基于灰水足迹的长江经济带耕地利用生态效率时空分异特征

    Characterization of the spatio-temporal divergence of eco-efficiency of cultivated land use using grey water footprint in the Yangtze River Economic Belt of China

    • 摘要: 长江经济带面临水生态环境污染制约下的农业发展困境,水环境约束下耕地利用生态效率的提升成为平衡耕地利用中经济效益与生态效益的关键手段,对于探索生态可持续的耕地利用模式、实现农业绿色发展具有重要意义。该研究以灰水足迹为视角,基于SBM-Undesirable模型、空间自相关分析及马尔可夫链模型探明2000—2020年长江经济带耕地利用生态效率时空格局及演变趋势。研究表明:1)长江经济带2000—2020年平均灰水足迹值呈现先增后减趋势,2015年后下降态势更为明显。在空间上呈现为“东西高,中部低”的空间分布特征,灰水足迹高值区域主要集中在粮食主产区省份。2)2000—2020年长江经济带耕地利用生态效率持续下降,效率均值处于0.5~0.8之间,存在较大提升空间。在空间上呈现高值区域多沿水系分布的特点。3)长江经济带市域耕地利用生态效率存在显著空间正相关性,以研究时段演变趋势来看,耕地利用生态效率的演进存在路径依赖,难以实现“跨越式”提升。因受到邻域背景影响,在空间上易显现出“俱乐部收敛”现象,“高-高集聚”与“低-低集聚”分布更为常见。可在农业生产重点区域采用差异化精准农业模式,需重视区域间动态协同发展,完善联防联治的面源污染防控机制,积极引导耕地利用生态效率高值区域逐步形成集中连片,同时对于耕地利用生态效率低效区提供财政与政策支持。研究结果可为各地区探索耕地利用可持续发展模式与农业生产活动中水生态环境保护提供参考依据。

       

      Abstract: The Yangtze River Economic Belt confronts the paradoxical challenge of agricultural growth and substantial water environmental contamination. Enhancing the eco-efficiency of cultivated land use while considering water environment limitations has emerged as a pivotal approach to harmonizing economic and ecological benefits in cultivated land utilization, thereby holding significant implications for exploring ecologically sustainable modes of cultivated land utilization and achieving green agricultural development. In light of this, a cultivated land use eco-efficiency evaluation index system is developed in this study, using the connotation definition of cultivated land use eco-efficiency from the standpoint of the grey water footprint. This study utilized the SBM-Undesirable model to assess the eco-efficiency of cultivated land use in 130 cities within the Yangtze River Economic Belt for the period from 2000 to 2020. Additionally, the spatial and temporal trends in eco-efficiency of cultivated land use, as well as their evolution from 2000 to 2020, were analyzed utilizing the spatial autocorrelation and Markov chain models. The findings indicate that the average grey water footprint value of the Yangtze River Economic Belt exhibited an initial increase followed by a subsequent decrease from 2000 to 2020. The decline in the grey water footprint value after 2015 was more pronounced, potentially attributable to the implementation of ecological management projects such as non-point source pollution control and reduction in fertilizer and pesticide usage in response to national policies across all regions. Simultaneously, the spatial distribution pattern of the grey water footprint demonstrated a " high in the east and west, low in the middle" trend, with higher values primarily concentrated in major grain-producing provinces. The intensive utilization of cultivated land and excessive resource consumption further exacerbated water environment pollution and ecological degradation within these regions. Throughout the period from 2000 to 2020, there has been a continuous decline in the eco-efficiency of cultivated land use within the Yangtze River Economic Belt, with an average efficiency level ranging between 0.5 to 0.8 indicating significant room for improvement. Notably, distinct regional disparities exist regarding the eco-efficiency of cultivated land use among upper, middle, and lower regions due to variations in environmental quality gradients, socio-economic development levels, and unequal allocation of production factors. The results of spatial autocorrelation and Markov chain model analysis reveal a significant positive spatial correlation in the eco-efficiency of cultivated land use within the Yangtze River Economic Belt, exhibiting evident geographical heterogeneity in its distribution. However, regions with high eco-efficiency of cultivated land use may exhibit dispersed spatial patterns or unstable input-output structures, potentially hindering collaborative and efficient utilization of cultivated land for green agricultural development. Considering the evolutionary trend observed during the study period, improvements in eco-efficiency of cultivated land use are challenging to achieve due to path dependence. Nevertheless, their stability is influenced by spatial factors. The influence of neighborhood background often leads to the "club convergence" phenomena in space, where both "high-high cluster" and "low-low cluster" distributions are commonly observed. In light of these findings, it is imperative to implement differentiated precision agriculture models and enhance measures for controlling agricultural non-point source pollution. Simultaneously, attention should be paid to fostering dynamic inter-regional development through increased financial support for agriculture. Directional agricultural policies can provide support for areas with inefficient eco-efficiency of cultivated land use, prompting input-output structure transformation and upgrading. Ultimately, this will lead to increased eco-efficiency of cultivated land use.

       

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