Factors affecting forest growth and possible effects of climate change in the Taihang Mountains, northern China

Author

1. Yonghui Yang ¹ , ^* , 
2. Masataka Watanabe ² , 
3. Fadong Li ¹ , 
4. Jiqun Zhang ³ , 
5. Wanjun Zhang ¹ and 
6. Jianwen Zhai ⁴

-Author Affiliations

1. ¹Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, No. 286, Huaizhong Road, Shijiazhuang 050021, China
2. ²National Institute for Environmental Studies, Onogawa, 16-2, Tsukuba, Ibaraki 305-8506, Japan
3. ³Water Resources Management Center, Ministry of Water Resources, 100053, Beijing, China
4. ⁴Forestry Department of Hebei Province, Shijiazhuang, Hebei 050081, China

1. *Corresponding author. E-mail: yonghui.yang@ms.sjziam.ac.cn
2. 
   
3. Received May 18, 2004.

Abstract

To estimate the possible effects of site factors and climate change on forest growth in the Taihang Mountains, northern China, we assessed the factors influencing forest growth by using forest inventory data from 712 forest sample plots. Meteorological data from 77 meteorological stations in the region were used to estimate temperature and precipitation at each site from elevation and longitude. Analyses showed that temperature, aspect, precipitation and soil thickness all significantly influenced forest growing stock (FGS), i.e. stem volume. When temperature rose, FGS was reduced, possibly because increasing temperature increased evapotranspiration. Precipitation had a positive effect on FGS. The effect of aspect on FGS was perfectly expressed as a cosine function, with south-west- and south-facing slopes having the lowest FGS and north-facing slopes having the highest. We developed multifactorial regression models to predict changes in FGS in the Taihang Mountains. Temperature, forest age, forest cover, soil thickness, precipitation and aspect were well related to FGS. The effects of a temperature decrease and a precipitation increase on FGS would be 2.5–8 per cent per degree centigrade and 10 per cent per 100 mm, respectively. The combination of temperature increase and precipitation changes under future climate change is likely to result in a decrease of FGS, though this does not take account the effect of increasing CO₂. We also used multifactorial regression models to analyse the effects of site factors on FGS of Pinus tabulaeformis Carr. and Robinia pseudoacacia L., two major species used in afforestation in the Taihang Mountains. Although site factors had similar effects on FGS, diameter at breast height and tree height of both species, prediction accuracy (regression coefficient) was improved greatly when we treated the species separately.

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