Reading PAGE

Peer Evaluation activity

Trusted by 1
Downloads 468
Views 31
Full text requests 5
Collected by 1
Followed by 3
Following... 3

Total impact ?

    Send a

    Jerome has...

    Trusted 0
    Reviewed 0
    Emailed 0
    Shared/re-used 0
    Discussed 0
    Invited 0
    Collected 37

     

    This was brought to you by:

    block this user Jerome K Vanclay Trusted member

    Professor

    Southern Cross University
    European Forest Institute Mediterranean Office (EFIMED)

    Modelling Forest Growth and Yield Applications to Mixed Tropical Forests

    Export to Mendeley

    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.

    Oh la laClose

    Your session has expired but don’t worry, your message
    has been saved.Please log in and we’ll bring you back
    to this page. You’ll just need to click “Send”.

    Your evaluation is of great value to our authors and readers. Many thanks for your time.

    Review Close

    Short review
    Select a comment
    Select a grade
    You and the author
    Anonymity My review is anonymous( Log in  or  Register )
    publish
    Close

    When you're done, click "publish"

    Only blue fields are mandatory.

    Relation to the author*
    Overall Comment*
    Anonymity* My review is anonymous( Log in  or  Register )
     

    Focus & Objectives*

    Have the objectives and the central topic been clearly introduced?

    Novelty & Originality*

    Do you consider this work to be an interesting contribution to knowledge?

    Arrangement, Transition and Logic

    Are the different sections of this work well arranged and distributed?

    Methodology & Results

    Is the author's methodology relevant to both the objectives and the results?

    Data Settings & Figures

    Were tables and figures appropriate and well conceived?

    References and bibliography

    Is this work well documented and has the bibliography been properly established?

    Writing

    Is this work well written, checked and edited?

    Write Your Review (you can paste text as well)
    Please be civil and constructive. Thank you.


    Grade (optional, N/A by default)

    N/A 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10
    Close

    Your mailing list is currently empty.
    It will build up as you send messages
    and links to your peers.

     No one besides you has access to this list.
    Close
    Enter the e-mail addresses of your recipients in the box below.  Note: Peer Evaluation will NOT store these email addresses   log in
    Your recipients

    Your message:

    Your email : Your email address will not be stored or shared with others.

    Your message has been sent.

    Description

    Title : Modelling Forest Growth and Yield Applications to Mixed Tropical Forests
    Author(s) : Jerome K Vanclay
    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.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 1994

    Affiliations Southern Cross University
    Volume : 58
    Issue : 2
    Publisher : CAB International
    Pages : 329
    Url : http://espace.library.uq.edu.au/view/UQ:8211

    Leave a comment

    This contribution has not been reviewed yet. review?

    You may receive the Trusted member label after :

    • Reviewing 10 uploads, whatever the media type.
    • Being trusted by 10 peers.
    • If you are blocked by 10 peers the "Trust label" will be suspended from your page. We encourage you to contact the administrator to contest the suspension.

    Does this seem fair to you? Please make your suggestions.

    Please select an affiliation to sign your evaluation:

    Cancel Evaluation Save

    Please select an affiliation:

    Cancel   Save

    Jerome's Peer Evaluation activity

    Trusted by 1
    Downloads 468
    Views 31
    Full text requests 5
    Collected by 1
    Followed by 3
    • Habiba Hassan Wassef, Senior professional, Independent international expert, United Nations, WHO, National Coordinator for the 7th European Framework Research Programme, National Research Center in Cairo, Egypt.
    • Thuy Nguyen, Student, Ph.D. Level, Silviculture Research Institute, Ha Noi, Vietnam, The University of Melbourne.
    • Guillaume Dupuy d'Angeac, Publisher, Collective Developments, HEC Alumni, Peerevaluation.
    Following... 3

    Jerome has...

    Trusted 0
    Reviewed 0
    Emailed 0
    Shared/re-used 0
    Discussed 0
    Invited 0
    Collected 37
    Invite this peer to...
    Title
    Start date (dd/mm/aaaa)
    Location
    URL
    Message
    send
    Close

    Full Text request

    Your request will be sent.

    Please enter your email address to be notified
    when this article becomes available

    Your email


     
    Your email address will not be shared or spammed.