Skip to main content
Log in

Small-area estimation of forest stand structure in Jalisco, Mexico

  • Research Paper
  • Published:
Journal of Forestry Research Aims and scope Submit manuscript

Abstract

Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources (i.e., forests, rangelands, grasslands, agriculture, etc.) at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in small-area analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco’s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Cochran WG. 1977. Sampling techniques. New York: John Wiley & Sons, 428 pp.

    Google Scholar 

  • DuMouchel WH, Duncan GJ. 1983. Using sample survey weights in multiple regression analysis of stratified samples. J. American Statistical Association, 78: 535–543.

    Article  Google Scholar 

  • Fay RE, Herriot RA. 1979. Estimation of income for small places: an application of James-Stein procedures to censis data. J. American Statistical Association, 74: 269–277.

    Article  Google Scholar 

  • Flores-Garnica JG, Mendoza-Briseño MA, Aguirre-Bravo C. 2007. Monitoreo de ecosistemas con estrategias geostadisticas, una aplicación de gran escala en Jalisco, Mexico. Madera y Bosques, 13: 97–104.

    Google Scholar 

  • Ghosh M, Rao JNK. 1994. Small area estimation: an appraisal. Statistical Sciences 9: 55–93.

    Article  Google Scholar 

  • Kearney M, Porter WP. 2004. Mapping the fundamental niche: physiology, climate and the distribution of a nocturnal lizard. Ecology, 85: 3119–3131.

    Article  Google Scholar 

  • Laake P. 1978. An evaluation of synthetic estimates of employment. Scandinavian Journal of Statistics, 5: 57–60.

    Google Scholar 

  • Lehtonen RP, Pahkinen E. 2004. Practical Methods for Design and Analysis of Complex Surveys. Chichester, England: John Wiley & Sons, Ltd., 360 pp.

    Google Scholar 

  • Pfeffermann D. 1999. Small area estimation — Big developments. Keynote Paper, Conference on Small Area Statistics, Riga, Latvia, August 1999.

  • Rao JNK. 1999. Some recent advances in model-based area estimation. Survey Methodology, 25: 175–186.

    Google Scholar 

  • Rao JNK. 2003. Small Area Estimation. Hoboken, New Jersey: John Wiley & Sons, 313 pp.

    Book  Google Scholar 

  • Reich RM, Aguirre-Bravo C, Bravo VA. 2008a. New approach for modeling climatic data with applications in modeling tree species distributions in the States of Jalisco and Colima, Mexico. Journal of Arid Environments, 72: 1343–1357.

    Article  Google Scholar 

  • Reich RM, Aguirre-Bravo C, Mendoza-Briseño MA. 2008b. An Innovative approach to inventory and monitoring of natural resources in the Mexican State of Jalisco. Journal of Environmental Monitoring and Assessment, 146: 383–396

    Article  Google Scholar 

  • SEDER-FIPRODEFO. 2007. Inventario y Monitoreo de los recursos Naturales del Estado de Jalisco-Reporte 2006. Gobierno del Estado de Jalisco, Secretaria de Desarrollo Rural (SEDER), Fideicomiso para la Administración del programa de Desarrollo Forestal (FIPRODEFO), Guadalajara, Jalisco, Mexico., Schreuder HT, Gregoire TG, Wood GB. 1993. Sampling methods for multiresource forest inventory. New York: John Willey and Sons, Inc. 464 pp.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robin M. Reich.

Additional information

Biography: Dr. Robin M. Reich (1954–), male, is a professor of forest biometrics/spatial statistics in the Department of Forest, Rangeland and Watershed Stewardship at Colorado State University. Dr. Reich is an expert in the application of spatial statistics in designing natural resource inventories and ecosystem modeling.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Reich, R.M., Aguirre-Bravo, C. Small-area estimation of forest stand structure in Jalisco, Mexico. Journal of Forestry Research 20, 285–292 (2009). https://doi.org/10.1007/s11676-009-0050-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11676-009-0050-y

Key words

Navigation