Land-Use/Land-Cover Change and Ecosystem Service Provision in Qinghai Province, China: From the Perspective of Five Ecological Function Zones

Abstract

Qinghai Province is an important part of the Qinghai-Tibet Plateau and has special importance in the construction of ecological civilisation in China, which is related to the ecological security of the country and long-term development. The land is the basis of terrestrial ecosystem services. Land use/cover change (LUCC) can alter the structure, distribution and processes of terrestrial ecosystems, thereby affecting ecosystem services. Ecological Function Zone (EFZ) is the special zone designated by the government to protect ecosystems more effectively. Studying the response of ecosystem services value (ESV) to LUCC within EFZ is of great significance to the construction of ecological civilization in Qinghai Province. This study uses five periods of land use data from 1980 to 2020 and selects the equivalent factor method, correction method and elasticity model to analyse the characteristics of land use change and its impact on the value of ecosystem services. The conclusions are as follows. (1) The results showed that the ESV of Qinghai Province decreased from 822.559 billion yuan in 1980 to 819.903 billion yuan in 2000, and then increased rapidly to 905.775 billion yuan in 2020, showing a total increase of 83.216 billion yuan (1 RMB equates to 0.144129 USD). The restoration of grassland and the expansion of water bodies are the main reasons for the growth of ESV. (2) The ESV of Sanjiangyuan EFZ was the highest, followed by Qaidam EFZ, Qinghai Lake EFZ and Qilian Mountains EFZ, while Hehuang EFZ was the lowest. (3) The elasticity of the ESV to LUCC generally declined in all EFZs. Every 1% change in the LUCC in the Qaidam EFZ will result in a 4.78% change in ESV, followed by the Sanjiangyuan EFZ (2.56%), Qilian Mountains EFZ (2.1%), Qinghai Lake EFZ (1.01%), and the Hehuang EFZ with the lowest elasticity index (0.53%). (4) The distribution of the high values of the ESV elasticity gradually expands, with a clear spatial distribution characteristic of high west and low east. (5) The most suitable area for urban construction in Qinghai Province is the Hehuang EFZ, and urban construction in the Qaidam EFZ should avoid encroaching on water bodies or polluting water sources. The conclusions can provide a reference for optimising the land use structure and harmonising conservation and development in Qinghai Province.

Land Use and Land Cover Change Effects on the Value of Ecosystem Services in the Konqi River Basin, China, under Ecological Water Conveyance Conditions

“…Moreover, the small area of cropland in the lower reaches leads to a low functional value of food production. These findings are consistent with other studies conducted elsewhere [49][50][51][52]. The low-value areas are predominantly located in environmentally vulnerable regions that are challenging to develop and utilize.…”

Assessing the Sustainability Impacts of the Xiaolangdi Dam: Land Use and Socioeconomic Change in the Middle and Lower Reaches of the Yellow River Basin

“…At the same time, 207 thousand km 2 of barren mountains and wasteland have undergone afforestation, thus alleviating and improving the deteriorating ecological environment and ecosystem functions [24]. For the reasons above, the declining trend of grassland in the study areas from 2010 to 2020 has slowed down.…”

Assessment of Ecotourism Environmental Carrying Capacity in the Qilian Mountains, Northwest China

“…Natural ecological environment support is mainly influenced by three indicators: biological richness index, water yield, and landscape diversity, with their weights being 0.250, 0.243, and 0.185, respectively (Table 1). The southeast region of QLMs has higher natural ecological environment support than the northwest region (Figures 1b and 5a-c), mainly due to the higher biological richness index and stronger water conservation function in the southeast region (Figure 2d,e) [30,31]. From the perspective of socio-economic pressure, the socio-economic pressure in the southeast counties was higher, mainly due to the higher population density, percentage of the tertiary sector, road network density, and number of schools in these regions (Figure 3a,c-e).…”