Reading PAGE

Peer Evaluation activity

Trusted by 1
Downloads 463
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)

    Mortality functions for north Queensland rain forests

    Export to Mendeley

    Subjective a priori grouping of tropical rain forest species for growth prediction may be unreliable because 1) there may be hundreds of species, many comparatively uncommon, the ecology of which may not be well known, 2) species within the same genus may have significantly different growth patterns, and 3) growth rate may not provide a reliable indication of mortality. Growth models can retain the species identity of each simulated tree, but some aggregation is necessary to enable estimation of increment and mortality functions. An objective approach aggregated 100 rain forest tree species into ten groups to enable efficient estimation of mortality functions. This strategy provided better predictions than a previous subjective grouping. Annual survival probabilities were predicted from tree size, stand density and site quality using a logistic equation fitted by maximum likelihood estimation. Additional species with insufficient data for analysis were subjectively assigned to these ten equations. Several strategies were investigated; the best approach for these species seemed to be to employ the equation which served the greatest number of species. The increment pattern did not provide a good basis for assigning such species to equations, and this suggests that different groupings may be necessary to model the various components of tree growth.

    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 : Mortality functions for north Queensland rain forests
    Author(s) : J K Vanclay
    Abstract : Subjective a priori grouping of tropical rain forest species for growth prediction may be unreliable because 1) there may be hundreds of species, many comparatively uncommon, the ecology of which may not be well known, 2) species within the same genus may have significantly different growth patterns, and 3) growth rate may not provide a reliable indication of mortality. Growth models can retain the species identity of each simulated tree, but some aggregation is necessary to enable estimation of increment and mortality functions. An objective approach aggregated 100 rain forest tree species into ten groups to enable efficient estimation of mortality functions. This strategy provided better predictions than a previous subjective grouping. Annual survival probabilities were predicted from tree size, stand density and site quality using a logistic equation fitted by maximum likelihood estimation. Additional species with insufficient data for analysis were subjectively assigned to these ten equations. Several strategies were investigated; the best approach for these species seemed to be to employ the equation which served the greatest number of species. The increment pattern did not provide a good basis for assigning such species to equations, and this suggests that different groupings may be necessary to model the various components of tree growth.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 1991

    Affiliations Southern Cross University
    Journal : Journal of Tropical Forest Science
    Volume : 4
    Issue : 1
    Pages : 15-36
    Url : http://www.mendeley.com/catalog/mortality-functions-north-queensland-rain-forests/

    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 463
    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.