Exploring the eco-efficiency of cultivated land utilization and its influencing factors in black soil region of Northeast China under the goal of reducing non-point pollution and net carbon emission

Abstract

To realize maximum benefits and minimize environment pollution, the eco-efficiency of cultivated land utilization(ECLU) is becoming a vital indicator in weighing the rationality of regional land use. Scientific analysis of spatial-temporal pattern variations, as well as factors influencing the ECLU, is of great significance to cultivated land protection, economic development and ecological environment protection in black soil region of Northeast China, and has become a global strategic issue related to the sustainable development. However, assessments of the indicators are still incomplete, the lack of information may inhabit planning guideline for the sustainable development of cultivated land resources. Thus, this study attempts to fill the gaps by incorporating the net carbon sink and non-point source pollution emissions into the measurement framework of ECLU. The super-efficiency SBM model with undesirable output and the Malmquist-Luenberger(ML) index were used to measure the ECLU and changes in the total factor productivity(TFP) of cultivated land use in the Songnen Plain from 1989 to 2019. Moran index and LISA clustering was used to reveal spatital correlation of ECLU, and Kernel density estimation and trend surface analysis maps were drawn to analyze variation tendency of the ECLU. Geographical detector model was employed to further analyze the influencing factors of ECLU. The study results revealed that:(1)The ECLU showed an overall development trend of "rising first and then declining", all of which were below the frontier efficiency. (2)The polarization of ECLU is prominent, and the ECLU had a significant heterogeneity and spatital correlation. (3)The TFP showing an increasing trend, technological progress is the main driving force to promote the progress of TFP, while the technological efficiency is the bottlenecks for the increasing the TFP of the cultivated land use. (4)According to the magnitude of influencing factor, increasing agricultural science and technology investments, lowering carbon emission, and controlling agrochemical investment could significantly enhance the ECLU. These findings have important implications for promoting high-efficient, low-carbon utilization of cultivated land resources and sustainable regional development in black soil region of Northeast China.

Analysis of spatial and temporal pattern changes and spatial spillover effects of regional agricultural carbon emission efficiency-Taking the Yangtze River Economic Belt as an example

“…Some scholars have used kernel density estimation to visually show the dynamic evolution of the time series of ACEE in China (Zhang et al 2023) to analyze the time evolution of provincial cultivated land e ciency in China (Kuang et al 2020) and evaluate agricultural environmental e ciency (Muchen et al 2022). Literatus examined the local and global spatial correlations of the overall factor productivity of agriculture in green areas using hotspot analysis and Moran's I index approach (Bao et al 2023), employing the Markov chain transfer probability matrix approach and Moran's I index to assess the effectiveness of agricultural carbon emission reduction (Cui et al 2021); using Moran's I index and LISA clustering revealed the spatial correlation of land that is farmed ecological utilization e ciency (Feng et al 2023).…”

The Impact of Industrial Agglomeration on Urban Land Green Use Efficiency and Its Spatio-Temporal Pattern: Evidence from 283 Cities in China

“…The focus of research on ULGUE has shifted from theoretical exploration to empirical studies. For measuring land use efficiency, the main methods which have been adopted in previous studies include analytic hierarchy process [15] (AHP), principal component analysis [16] (PCA), data envelopment analysis [17] (DEA), factor analysis [18], Malmquist productivity index [19], etc. However, compared to DEA AHP, PCA and factor analysis can only be used to measure a single aspect of input or output, and cannot measure ULGUE from the land use system as a whole.…”

Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China

“…Gross regional product, industrial structure, and urbanization-which can mobilize the transfer of human, material, and financial resources and information technology within a catchment area-affect agricultural efficiency through economies of scale and structural effects [17,31,38,41]. Natural resource endowment and crop acreage share have a significant positive effect on agricultural efficiency [42,43].…”