A Composite Index-based Approach for Hierarchical Assessment of Forest Ecosystem Health: An Example of Pinus tabulaeformis

Assessing forest ecosystem health is an effective way for forest resource management. Taking as an example Pinus tabulaeformis Carr., a superior afforestation species in northern China, this study establishes a forest health assessment model and a three-level indicator system using the analytic hierarchy process. The results showed that Pinus tabulaeformis forest health is proposed for evaluation into four grades by composite index (HI), ill-health forest was 48.39% among the sample plots, and average HI was accounted for 25% of healthy forest. So Pinus tabulaeformis forest ecosystem was in development stage; additionally, at an altitude of 1500 ~ 1800 m, slope 35 ~ 40 °, Pinus tabulaeformis forest were the most healthy in western Qinling Moutain. Forest community stability change with altitude is evident unimodal curve form, stability is a downward trend when the elevation and slope is too low or too high. This evaluation indicator system is suitable for extending its application in forest health judgment. The evaluation results have certain guiding significance for regional forest management and nurturing.

[1]  Yanhong Tang,et al.  Long-term grazing alters species composition and biomass of a shrub meadow on the Qinghai-Tibet Plateau , 2006 .

[2]  Xiao Fengjin Forest Ecosystem Health Assessment Indicators and Application in China , 2003 .

[3]  E. Nelson,et al.  Impact of Forest Seral Stage on use of Ant Communities for Rapid Assessment of Terrestrial Ecosystem Health , 2010, Journal of insect science.

[4]  R. Foroughbakhch,et al.  Use of quantitative methods to determine leaf biomass on 15 woody shrub species in northeastern Mexico , 2005 .

[5]  M. E.,et al.  Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico , 2004 .

[6]  E. Allen Forest Health Assessment in Canada , 2001 .

[7]  Javier Estornell,et al.  Estimation of shrub biomass by airborne LiDAR data in small forest stands , 2011 .

[8]  J. Diem,et al.  Remote Assessment of Forest Health in Southern Arizona, USA: Evidence for Ozone-Induced Foliar Injury , 2002, Environmental management.

[9]  Hongyan Liu,et al.  Climate-growth relationships of relict Pinus tabulaeformis at the northern limit of its natural distribution in northern China , 2008 .

[10]  Guo Ning,et al.  Health evaluation on spruce and Fir forests in Miyaluo of the Western Sichuan. , 2009 .

[11]  S. Perkins,et al.  Growth and biomass allocation of shrub and grass seedlings in response to predicted changes in precipitation seasonality , 2003, Plant Ecology.

[12]  Craig J. Palmer,et al.  Forest Health Monitoring in the United States: First Four Years , 1999 .

[13]  Michael R. Wagner,et al.  Concepts of forest health: Utilitarian and ecosystem perspectives , 1994 .

[14]  S. Díaz,et al.  Shrub biomass estimation in the semiarid Chaco forest: a contribution to the quantification of an underrated carbon stock , 2013, Annals of Forest Science.

[15]  Jiangfeng Shi,et al.  Statistical and process‐based modeling analyses of tree growth response to climate in semi‐arid area of north central China: A case study of Pinus tabulaeformis , 2008 .

[16]  Marco Ferretti,et al.  Forest Health Assessment and Monitoring – Issues for Consideration , 1997 .

[17]  Luke J. Marzen,et al.  Developing a land-cover classification to select indicators of forest ecosystem health in a rapidly urbanizing landscape , 2010 .

[18]  Liu Yu,et al.  January to August temperature variability since 1776 inferred from tree-ring width of Pinus tabulaeformis in Helan Mountain , 2007 .

[19]  V. Dale,et al.  Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico , 2004 .