IDEAS home Printed from https://ideas.repec.org/a/caa/jnljfs/v61y2015i12id51-2015-jfs.html
   My bibliography  Save this article

Individual tree basal area growth models for Chir pine (Pinus roxberghii Sarg.) in western Nepal

Author

Listed:
  • A. Gyawali

    (Institute of Forestry, Pokhara Campus, Tribhuwan University, Nepal)

  • R. P. Sharma

    (Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic)

  • S.K. Bhandari

    (Institute of Forestry, Pokhara Campus, Tribhuwan University, Nepal)

Abstract

The individual tree growth models are important decision-making tools in forestry. Age dependent and age independent individual tree basal area growth models were developed for Chir pine (Pinus roxberghii Sarg.) in one of the western districts, Rukum district, in Nepal. Data from thirty-five destructively sampled trees, which were representative of all possible stand densities, site productivities, age classes, and size classes of Chir pine forests in the district, were used. Sample trees were felled and diameters and ages were measured on the cut surface of the stump (at 30 cm above the ground). Since measurements from the same stump of a tree were strongly correlated, the autoregressive error structure modelling approach was applied while specifying the model in order to reduce bias. All parameter estimates of the models were significant (P < 0. 01) and the models described most of the variations of basal area growth (R2adj > 0.86). Residual graphs showed no serious systematic bias for all observed age classes and diameter classes. The age independent growth model showed relatively better fit statistics (R2adj = 0.8751, RMSE = 4.8494) than its age dependent counterpart (R2adj = 0.8668, RMSE = 5.0158). Because of being more precise and simpler, the age independent model is recommended to apply to both even-aged and uneven-aged stands of Chir pine in the district.

Suggested Citation

  • A. Gyawali & R. P. Sharma & S.K. Bhandari, 2015. "Individual tree basal area growth models for Chir pine (Pinus roxberghii Sarg.) in western Nepal," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 61(12), pages 535-543.
    • Handle: RePEc:caa:jnljfs:v:61:y:2015:i:12:id:51-2015-jfs
    DOI: 10.17221/51/2015-JFS
    as

    Download full text from publisher

    File URL: http://jfs.agriculturejournals.cz/doi/10.17221/51/2015-JFS.html
    Download Restriction: free of charge
    File URL: http://jfs.agriculturejournals.cz/doi/10.17221/51/2015-JFS.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.17221/51/2015-JFS?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pommerening, Arne & LeMay, Valerie & Stoyan, Dietrich, 2011. "Model-based analysis of the influence of ecological processes on forest point pattern formation—A case study," Ecological Modelling, Elsevier, vol. 222(3), pages 666-678.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pommerening, Arne & Szmyt, Janusz & Zhang, Gongqiao, 2020. "A new nearest-neighbour index for monitoring spatial size diversity: The hyperbolic tangent index," Ecological Modelling, Elsevier, vol. 435(C).
    2. Pommerening, Arne & Sterba, Hubert & West, Philip, 2022. "Sampling theory inspires quantitative forest ecology: The story of the relascope kernel function," Ecological Modelling, Elsevier, vol. 467(C).
    3. Pommerening, Arne & Särkkä, Aila, 2013. "What mark variograms tell about spatial plant interactions," Ecological Modelling, Elsevier, vol. 251(C), pages 64-72.
    4. Häbel, Henrike & Myllymäki, Mari & Pommerening, Arne, 2019. "New insights on the behaviour of alternative types of individual-based tree models for natural forests," Ecological Modelling, Elsevier, vol. 406(C), pages 23-32.
    5. Peters, Ronny & Lin, Yue & Berger, Uta, 2016. "Machine learning meets individual-based modelling: Self-organising feature maps for the analysis of below-ground competition among plants," Ecological Modelling, Elsevier, vol. 326(C), pages 142-151.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:caa:jnljfs:v:61:y:2015:i:12:id:51-2015-jfs. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.