Increase in global per capita cropland imbalance across countries from 1985 to 2022: A threat to achieving Sustainable Development Goals

Abstract

Sustainable Development Goal 2 (SDG 2, zero hunger) highlights that global hunger and food insecurity have worsened since 2015, driven in part by growing imbalance. Addressing the challenge of achieving SDG 2 in the face of rapid global population growth requires sustained attention to global and national cropland changes. Accurately quantifying the correlation between population and cropland area (i.e., SDG 2.4.1 per capita cropland) and analyzing the trends of global cropland imbalance are essential for a comprehensive understanding of SDG 2. In this study, we utilized a new global 30 m land-cover dynamic dataset (GLC_FCS30D) to analyze cropland dynamics, quantify per capita cropland and its changes across various countries and levels of development. Our results indicate that the global cropland area expanded by 0.944 million km² from 1985 to 2022, with an average expansion rate of 2.42 × 10⁴ km²/yr. However, the global per capita cropland area decreased from 0.347 ha in 1985 to 0.217 ha in 2022, mainly due to a higher population increase of nearly 65 % in the same period. In the context of globalization, cropland expansion and per capita cropland exhibited spatial imbalances globally, particularly in developing countries. Developing countries saw an increase in total cropland area by 7.09 % but a significant decrease in per capita cropland area by 37.38 %. From a temporal perspective, the global imbalance has been steadily increasing with the Gini index rising from 0.895 in 1985 to 0.909 in 2022. Consequently, this study reveals an increasing imbalance of global per capita cropland across various countries, which threatens the attainment of the targets of SDG 2.

Keywords

Sustainable Development Goals / GLC_FCS30D / Cropland changes / Population / Imbalance

CRediT authorship contribution statement

Tingting Zhao: Writing – review & editing, Writing – original draft, Visualization, Methodology, Formal analysis, Conceptualization. Xiao Zhang: Writing – review & editing, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. Wendi Liu: Writing – review & editing, Supervision, Investigation, Formal analysis, Data curation. Jinqing Wang: Writing – review & editing, Supervision, Investigation, Data curation. Zhehua Li: Writing – review & editing, Supervision, Investigation, Data curation. Liangyun Liu: Writing – review & editing, Supervision, Methodology, Funding acquisition, Conceptualization.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (Grant No. 2023YFB3907403), the National Natural Science Foundation of China (Grant No. 42201499), and the Open Research Program of the International Research Center of Big Data for Sustainable Development Goals (Grant No. CBAS2022ORP03).

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