Skip to main content

Projecting Diameter Growth in Tropical Trees: A New Modeling Approach

Buy Article:

$21.50 plus tax (Refund Policy)

An important and heretofore unresolved challenge in forestry has been how to project long-term tree growth (i.e., decades to hundreds of years) from short-term measurements (here 1 year) for trees that do not present annual growth rings in their trunk wood. Such a method is crucial in the lowland tropics, where few long-term growth measurements have been taken, and where frequently trees lack reliable annual growth rings because of the lack of winters or highly seasonal dry periods. The new piecewise linear (PL) growth model, developed in this article, relates logarithmic relative growth to trunk diameter. Having obtained the coefficients from piecewise linear regression, the long-term age-diameter curve is calculated, i.e., the expected average growth curve of a statistical population of individual trees. The model is applied to the following five tree species without annual growth rings from the tropical rainforest in Los Tuxtlas (Veracruz, Mexico): Aspidosperma megalocarpon, Cordia alliodora, Dialium guianense, Guarea grandifolia, and Persea schiedeana. Using the tools of multiple linear regression, the PL model is highly flexible to derive sigmoid, exponential, and over-exponential growth separately for different diameter segments. FOR. SCI. 50(2):213–224.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Bootstrap; environmental management; exponential integral; forest; forest management; forest resources; forestry; forestry research; forestry science; multiple linear regression with fixed intercept; natural resource management; natural resources; piecewise linear regression carried out as multiple linear regression

Document Type: Regular Article

Affiliations: 1: Estación de Biología Tropical “Los Tuxtlas” Universidad Nacional Autónoma de México (UNAM) Apartado postal 94 San Andrés Tuxtla Veracruz Mexico 95701 Phone: 52-29494-26623 [email protected], Email: [email protected] 2: Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS) UNAM Apartado postal 20-726, Administración 20, Delegación Álvaro Obregón México D.F. Mexico 01000 Phone: 52-55-5622-3595 [email protected], Email: [email protected]

Publication date: 2004-04-01

More about this publication?
  • Important Notice: SAF's journals are now published through partnership with the Oxford University Press. Access to archived material will be available here on the Ingenta website until March 31, 2018. For new material, please access the journals via OUP's website. Note that access via Ingenta will be permanently discontinued after March 31, 2018. Members requiring support to access SAF's journals via OUP's site should contact SAF's membership department for assistance.

    Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more