基于模糊数学(Fuzzy)法的中国水稻土肥力质量近30年的时空变化特征  

Spatiotemporal Variation of Fertility Quality of Chinese Paddy Soil Based on Fuzzy Method in Recent 30 Years

作　　者：黄晶[1,2] 韩天富 申哲[1] 柳开楼 马常宝[4] 王慧颖 曲潇琳 于子坤 谢建华 张会民 HUANG Jing;HAN Tianfu;SHEN Zhe;LIU Kailou;MA Changbao;WANG Huiying;QU Xiaolin;YU Zikun;XIE Jianhua;ZHANG Huimin(Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences/National Engineering Laboratory for Improving Quality of Arable Land,Beijing 100081,China;National Observation and Research Station of Qiyang Agri-ecology System,Qiyang,Hunan 426182,China;Jiangxi Institute of Red Soil/National Engineering and Technology Research Center for Red Soil Improvement,Jinxian,Jiangxi 330046,China;Center of Cultivated Land Quality Monitoring and Protection,Ministry of Agricultural and Rural Affairs,Beijing 100125,China)

机构地区：[1]中国农业科学院农业资源与农业区划研究所/耕地培育技术国家工程实验室,北京100081 [2]祁阳农田生态系统国家野外科学观测研究站,湖南祁阳426182 [3]江西省红壤研究所/国家红壤改良工程技术研究中心,江西进贤330046 [4]农业农村部耕地质量监测保护中心,北京100125

出　　处：《土壤学报》2023年第2期355-366,共12页Acta Pedologica Sinica

基　　金：国家重点研发计划项目课题(2016YFD0300901);现代农业产业技术体系(CARS-01-88,CARS-22-Z09)资助。

摘　　要：基于农业农村部在我国主要稻区的长期定位监测数据(1988—2017年),采用模糊数学(Fuzzy)法对水稻土肥力质量进行评价,并结合地统计学和机器学习,阐明我国水稻土肥力质量时空变化特征及其影响因素。近30 a来全国稻区土壤肥力质量呈显著上升趋势(P<0.05),从前期(1988—1999年)至中期(2000—2009年)和从中期至近期(2010—2017年),全国稻田土壤肥力指数(SFI)分别平均增加了6.9%和17.7%。各稻区SFI阶段性变化特征存在差异,西南和长江中游稻区呈前慢后快的显著上升趋势(P<0.05),华南和长江三角洲(长三角)稻区呈前快后稳的上升趋势,东北稻区呈前降后升的变化趋势。近期全国稻田SFI呈现北高南低、东高西低的分布特征,SFI超过全国平均值(0.61)的区域占50.2%。与中期相比较,近期全国稻区SFI总体呈上升趋势,SFI增加的区域占69.3%。各稻区在前期和中期(东北稻区的中期除外)均表现为土壤有机质和全氮影响SFI变化的相对重要性占比(19.4%~60.3%)远大于其他指标(0.1%~13.3%)。至近期,所有稻区各指标影响SFI变化的相对重要性占比差距缩小(7.4%~26.8%),土壤有效磷和速效钾及土壤pH(东北稻区pH除外)等指标的相对重要性增加,其中长江中游稻区土壤有效磷含量的相对重要性增至最大,但各稻区仍均以土壤全氮和有机质含量的相对重要性较大。综上,应综合考虑不同阶段和不同稻区土壤肥力质量时空差异特征及其关键肥力指标相对重要性的变化,针对性地优化施肥措施,防治水稻土酸化,以改善和提高水稻土肥力质量。【Objective】The spatiotemporal variation characteristics and driving factors of fertility quality of paddy soils in China were studied.【Method】Based on the long-term monitoring data(1988—2017)of the Ministry of Agriculture and Rural Affairs in the main rice areas in China,the fertility quality of paddy soil in the main rice areas was evaluated by the fuzzy mathematics(Fuzzy)method,and combined geo-statistics with machine learning.【Result】In the recent 30 years,the soil fertility index(SFI)of the rice area in China increased significantly(P<0.05).From the prophase(1988—1999)to the interim(2000—2009)and from the interim to the recent(2010—2017),the national paddy field SFI increased by 6.9%and 17.7%on average,respectively.The characteristics of SFI varied in different time stages in the main rice regions.The rice regions in southwest China and the middle reaches of the Yangtze River showed a significant increasing trend of slow in the early period(from prophase to interim)and fast in the later period(from interim to recent)(P<0.05).Also the rice fields in South China and the Yangtze River Delta showed a rising trend of fast in the early stage(from prophase to interim)and stable in the later stage(from interim to recent).There was a decreasing trend in the earlier period(from interim to recent)and increasing in the later period(from interim to recent)in the Northeast rice region.At the recent,the distribution of paddy SFI in China showed a trend of higher in the north and lower in the south,higher in the east and lower in the west.The area with SFI exceeding the national average(0.61)accounted for 50.2%.Compared with the SFI of the rice region in the interim,the SFI showed an overall upward trend in the recent.The increased area accounted for 69.3%.The relative importance of soil organic matter and total nitrogen to SFI change(19.4%—60.3%)was much higher than that of other indexes(0.1%—13.3%)in all rice areas in the prophase and interim(except the middle stage of the northeast rice region).The

关 键 词：水稻土 主要稻区 模糊数学(Fuzzy)法 土壤肥力指数 时空变化 增强回归树 

分 类 号：S156.6[农业科学—土壤学]