Identification of important biodiversity areas by InVEST model considering opographic relief: A case study of Yunnan Province, China

doi:10.13287/j.1001-9332.202112.004

Abstract

Abstract: Accurately identifying important areas of biodiversity is one of the key issues in ecology and biodiversity research, as well as an important basis for the delineation of the red line for ecologi-cal protection and territorial spatial planning. With China’s typical plateau mountainous area (Yunnan Province) as a research case, we used the net primary productivity (NPP) quantitative index method, InVEST model and InVEST model focusing on topographic relief to identify biodiversity important areas. The results showed that NPP quantitative index method was not suitable for the plateau mountainous areas with obvious vertical zonal development. The identified area contained only 26.1% of the protected areas. The InVEST model had higher identification accuracy than the NPP quantitative index method in Yunnan Province. The identified area covered 49.4% of the protected natural areas. Fragmentation was obvious in northwest Yunnan. The InVEST model focusing on topographic relief improved the identification accuracy of important areas of biodiversity, including 71.7% of nature reserves. The deficiency of NPP quantitative index method in water area identification was made up and the fragmentation problem of InVEST model was solved. The area of biodiversity important areas was 119466.94 km², accounting for 30.3% of the total land area of Yunnan Province. The spatial distribution showed a pattern of “three barriers, two zones and one region for multi-point development”.

Key words: net primary productivity (NPP) quantitative index method, InVEST model, topographic undulation, important biodiversity area, plateau mountainous area

YANG Wen-xian, LI Shi-hua, PENG Shuang-yun, LI Ying-xin, ZHAO Shou-lou, QIU Li-dan. Identification of important biodiversity areas by InVEST model considering opographic relief: A case study of Yunnan Province, China[J]. Chinese Journal of Applied Ecology, 2021, 32(12): 4339-4348.

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