Spatial autocorrelation in land use type and ecosystem service value in Hainan Tropical Rain Forest National Park

Abstract

National parks promote the protection of the ecological environment and global biodiversity conservation. However, the changes in land use obviously damages the natural habitat, leading to habitat fragmentation and degradation. Land use changes affect ecosystem service value (ESV) and its spatial distribution. In this study, a framework for the assessment of regional spatial patterns in land use/cover changes (LUCC) and ESV was established; the framework relies on the application of a classical spatial autocorrelation model. Remote sensing data for Hainan Tropical Rain Forest National Park (HNTRFNP) were used as a test case for the autocorrelation model approach to analyzing spatial patterns in ESV. Across HNTRFNP, ESV averaged 6201.44 million USD, with high ESV seen in aquatic and forested areas. Furthermore, land use types in HNTRFNP showed spatial autocorrelation (P < 0.05), though the extent varied among types. Forests and water exhibited the most aggregation. The ESV showed significant spatial autocorrelation (P < 0.05). High ESV clusters occurred in primary tropical rainforests (i.e., Bawangling, Jianfengling, Wuzhishan, and Yinggeling) and aquatic areas (i.e., Changhua river, Daguangba reservoir, Nandu river, Taiping reservoir, Xiaomei reservoir, and Wanquan river tributaries). Low ESV areas occurred in villages and surrounding farmlands. There was a negative correlation (P < 0.05) between land use intensity and ESV. In conclusion, to heighten the ESV of HNTRFNP, we should return farmlands to forest, carry out relocation projects in key areas, and construct migration corridors to expand key species habitat.

Keywords

• Land use
• Ecosystem service value
• Tropical rainforest
• National park
• Hainan