Arid Zone Research ›› 2023, Vol. 40 ›› Issue (1): 111-122.doi: 10.13866/j.azr.2023.01.12

• Ecology and Environment • Previous Articles     Next Articles

Identification of priority areas for forest land expansion in Shanxi Province

MENG Na(),ZHANG Ying()   

  1. School of Economics and Management, Beijing Forestry University, Beijing 100083, China
  • Received:2022-06-10 Revised:2022-08-21 Online:2023-01-15 Published:2023-02-24

Abstract:

Over the past 70 years, large-scale afforestation activities have been conducted in arid and semi-arid areas in China with remarkable success, but localized afforestation has failed due to regional human activities and climatic influences. Although the potential for afforestation in arid areas is recognized, it is unknown in which micro-region afforestation should be concentrated. Taking Shanxi Province, a typical region of the Loess Plateau, as an example, this study constructs a framework for the identification of forestable land and uses the PLUS and Markov models to simulate land use changes under different scenarios in 2030, analyzing woodland expansion, trends in internal changes in forest stands, and spatial distribution. The results show that: The current space for woodland growth in Shanxi Province is 5.38%, and the southeast is the main potential growth area; there is a possibility of woodland degradation at the edges of woodlands in the central and western parts of the province, while the degree of woodland fragmentation in the north is higher; the frequency of intra-forest conversion is higher; in order of expansion potential, there are woodland > shrubland > open woodland > other woodlands. In this context, a cautious attitude is taken toward large-scale afforestation in Shanxi Province. This study can provide a reference for effective afforestation management and enhancement of forest carbon sequestration levels in the Shanxi Province.

Key words: PLUS model, Markov model, afforestation, scenario simulation, priority zone identification, arid and semi-arid areas