranged from 0.79 (MFA) to 0.85 (air-dry density). Differences between calibrations developed using the radial longitudinal and transverse faces were small. Calibrations were tested on an independent set. Predictive errors were relatively large for so...

Estimation of the physical wood properties of green Pinus taeda radial samples by near infrared spectroscopy

Preliminary studies based on small sample sets show that near infrared (NIR) spectroscopy has the potential for rapidly estimating many important wood properties. However, if NIR is to be used oper...

/pdf/nondestructive-estimation-of-pinus-taeda-l-wood-properties-2h8nrujtmb.pdf

Nondestructive estimation of Pinus taeda L. wood properties for samples from a wide range of sites in Georgia

The use of calibrated near infrared (NIR) spectroscopy for predicting the chemical composition of Pinus taeda L. (loblolly pine) wood samples is investigated. Seventeen P. taeda radial strips, representing seven different sites were selected and NIR spectra were obtained from the radial longitudinal face of each strip. The spectra were obtained in 12.5 mm sections from pre-determined positions that represented juvenile wood (close to pith), transition wood (zone between juvenile and mature wood), and mature wood (close to bark). For these sections, cellulose, hemicellulose, lignin (acid soluble and insoluble), arabinan, galactan, glucan, mannan, and xylan contents were determined by standard analytical chemistry methods. Calibrations were developed for each chemical constituent using the NIR spectra, wood chemistry data and partial least squares (PLS) regression. Relationships were variable with the best results being obtained for cellulose, glucan, xylan, mannan, and lignin. Prediction errors were high and may be a consequence of the diverse origins of the samples in the test set. Further research with a larger number of samples is required to determine if prediction errors can be reduced.

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Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy

The development of this model was supported by the Loblolly Pine Growth and Yield Research Cooperative and the School of Forestry and Wildlife Resources at Virginia Polytechnic Institute and State University. Cooperation from Bowater, Inc., Champion International Corp., Chesapeake Corp., Continental Forest Investments, Inc., Cavenham Forest Industries, Inc. (formerly Crown Zellerbach Corp,), Federal Paper Board Co., International Paper Co., Union Camp Corp., Westvaco Corp., Weyerhaeuser Co., Willamette Industries, Inc., North Carolina Division of Forestry, Virginia Division of Forestry, and the USDA Forest Service (by cooperative agreement) is gratefully acknowledged.

Richard F. Daniels

Papers

A comparison of competition measures for predicting growth of loblolly pine trees

Estimation of the physical wood properties of green Pinus taeda radial samples by near infrared spectroscopy

Nondestructive estimation of Pinus taeda L. wood properties for samples from a wide range of sites in Georgia

Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy

Simulation of Individual Tree Growth and Stand Development in Loblolly Pine Plantations on Cutover, Site-Prepared Areas