基于CMIP6和MaxEnt模型的江淮一季稻适生区分布预估

doi:10.12006/j.issn.1673-1719.2025.056

摘要/Abstract

摘要： 基于CMIP6气候模式数据和MaxEnt模型，耦合土壤、地形及人类活动等多维环境因子，系统评估了江淮一季稻在气候基准期（1985—2014年）与未来（2026—2100年）不同情景下适生区演变。结果表明：(1)通过共线性检验结合刀切法的“双指标”机制，从14个潜在环境因子中优选出9个主导因子，其累计贡献率达94.4%。模型验证表明，优化后的MaxEnt模型预测精度显著提升（AUC=0.923)。(2)未来江淮一季稻全生育期平均气温呈现显著上升趋势，其中SSP5-8.5情景下的升温速率最大（0.50℃/(10 a))；降水量总体呈增加趋势，江淮地区中北部降水增加趋势高于南部。(3)气候基准期高适生区集中在长江三角洲和沿江平原，占总面积的21.7%，其典型特征为水稻土占比高且水热条件优越；中适生区集中分布在淮河以南平原区，占26.2%；低适生区分布在淮北平原，占35.1%；非适生区主要包括大别山区和皖南山区、西北部旱地及城市化区域，占17.1%。(4)在未来时期，适生区呈现“东缩北扩”趋势，至SSP5-8.5情景下的远期，高适生区面积减少3.8个百分点，低适生区面积增加6.6个百分点。该演变主要受气候变暖“双刃剑”效应驱动：一方面安徽北部（32°N以北）因≥10℃积温增加300~450℃·d、生育期延长12~18 d成为主要扩展区；另一方面江苏南部（32°N以南）受高温日数增至35~45 d的胁迫，特别是在水稻关键生育期（孕穗-抽穗期）遭遇极端高温的概率增加3~5倍，因而适生区显著退缩。建议通过耐高温品种选育和种植布局优化提升气候韧性，为区域农业适应性策略制定提供科学依据。

关键词: 江淮一季稻, 适生区, 气候变化预估, MaxEnt模型

Abstract:

Based on CMIP6 climate model data and the MaxEnt model, this study systematically evaluates the evolution of suitable cultivation areas for single-cropping rice in the Jianghuai region during the climatic baseline period (1985-2014) and the future (2026-2100) under different scenarios, by coupling environmental factors such as soil, topography, and human activities. The results are as follows. (1) Through the “dual-index” mechanism combining collinearity testing and Jackknife method, 9 dominant factors were screened from 14 potential environmental factors, with a cumulative contribution rate of 94.4%. Model validation shows that the prediction accuracy of the optimized MaxEnt model was significantly improved (AUC=0.923), which is superior to the prediction accuracy reported in similar studies (e.g., 0.85-0.90). (2) The mean temperature during the entire growth period of single-cropping rice in the Jianghuai region shows a significant upward trend in the future, with the maximum warming rate under the SSP5-8.5 scenario (0.50℃/(10 a)). Precipitation generally shows an increasing trend, which is higher in the central and northern Jianghuai region than that in the south. (3) During the climatic baseline period, high-suitability areas are concentrated in the Yangtze River Delta and along-river plains, accounting for 21.7% of the total area, characterized by high proportion of paddy soil and superior hydrothermal conditions; medium-suitability areas are mainly located in the plains south of the Huaihe river, accounting for 26.2%; low-suitability areas are distributed in the Huaibei plain, accounting for 35.1%; non-suitability areas include the Dabie mountains and southern Anhui mountains, northwestern drylands, and urbanized areas, accounting for 17.1%. (4) In the future, the suitable areas show a trend of “eastern contraction and northern expansion”. In future periods, under the SSP5-8.5 scenario, the area of high-suitability areas will decrease by 3.8 percentage points, and that of low-suitability areas will increase by 6.6 percentage points. This evolution is mainly driven by the “double-edged sword” effect of climate warming: on one hand, northern Anhui (north of 32°N) becomes the main expansion area due to the increase of ≥10℃ accumulated temperature by 300-450℃·d and the extension of the growth period by 12-18 days; on the other hand, southern Jiangsu (south of 32°N) shows significant contraction under the stress of increased high-temperature days to 35-45 days, especially the probability of extreme high temperature during the critical growth stages (booting-heading stage) of rice increases by a factor of 3-5. It is proposed to enhance climate resilience through the breeding heat-tolerant varieties and optimizing planting layouts, providing a scientific basis for formulating regional agricultural adaptation strategies.

Key words: Single-cropping rice in the Jianghuai region, Suitable habitat, Climate change projection, MaxEnt model

王胜, 陈健, 周宇, 孙佳丽, 翟振芳, 谢五三, 戴娟, 丁小俊, 吴蓉. 基于CMIP6和MaxEnt模型的江淮一季稻适生区分布预估[J]. 气候变化研究进展, 2025, 21(6): 766-776.

WANG Sheng, CHEN Jian, ZHOU Yu, SUN Jia-Li, ZHAI Zhen-Fang, XIE Wu-San, DAI Juan, DING Xiao-Jun, WU Rong. Projection of the suitable cultivation area for single-cropping rice in the Jianghuai region based on CMIP6 and MaxEnt model[J]. Climate Change Research, 2025, 21(6): 766-776.

图/表 9

图1 江淮一季稻种植区空间分布

Fig. 1 Potential distribution of single-cropping rice planting areas in the Jianghuai region

表1 CMIP6模式介绍

Table 1 CMIP6 climate models used in this study

表2 江淮一季稻种植分布的潜在影响因子

Table 2 Potential impact factors for the distribution of single-cropping rice planting in the Jianghuai region

图2 泰勒图评估CMIP6模式模拟江淮地区4—9月平均气温(a)和降水(b)的能力注：图中虚线为均方根误差线。

Fig. 2 Taylor diagram of the mean temperature (a) and precipitation (b) during April-September simulated by CMIP6 climate models compared with observations

图3 2026—2100年不同情景一季稻全生育期平均气温(a)和降水量(b)变化预估

Fig. 3 Projected changes in mean temperature (a) and precipitation (b) during the entire growth period of single-cropping rice under different SSPs scenarios from 2026 to 2100

图4 气候基准期江淮一季稻种植潜在分布格局

Fig. 4 Potential distribution pattern of single-cropping rice planting in the Jianghuai region during the baseline period of model hindcasting

表3 基准期和未来情景下一季稻适生区面积占比

Table 3 Proportion of suitable area for single-cropping rice during the baseline period and future scenarios

图5 不同SSP情景下江淮一季稻适生区变化

Fig. 5 Comparison of the potential spatial distribution pattern changes of single-cropping rice planting in 2026-2040, 2041-2070, and 2071-2100 relative to the baseline period

表4 SSP5-8.5情景下江苏南部（32°N以南）高温日数与极端高温概率变化

Table 4 Changes in high-temperature days and extreme temperature probability in southern Jiangsu (south of 32°N) under SSP5-8.5

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