The carbon lock-in effect represents a systematic challenge to achieve the goal of carbon peaking and carbon neutrality. Identifying its spatio-temporal evolution patterns and regional transmission mechanisms is of great significance for facilitating China's low-carbon transformation. Based on an improved evaluation system, the study measured the carbon lock-in levels of 30 provinces in China from 2002 to 2022. Spatio-temporal analysis method was employed to depict their spatial patterns and evolutionary laws, and further explore their spatial association mechanisms and evolutionary trends. The results show that: The national carbon lock-in level exhibits a three-stage trend overall: a slow decline, accelerated unlocking, and gentle fluctuation. It also demonstrates an evolutionary characteristic of "eastern regions taking the lead in unlocking, central regions undergoing rapid transformation, and western regions following suit continuously" in spatial patterns. Moreover, a comprehensive spatio-temporal analysis indicates that the degree of national carbon lock-in discretization has increased, regional disparities have expanded, and a multi-polarization tendency is evident. Carbon lock-in demonstrates a significant positive spatial spillover effect. The growth rate of fixed asset investment has a positive influence on carbon lock-in in adjacent areas, while the urbanization rate and the proportion of labor compensation have substantial negative impacts. The inter-provincial carbon lock-in network interaction shows a three-stage evolutionary trend bounded by the Hu Huanyong Line and transmission characteristics of "continuous deepening of inter-provincial connections, significant polarization of hub nodes, and explicit regional transmission paths". The differentiated evolution of functional interactions between northern and southern blocks bounded by the Qinling-Huaihe Line is obvious. The prediction results indicate that the carbon lock-in level is under pressure from diminishing marginal returns and faces risks of local rebound. The key to breaking the carbon lock-in network lies in the provinces with high betweenness centrality.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |