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Changes of forestland in China's coastal areas (1996-2015): Regional variations and driving forces

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  • Zhang, Xiaoxiang
  • Yao, Jing
  • Wang, Jing
  • Sila-Nowicka, Katarzyna

Abstract

Coastal forests play a critical role in the defence of natural disasters like typhoons and tsunamis. The deforestation and forest degradation due to rapid urbanization has presented great challenges (e.g. debris flows and floods) to China’s coastal areas. Using a unique national land-use survey dataset and geographical information system (GIS)-based spatial analytics, including local Moran’s I and geographically weighted regression (GWR), this paper investigates the regional variations and associated driving forces of forestland changes in China’s coastal areas across three periods: 1996−2000, 2000–2008 and 2009–2015. The results suggest that the forestland has generally increased until 2008 and has decreased since 2009. Particularly, some counties in the south coast have higher degree of forestland loss during 1996–2008 and the growth of forestland after 2009 was only found in a few counties in the north and east coast. Also, the results indicate that the initial proportion of forestland in each period and the changes of arable-land have significant positive associations with the forestland changes across all the three periods, where the former mainly affects the northern coast while the latter has a primary influence in the southern coast. The findings suggest that government policies for increasing forestland such as the “Grain for Green” project were highly effective in China’s coastal areas before 2008 but have shown less impact ever since. This research provides insights into the dynamics of forestland in China’s coastal areas and can assist with future decision-making regarding forest resources protection and management.

Suggested Citation

  • Zhang, Xiaoxiang & Yao, Jing & Wang, Jing & Sila-Nowicka, Katarzyna, 2020. "Changes of forestland in China's coastal areas (1996-2015): Regional variations and driving forces," Land Use Policy, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:lauspo:v:99:y:2020:i:c:s0264837720305378
    DOI: 10.1016/j.landusepol.2020.105018
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    References listed on IDEAS

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    1. Gollini, Isabella & Lu, Binbin & Charlton, Martin & Brunsdon, Christopher & Harris, Paul, 2015. "GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i17).
    2. A. Fotheringham & Ricardo Crespo & Jing Yao, 2015. "Exploring, modelling and predicting spatiotemporal variations in house prices," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 417-436, March.
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