Ge Shen

Crop rotation affects soil pH by disturbing H⁺ production and consumption within soil–crop systems, primarily through fertilization, irrigation, cropping, and harvest. Studies have shown that crop rotation improves soil organic matter prediction. However, simply incorporating crop rotation may not significantly improve soil pH prediction, because the spatial variability in soil pH is lower and the way crop rotation influences pH is different. To quantify the extent to which crop rotation improves soil pH mapping, we introduced the strategy of grouping soil samples by crop rotation and modeling separately. We chose a typical multiple-cropping region suffering soil acidification in Southern China, where the complex crop rotation was mapped by Sentinel-1/2 time series and a legend featuring three main systems (i.e., paddy, vegetable, and orchard) and nine subsystems. This crop rotation map was then combined with other variables to derive multiple combinations and predict soil pH. Based on the best combination, we further assessed the grouping strategy. The results showed that simply incorporating crop rotation in one joint model was useful but could not obtain the expected accuracy, with a root mean squared error (RMSE) of 0.66 and an R² of 0.36. The individual statistical accuracies were quite low for the vegetable and orchard rotations, with an RMSE of 0.77/0.70 and an R² of 0.30/−0.04. Grouping soil samples by crop rotation significantly enhanced soil pH predictability with a decrease in the RMSE of 15% and an increase in the R² of 53%. The results proved that grouping by crop rotation can fit and optimize the sub-models after learning the characteristics of the rotation subsamples, offering a way for improving digital mapping of soil pH over heterogeneous agricultural landscapes.

The decrease in grain plantation areas poses a growing concern for global food security. China, with its large population, increasingly diversified food demands, and relatively small cultivated lands, has suffered deeply from this phenomenon (non-grain production, NGP) in recent years. Since 2020, the central government of China has claimed to deal with this problem by attracting agriculturalists and organizations involved in grain plantation. In this context, understanding the global NGP of the national situation is vital for policy making. Remote sensing is regarded as the most effective and accurate method for this purpose, but existing studies have mainly focused on algorithms operating at the local scale or exploring grain-producing capability from the perspective of agricultural space. As such, the characterization of NGP on a national scale remains deficient. In this study, we tried to bridge the gap through spatio-analysis with a newly published nationwide crop pattern and land use geo-datasets; the quantitative, spatial, and structural features, as well as the utilization of NGP cropland in the year 2019, were observed. The results showed that about 60% of the cropland was used for non-grain plantation. About 15% of the NGP parcels were cultivated with grains at least three times in the past 4 years, and of these 60% and 40% were parcels with double- or single-season plantation, respectively, which could result in a 16–22% increase in the grain-sown area compared with 2019. Forest and grassland were the dominant non-cropping categories which NGP cropland transferred into, indicating more time and economic cost for regaining grains. NGP parcels also presented spatio-heterogeneity regarding cropping intensity and transformation. Parcels with double-season plantation mostly emerged in northern, central, and southern provinces, while those with single-season plantation were always located in northeastern and western provinces. The parcels that were transferred into forest or grassland mainly appeared in southern and Inner Mongolia, respectively, while the parcels in northern and central areas mostly continued cropping. According to these results, we propose remediation policies focusing on raising the cropping intensity of cultivated land in central and northern provinces due to their advantages of water, heat, terrain, and land use change features. Future work is warranted based on this study’s deficiencies and uncertainties. As a forerunner, this study provides a holistic observation of the NGP phenomenon in mainland China on a national scale, and the findings can inform improvements in land use policies concerning grain production and food security in China.

Abandoned cropland is a widespread issue globally, with the impacts of utilizing abandoned cropland, such as grain production and carbon emissions, raising increasing concern. However, existing studies have largely overlooked the potential spillover effects on other regions through grain flows when increasing grain production in one region by utilizing abandoned cropland. Therefore, this study aimed to comprehensively estimate the impacts of using winter fallow fields (a typical seasonal abandoned cropland) on grain production and carbon emissions, particularly its neglected spillover impact. Focusing on Zhejiang province, this study used remote sensing techniques to identify winter fallow fields in 2018 and then assessed the impact of using those winter fallow fields on grain production based on grain yield data from the FAO, as well as its local and spillover impacts on carbon emissions based on the Greenhouse Gas Emission Factor method and a transportation carbon emission model. The results indicate the following: (1) The winter fallow fields in Zhejiang cover 5,161,000 hectares, accounting for 40.8% of the total cropland, with a notable prevalence in Jiaxing, Huzhou, Jinhua, and Quzhou. (2) Using winter fallow fields would increase grain production by 1,870,000 tons. (3) At the same time, local carbon emissions would rise by 261,000 tons if using winter fallow fields, but this would be paired with a reduction of 668,000 tons of carbon emissions from other regions (that is, a spillover impact), reflecting a net reduction (−447,000 tons) in overall emissions. In conclusion, using winter fallow fields can achieve a ‘win–win’ effect, increasing grain production while reducing carbon emissions. This study highlights that the spillover effects of using winter fallow fields on carbon emissions significantly surpass the localized impact, underscoring a critical aspect that has been traditionally undervalued, which should be paid more attention when policymakers formulate and implement cropland use policies. This study not only contributes to the academic discourse on sustainable land management but also serves as a practical guide for policymakers seeking to optimize agricultural productivity while curtailing the carbon footprint, thereby advancing towards a more secure and environmentally responsible food system.