Optimizing factor allocation is the premise of promoting high-quality development of agriculture. Based on the panel data of 31 provinces in China from 2004 to 2020, this paper examines the relationship between factor mismatch and high-quality agricultural development. We found that the high-quality development level of China’s agriculture shows a state of fluctuation and improvement, but the overall level is relatively low and the inter-provincial difference is expanding. Factor mismatch significantly inhibited the improvement of agricultural high-quality development, and the inhibition effect showed obvious temporal and spatial heterogeneity. We also found that the allocation of factors in extreme cases will lead to a 0.01% inter-provincial difference in the high-quality agricultural development. However, with the optimization and upgrading of the agricultural industrial structure and the improvement of the agricultural science and technology, the inhibitory effect of factor mismatch on high-quality agricultural development is constantly weakening. The above conclusion still holds after a series of robustness tests. The conclusions of this paper enrich the theoretical literature on the influencing factors of high-quality agricultural development, and provide an empirical reference for the policy maker of reducing factor mismatch and promoting high-quality agricultural development.

The increase in income among Chinese residents has been accompanied by dramatic changes in dietary structure, promoting a growth in carbon emissions. Therefore, in the context of building a beautiful countryside, it is of great significance to study the carbon emissions of rural residents’ food consumption to realize the goal of low-carbon food consumption. In this paper, the calculation of food consumption carbon emissions of Chinese rural residents is based on the carbon conversion coefficient method, and the spatial heterogeneity of influencing factors is analyzed with the aid of the ESDA-GWR model. The results indicate that the per capita food consumption carbon emissions of rural residents have increased by 1.68% annually, reaching 336.73 kg CO2-eq in 2020, which is 1.32 times that of 2002. Carbon emissions generated from rural residents’ food consumption have significant spatial agglomeration characteristics, showing the spatial distribution characteristics of a north–south confrontation, with a central area collapse. The influencing factors of food consumption carbon emissions have significant spatial heterogeneity, among which, as the main force to restrain the growth of food consumption carbon emissions, the price factor has a regression coefficient between −0.1 and −0.3, and its influence has weakened from northwest to southeast in 2020. The education–social factor is the main driving force for the growth of food consumption carbon emissions, with a regression coefficient between 0.58 and 0.99, and its influence has increased from east to west. In the future, formulating food consumption optimization policies should be based on the actual situation of food consumption carbon emissions in various regions to promote the realization of low-carbon food consumption.

As the most important driving force for ensuring the effective supply of grain in the country, the production stability of the major grain-producing areas directly concerns the national security of China. In this paper, considering the “water–soil–energy–carbon” correlation, water, soil and energy resource factors, and carbon emission constraints were included in an index system, and the global common frontier boundary three-stage super-efficient EBM–GML model was used to measure the grain production resource utilization efficiency of the major grain-producing areas in China from 2000 to 2019. This paper also analyzed the static and dynamic spatiotemporal characteristics and the restrictions of utilization efficiency. The results showed that, under the measurement of the traditional data envelopment analysis model, the grain production resource utilization efficiency in the major producing areas is relatively high, but there is still room to improve by more than 20%, and grain production still has enormous growth potential. After excluding external environmental and random factors, it was found that the utilization efficiency of grain production resources in the major producing areas decreased, and the efficiency and ranking of provinces changed significantly. External factors inhibit pure technical efficiency and expand the scale efficiency. The utilization efficiency of Northeast China was much higher than that of the Huang-Huai-Hai region and the middle and upper reaches of the Yangtze River region, and its grain production resource allocation management had obvious advantages. The total factor productivity index of food production resources showed an upward trend as a whole, and its change was affected by both technological efficiency and technological progress, of which technological progress had the greater impact. Therefore, reducing the differences in the external environment of different regions while making adjustments in accordance with their own potential is an effective way to further improve the utilization efficiency of food production resources.

Increasing agricultural output by reducing capital misallocation is a capital-saving strategy, as it does not require the usage of additional inputs. Based on the panel data of 36 prefecture-level cities in northeast China from 2011 to 2020, this paper uses the spatial Durbin model to test the impact of capital mismatch on agricultural output and its mechanisms. We found that capital misallocation is prevalent in prefecture-level cities, showing a spatial distribution characteristic of “north-south confrontation and central collapse”, with a significant spatial spillover effect. A one-unit increase in capital misallocation leads to a 16.00% decrease in local agricultural output and a 1.80% decrease in adjacent areas. However, with the optimization and upgrading of the agricultural industry and agricultural technology progress, the inhibitory effect of capital misallocation on the growth of agricultural output is constantly weakening. The above conclusion still holds after a series of robustness tests. The conclusion of this paper provides policy inspiration for promoting the rational allocation of factors between cities and regions, coordinating regional coordinated development, and then promoting the sustainable growth of agricultural output.

Natural Platycladus orientalis forests in the Yin Mountains are the northwestern boundary of natural Chinese P. orientalis forests and also one of the most important forests in the Yin Mountains, with respect to erosion prevention, soil conservation, water conservation, and habitat improvement. This study examined details about the characteristics of the population, community, and distribution of natural P. orientalis forests, to allow for better management as well as to provide a theoretical basis. Natural P. orientalis forests in Daqing Mountain and Wula Mountain were selected as the research subjects, and through quadrat investigations, were divided into 6 associations. Characteristics of the flora and the structure were analyzed. We also discussed the diameter structure of each association of P. orientalis and the distribution succession series between associations. The main results are as follows: (1) There were 96 vascular plants belonging to 70 genera of 30 families found in the natural P. orientalis forests, and the geographic components of species contained 8 types and 18 subtypes, which were mainly distributed in the East Pan-North Pole, followed by East Asia; (2) From the analysis of community structure, well-developed natural P. orientalis forests were characterized by a tree layer and herb layer, however the shrub was sensitive to interference, and coverage was generally lower in areas with more human interference, and could even disappear; (3) The diameter structure of P. orientalis followed a normal distribution which is a stable community type, and average plant height increased with the diameter overall growth model; (4) Due to strong interference and harsh habitats,