Abstract

The trade-off and synergy relationship between ecosystem services (ESs) and human well-being (HWb) in the land-use process has become a research hotspot. The evolutionary process and regional contribution of the accurate quantification of ESs and HWb can provide a reference for government departments to formulate macroeconomic policies. Therefore, this study first constructed an analysis framework to identify the synergistic states/evolutionary stages of the gross ecosystem product (GEP) per capita (PGEP) and gross domestic product (GDP) per capita (PGDP) and the regional contribution of the GEP–GDP synergy of 362 municipal units in mainland China from 2000 to 2015. We did this by employing the Markov transition probability matrix, land use data, and economic data based on satellite remote sensing images. The findings of this study show that (1) the PGEP of the Chinese mainland has a remarkable spatial divergence featuring a higher value in the northwestern Chinese mainland and a lower value in the southeastern Chinese mainland on both sides of the Hu Line during the investigation period; despite the eastern Chinese mainland having a higher PGDP, the PGDP at the national level is distributed in dispersion on both sides of the Hu Line; (2) during the first half of the investigation period, the GEP–GDP synergy in the Chinese mainland was generally in the pseudo-synergy stage or the transition stage from pseudo-synergy to primary/intermediate synergy, while in the second half of the period, the GEP–GDP synergy in the Chinese mainland continued to improve; (3) the GEP–GDP synergy was relatively stable on the Chinese mainland during the investigation period, with 24.28% of the units shifting to a lower or higher level synergy, and the GEP–GDP synergy was more stable in the western and central Chinese mainland, while it was more likely to shift to a higher state in the northeastern and eastern Chinese mainland. This study suggests that the GEP–GDP relationship varies with spatial scales; a hierarchical, multiscale approach is necessary to study and improve both of these relationships, as simply extrapolating policies across single administrative levels may lead to unintended outcomes.

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