Jerome K. Vanclay

Bio: Jerome K. Vanclay is an academic researcher from Southern Cross University. The author has contributed to research in topics: Forest management & Logging. The author has an hindex of 47, co-authored 300 publications receiving 10665 citations. Previous affiliations of Jerome K. Vanclay include University of the Sunshine Coast & Center for International Forestry Research.

Modelling Forest Growth and Yield: Applications to Mixed Tropical Forests

Abstract: 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.

Sustaining conservation values in selectively logged tropical forests: the attained and the attainable

Abstract: Most tropical forests outside protected areas have been or will be selectively logged so it is essential to maximize the conservation values of partially harvested areas. Here we examine the extent to which these forests sustain timber production, retain species, and conserve carbon stocks. We then describe some improvements in tropical forestry and how their implementation can be promoted. A simple meta-analysis based on >100 publications revealed substantial variability but that: timber yields decline by about 46% after the first harvest but are subsequently sustained at that level; 76% of carbon is retained in once-logged forests; and, 85‐100% of species of mammals, birds, invertebrates, and plants remain after logging. Timber stocks will not regain primary-forest levels within current harvest cycles, but yields increase if collateral damage is reduced and silvicultural treatments are applied. Given that selectively logged forests retain substantial biodiversity, carbon, and timber stocks, this “middle way” between deforestation and total protection deserves more attention from researchers, conservation organizations, and policy-makers. Improvements in forest management are now likely if synergies are enhanced among initiatives to retain forest carbon stocks (REDD+), assure the legality of forest products, certify responsible management, and devolve control over forests to empowered local communities.

Forest site productivity: a review of the evolution of dendrometric concepts for even-aged stands

Abstract: Summary Forest site productivity is the production that can be realized at a certain site with a given genotype and a specifi ed management regime. Site productivity depends both on natural factors inherent to the site and on management-related factors. This review of the evolution of site assessment highlights three tenets of forest site productivity: the height – age site index, Eichhorn’s rule and the thinning response hypothesis. These tenets rely on the hypotheses that height growth correlates well with stand volume growth, that total volume production of a given tree species at a given stand height should be identical for all site classes and that stand volume growth is independent of thinning practice for a wide range of thinning grades. The maturation of long-term fi eld experiments has provided for the revision of these hypotheses, and contributed to an understanding of situations where they do not hold. This led to the introduction of the concept of yield level, the stand volume growth per unit of height growth. The use of the yield level theory for estimating site productivity has facilitated the development of a three-dimensional model of the relationship between stem number, quadratic mean diameter and stand basal area. Given this model, a stand density index based on the combination of stem number and quadratic mean diameter provides an indication of the yield level, which may be used to adjust height-age – based estimates of site productivity.

Out of the Crisis

Abstract: According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

国际刊物《Scientometrics》文献计量研究

Abstract: 本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。