Identification of priority conservation areas in Beijing-Tianjin-Hebei using multi-scenario trade-offs based on different spatial scales and their drivers
Year: 2024
Type: article
Abstract: Beijing-Tianjin-Hebei region (BTH) is located in the centre of northern China around the Bohai Sea and is known as China's "capital economic circle". With rapid economic development and changes in land use, intensification of agriculture, and urbanization, the ecosystem that sustains human life has been severely tested. Identifying priority conservation areas (PCAs) on the basis of ecosystem services (ES) trade-offs is a crucial step in achieving optimal ecosystem management in the BTH, while ecosystems have intricate spatio-temporal and scaling effects. This study thoroughly examined the spatial and temporal variations in ESs functions across multiple scales in the BTH region, and their interrelationships from 2000 to 2020. After that, to identify PCAs at different spatial scales, the Ordered Weighted Average (OWA) was introduced to simulate multiple scenarios. Finally, we employed Geo-detector to explore the drivers of ES in PCAs. The results indicated that FS, WY, and SR in the BTH increased by 16.4×104t/hm2, 81.81mm, and 37081.29t/hm2, respectively. In contrast, CS and HQ showed a decrease, but the variation was less pronounced. The county scale demonstrated greater changes than the grid scale. The trade-offs and synergies between the five ESs exhibited analogous mechanisms of change across both scales, with spatial heterogeneity. Relationships were found to be more pronounced at the county scale than at the grid scale. The distribution of PCAs corresponding to each scenario was consistent at both scales. Scenario 6, with PCAs mainly in the northern and western of the study area, showed the most balanced conservation efficiency across ESs. PCAs had greater explanatory power for ESs by optimizing natural factors rather than socio-economic factors. The study found that the variable PRE had the greatest influence on FS, WY, and SR, while NDVI and ET were the main factors for CS and HQ. Notably, the study revealed that the explanatory power was greater at the county scale. Moreover, the explanatory power of the drivers was further enhanced by the effects of interaction factors. These findings provide valuable theoretical references for making informed decisions regarding ecosystem service management at various spatial scales.
Source: Ecological Indicators
Authors: Shanting Bi, Ze Li, Ying Chen, Qing Zhang, Teng Ye
Institution: Hebei Agricultural University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,970
OpenAlex ID: W4401628424