Yafen He

【目的】国外消费引致的出口贸易是导致中国碳排放增长的重要原因，明确出口贸易对碳排放的影响，能够为碳减排提供新的思路。【方法】本文基于2005—2022年中国281个地级及以上城市的面板数据，检验了出口贸易对城市碳排放的影响，并使用调节效应模型探究了地理区位特征和地理气候特征在其中所起的作用，最后借助空间杜宾模型分析了出口贸易碳排放效应受地理相关性的影响。【结果】①出口贸易显著正向影响城市碳排放，在其他条件不变的情况下，出口贸易额每增加1倍，碳排放增加0.37 Mt，即出口贸易显著促进了中国城市碳排放的增长。②出口贸易碳排放效应存在明显的南北异质性，北方城市的出口贸易碳排放效应相对更大，且北方城市之间呈现显著的东中西部梯度分异；海拔和气温对出口贸易碳排放效应具有负向调节作用，气压对出口贸易碳排放效应具有正向调节作用。③出口贸易对城市碳排放的影响存在显著的空间溢出效应，即一个城市的出口贸易会对周边城市的碳排放产生影响，并且本城市碳排放受周边城市出口贸易的间接影响大于自身出口贸易所带来的直接影响。【结论】出口贸易碳排放效应存在显著的地理差异性和空间溢出性，且后者尤为突出。为实现“双碳”目标，应推行差异化的城市碳减排政策，构建跨区域碳排放协同治理网络。

The bidirectional empowerment between value realization of ecological products and rural cultural revitalization is an important proposition for comprehensively advancing rural revitalization. Based on the "human-culture-technology-industry-institution" five-dimensional synergy framework to systematically explore the fundamental logic, operational mechanisms, and key strategies for the bidirectional empowerment between the value realization of ecological products and rural cultural revitalization. The study reveals that ecological resources and rural cultural exhibit inherent symbiosis. The bidirectional empowerment of the value realization of ecological products and rural cultural revitalization embodies the unification of theoretical inevitability, institutional necessity, and practical feasibility. This synergy is achieved through three mechanisms: resource integration, economic incentives, and cultural identity reconstruction. To address the practical challenges of bidirectional empowerment, we propose the following key pathways: multiple actors cultivation and incentive pathway; cultural conservation and innovation-driven pathway; digital technology empowerment for the entire chain pathway; ecocultural industry value-added pathway; planning leadership and policy coordination pathway.

Integrating the landscape pattern holistically and identifying priority areas for ecological restoration scientifically are the key challenges of national land space planning and ecological protection. Taking Xiushui County, a fragile ecological region in the south, as an example, this study established an evaluation index system based on the pattern-process principle, including the importance of ecosystem services and ecosystem sensitivity, and explored regional priority areas for ecological restoration through GIS spatial analysis technology. The results show that the ecological restoration priority area in the case study area is 2880.64 km2 in total, covering 63.93% of the overall area. Of that amount, 367.55 km2 is the bottom-line priority areas for ecological restoration, accounting for 8.16%. Regarding land use types within the major ecological restoration priority area, the arable land and construction land areas are 210.83 km2 and 122.52 km2, covering 55.35% and 51.43% of the overall area, respectively. Determining the priority areas at different levels can help decision-makers to prioritize the restoration needs of degraded areas and provide a basis for adopting targeted ecological restoration measures for areas with different degrees of degradation. Identifying priority areas also provides basic information for the protection and construction of the eco-security pattern of the territorial space, which is vital for improving the regional ecological environmental safety and building a harmonious community between humans and nature.

Ecological land is constantly modified by agriculture and construction, which leads to soil erosion, land degradation, soil pollution flood disasters, and many other land ecological security problems, threatening sustainable development. Few studies have been made to construct a land‐use ecological security pattern (LUESP) aimed at achieving urban expansion, food security, and ecological security from the perspective of land‐use needs. This study seeks to provide decision makers with the choice of multi‐scenario LUESPs by simulating the LUESP under different scenarios, offering a reasonable land‐use ecological security regulation strategy. In this paper, the ecological security evaluation method was used to identify key ecological space of a study area and the scenario analysis method was used to set up three security scenarios: ideal security (IS) scenario, satisfactory security (SS) scenario, and bottom‐line security (BS) scenario, thereby constructing the constrained cellular automata (CA) model of the LUESP and simulating the LUESPs under three security scenarios for Xingguo County, China. The results showed that the LUESP construction land index and arable land index did not exceed the total amount of the General Plan of Land Use in Xingguo County under the three security scenarios. Moreover, both key ecological space loss and landscape fragmentation degree were greatly reduced, the ecological patches tend to cluster, and the anti‐jamming ability of the landscape pattern was enhanced. The ranking of LUESPs under three security scenarios was as follows: BS scenario > SS scenario > IS scenario. These results implied that the LUESPs met the demand for land in Xingguo County for ecological security, food security, and economic development, while space occupied is different under three security scenarios. The decision makers can adopt appropriate land‐use ecological security regulation strategies according to the future development plans of the region.

Landscape morphology can reflect the spatial behavior of land use. Using the Poyang Lake area as an example, the landscape pattern characteristics in 1995, 2000, 2015, and 2018 are determined by calculating the fractal dimension, fractal stability, patch density, patch shape fragmentation, and landscape isolation, and fractal theory is used to analyze the spatial behavior of land use. The results show that building land was the land use type which consistently had the highest fractal dimension, but the fractal dimension of building land shows a downward trend, indicating that the spatial form of building land gradually developed in an orderly direction under the action of land use spatial behavior. Paddy, dryland, and forested land were the land use types which always had the lowest fractal dimension, and they are in unstable states. The calculation results of patch density, patch shape fragmentation index, and landscape isolation index supported the conclusions of the fractal analysis. One recommendation for realizing the rational layout of the land is to reduce the fractal dimension of building land through scientific and reasonable planning and to guide the orderly development of building land. For natural landscapes such as forested land, shrub forest land, high-coverage grassland, and water area, their fractal dimensions should be increased to reduce human interference and maintain their stability. Finally, the results of this study suggest that the fractal dimension should be introduced into the National Spatial Planning, and used as an index for evaluating the rationality of the regional land use pattern.

In the context of high-quality economic development and coordinated regional development, this paper measures the urban land use efficiency of 275 prefecture-level cities in China from 2003 to 2016, taking into account the unexpected output (environmental pollution), and explores the temporal and spatial evolution of urban land use efficiency through kernel density estimation and spatial autocorrelation analysis. The results show that: (1) From 2003 to 2016, China's urban land use efficiency showed an overall fluctuating growth, but it remained at a low level. The mean value of urban land use efficiency has been gradually decreasing in east, west and central regions. (2) In the whole country and the eastern, central and western regions, the regional differences have been increasing, and the efficiency values of the whole country and the east have become polarized. (3) Urban land use efficiency shows a weak spatial positive correlation, but the degree of spatial agglomeration is increasing. High-high agglomeration areas are mostly distributed in the southeastern coastal areas, and extend into the central region, while most of the high-low polarized areas are the capital cities of the central and western regions. The low-high depressed areas are scattered around the high-value accumulation areas, some of which have turned into high-high agglomeration areas during the study period, while the low-low homogeneous areas are mainly distributed in the central, western and northeastern regions. Therefore, it is proposed that strengthening the utilization of urban stock land, strengthening the regional cooperation mechanism, and formulating policies which improve the efficiency of land use are effective ways to promote the intensive and economical use of urban land, as well as regional coordinated development.

Loss of biodiversity due to the insufficient conservation of resources caused by land use is a serious problem humankind is facing. It is important to determine the priorities of biodiversity conservation. Based on the construction of an identification framework for a priority biodiversity conservation area, Xingguo County, a typical county administrative unit in the southern forested area of China, is used as an example. First, this paper constructs the priority identification framework for regional biodiversity conservation based on MCDA methods. Second, it adopts the InVEST-habitat quality model to evaluate the habitat quality in 2015. Third, factors such as elevation, slope, distance to nearest road and revenue loss for the forestry industry are selected to reflect the transportation cost, infrastructure cost, and opportunity cost of biodiversity conservation in the study area. By spatializing these factors and assigning weights to them, a spatial pattern of the biodiversity conservation costs in the study area is constructed. Last, a priority biodiversity conservation area is determined by an overlaid habitat quality map and the spatial pattern of conservation costs. The first priority area covers 620.61 km2, accounting for 19.31% of the total area of Xingguo County. Through well-financed biodiversity measures, the second and third priority areas can be selected using a stepwise approach. Our study may provide ideas and technical methods to help underdeveloped areas to achieve effective protection of biodiversity.