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。
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.
作者
王胜
陈健
周宇
孙佳丽
翟振芳
谢五三
戴娟
丁小俊
吴蓉
WANG Sheng;CHEN Jian;ZHOU Yu;SUN Jia-Li;ZHAI Zhen-Fang;XIE Wu-San;DAI Juan;DING Xiao-Jun;WU Rong(Anhui Climate Centre,Hefei 230031,China;Hefei Meteorological Observatory,Hefei 230041,China;Shanghai Climate Centre,Shanghai 200030,China;Jiangsu Climate Centre,Nanjing 210019,China;Huaihe River Basin Meteorological Centre,Hefei 230031,China)
出处
《气候变化研究进展》
北大核心
2025年第6期766-776,共11页
Climate Change Research
基金
华东区域气象科技协同创新基金合作项目(QYHZF202309)
淮河流域气象开放研究基金(HRM202404)
安徽省自然科学基金(2408055UQ008)。
关键词
江淮一季稻
适生区
气候变化预估
MaxEnt模型
Single-cropping rice in the Jianghuai region
Suitable habitat
Climate change projection
MaxEnt model
