东北黑土区玉米产量时空演变规律及其驱动因素

    Spatiotemporal dynamics of maize yield and associated driving factors in the black soil region of Northeast China

    • 摘要: 东北黑土区是中国重要的粮食生产基地。近年来,受气候变化和土壤肥力等因素共同影响,东北黑土区农作物产量的时空演变规律及其关键驱动因素尚不清楚。基于农业农村部耕地质量监测网络1988—2021年的监测数据和气候资料,分析东北黑土区玉米产量和基础地力贡献率的时空演变特征,结合可解释机器学习模型SHAP(Shapley Additive exPlanations)量化土壤和气候因素对玉米产量的影响程度,采用偏最小二乘法明确玉米产量时空变化与气候和土壤等因素的耦联关系。结果表明:1)玉米年均产量和基础地力贡献率分别从第Ⅰ阶段(1988—2000年)的8.09 t/hm2和47%提升至第Ⅱ阶段(2001—2010年)的8.83 t/hm2和53%、第Ⅲ阶段(2011—2021年)的10.15 t/hm2和59%。2)玉米产量和基础地力贡献率呈现东部高(大兴安岭东麓松嫩平原,平均值分别为11.75 t/hm2和82%)、西北部低(内蒙古西北部,6.95 t/hm2和34%)的空间特征。3)干旱指数和气温日较差等气候因素是玉米产量变化的主要影响因子,其相对贡献率为61.34%;有效磷和速效钾等土壤肥力指标也是控制玉米产量变化的关键因素(相对贡献率为38.66%)。综上,该研究为准确预测未来气候变化和土壤肥力演变交互作用下东北黑土区玉米生产力演变规律提供理论支撑。

       

      Abstract: The black soil region of Northeast China can serve as a crucial grain production base in the world. However, there is a complex interaction between the climate and soil fertility. This present study aims to explore the spatiotemporal dynamics of the maize yield and its key driving factors in the black soil region. The monitoring climate data was collected from the Cultivated Land Quality Monitoring Network of the Ministry of Agriculture and Rural Affairs from 1988 to 2021. Shapley Additive exPlanations (SHAP) interpretable machine learning model was employed to quantify the influence of the soil and climate factors on the maize yield. Partial least squares regression was used to determine the coupling relationship between the maize yield and climate or soil factors. The contribution rate of the soil fertility was finally calculated for the high yield. The results showed that the annual maize yield increased from 8.09 t/hm2 during Stage I (1988–2000) to 8.83 t/hm2 in Stage II (2001—2010), and further to 10.15 t/hm2 in Stage III (2011—2021). The contribution rate of the soil fertility rose from 47% in Stage I to 53% in Stage II and 59% in Stage III. Spatially, the maize yield and soil fertility contribution rates were higher in the eastern region (Songnen Plain on the eastern of the Greater Khingan Mountains, with averages of 11.75 t/hm2 and 82%, respectively), and lower in the northwestern region (northwestern Inner Mongolia, with averages of 6.95 t/hm2 and 34%, respectively). Climate factors, particularly the drought index and diurnal temperature range, were identified as the primary drivers of the maize yield, accounting for 61.34% of the relative contribution. Soil fertility indicators, notably available phosphorus and available potassium, were also key controlling factors on the yield, thus relatively contributing 38.66% of the total. The SHAP analysis revealed that the available phosphorus and potassium promoted the maize yield. Their positive correlation was saturated relatively, when the available phosphorus and potassium exceeded 18 and 170 mg/kg, respectively. The drought index of 0.5 to 1.5 and the diurnal temperature range of 9 to 11℃ were found to be optimal for the maize yield. Interaction analysis showed that there was a positive correlation between the higher available phosphorus (>18 mg/kg) with the lower drought index (0.5-1.5) and suitable diurnal temperature range (9-11℃). Partial least squares regression indicated that the climate and soil factors together were used to explain 24% of the spatiotemporal variation in the maize yield. Climate factors shared a strong direct effect on the maize yield (path coefficient of 0.43). While their indirect effects were weaker through soil nutrients and pH. Among the climate factors, the relative humidity, heavy rainfall days, and extreme rainfall shared the positive effects, whereas the negative effects were found in the warm spell duration index, drought index, and diurnal temperature range. In total, the climate factors shared a stronger influence on the maize yield (45.74%), compared with the soil nutrients (16.48%) and pH (4.69%). This finding can provide the theoretical support to predict the dynamics of the maize productivity in the black soil region of Northeast China under future climate and soil fertility. It highlights the climate factors monitoring and soil improvement measures for the stable and high maize yields. Future research should explore the interactions between climate, soil factors, and agricultural management practices. A more comprehensive understanding of the maize yield dynamics can be gained to support sustainable agriculture.

       

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