明代疫灾时空分布及环境机理研究

发布时间：2018-05-18 01:21

  本文选题：明代 + 疫灾　； 参考：《华中师范大学》2015年博士论文

【摘要】：疫灾是与人类相伴始终的顶级自然灾害之一。深入研究历史时期疫灾流行及其与自然环境的关系,可以为当前传染病防控提供历史参考,是当今时代的需要。本文以明代疫灾史料、气候变迁数据和自然灾害史料为基础,运用空间分析及数理统计方法,研究明代疫灾的时空分布特征及其环境机理。明代疫灾,在王朝分布上,崇祯朝的灾情最为严重,其次为万历朝和嘉靖朝,灾情最轻的为建文和洪熙朝；在季节分布上,春季和夏季是疫灾高发季节,秋季是疫灾多发季节,冬季疫灾最少；在趋势周期上,整体呈上升趋势,每隔十年疫灾县数约增加9.5个,存在100年和50年两种尺度的波动周期,在100年尺度周期下,经历了约5个“轻-重”转换周期,在50年尺度周期下,经历了约8个“轻-重”转换周期；在省域分布上,明代疫灾呈现自东北向西南递减的总体趋势,疫灾较严重省份主要位于东北部地区,包括南直隶、北直隶、浙江等省,位于西南部的广东、广西、云南、贵州、四川等省份疫灾普遍较轻；在县域分布上,共有1009个县有疫灾发生,其中疫灾频度最高的为南直隶吴县,达到8.3%,其次为北直隶大兴和宛平县,均为7.94%,有542个县无疫灾发生,疫灾频度为0；在冷热点分布上,疫灾热点主要分布在东北部三个区域,冷点主要分布在西南部三个区域；明代共有10个特大疫灾年份,可以归纳为5个特大疫灾过程。明代全国气候冷暖变迁趋势与疫灾变化趋势相反,波动周期比较接近,呈显著负相关关系,气候温暖阶段疫灾县数显著减少,寒冷阶段则显著增加。二者间的因果关系符合回归方程y=-1.456x-0.577,全国温度距平标准化值每减小1个单位,疫灾县数标准化值增加1.456个单位,气候冷暖变迁可以解释23%的疫灾县数变化。在区域尺度上,华北地区气温与本区疫灾变化趋势相反,二者间呈显著负相关关系,并具有统计学上的显著性,其因果关系符合回归方程y=-0.631x,温度距平值标准化值每减小1个单位,疫灾县数标准化值增加0.631个单位,气候冷暖变迁可以解释39.6%的疫灾变化；华东地区气温与本区疫灾变化趋势相反,呈低度负相关关系,并具有统计学上的显著性,二者间因果关系符合回归方程y=-0.429 x-0.001,温度距平值标准化值每减小1个单位,疫灾县数标准化值增加0.429个单位,气候冷暖变迁可以解释15.4%的疫灾变化；华中地区、华南地区、和西南地区气温与各自区域疫灾变化趋势均相反,均呈微弱负相关关系,都不具有统计学上的显著性。明代东部地区干湿变迁趋势与疫灾变化趋势相反,波动周期较为接近,二者间呈低度负相关关系,但不具有统计学上的显著性,气候的干湿变化对疫灾轻重的影响不显著。在东部各区域上,华北地区和江淮地区干湿变迁与疫灾变化均为微弱负相关关系,都不具有统计学上的显著性,明代江南地区干湿变迁与疫灾变化为低度负相关关系,具有统计学上的显著性。明代疫灾与水灾在时间分布上具有显著正相关关系,相关系数为0.739。具体来说,二者增长趋势具有统计学上显著的完全正相关关系,相关系数为1,波动周期性在总体上不存在显著的相关性。在空间分布上也显著正相关,相关系数为0.613,疫灾与水灾灾情均呈现从沿海向内陆递减的趋势,疫灾中心基本与水灾中心重合。二者的因果关系符合回归方程y=0.421x-20.961,十年水灾县数每增加1个,十年疫灾县数平均增加0.421个,十年水灾县数可以解释33.1%的十年疫灾县数的变化。明代疫灾与旱灾在时间分布上具有高度正相关关系,相关系数为0.861,疫灾较重时旱灾也较为严重,反之亦然。具体来说,在增长趋势上具有一致性,均呈上升趋势,相关系数为0.998,具有统计学上显著的高度正相关关系,在周期分布上也具有高度的正相关性,相关系数为0.844。在空间分布上也显著正相关,相关系数为0.657,即疫灾较重的区域旱灾也较为严重,反之亦然,疫灾中心与旱灾中心基本重合。其因果关系符合回归方程y=0.546x-18.230,十年旱灾县数每增加1个,十年疫灾县数平均增加0.546个,十年旱灾县数可以解释74.1%的十年疫灾县数的变化。明代疫灾与蝗灾在时间分布上具有显著正相关关系,相关系数为0.681,疫灾较重时蝗灾也较为严重,反之亦然。具体来说,在增长趋势上具有一致性,相关系数为1,具有统计学上显著的完全相关关系,在周期分布上也具有显著的正相关性,相关系数为0.541。在空间分布上也显著正相关,相关系数为0.555,即疫灾较重的区域蝗灾也相对较为严重,反之亦然,东北部地区蝗灾较严重的地区疫灾也较为严重,西部及南部地区疫灾和蝗灾都较轻。二者间的因果关系符合回归方程y=0.705x+10.724,十年蝗灾县数每增加1个,十年疫灾县数平均增加0.705个,十年蝗灾县数可以解释46.4%的十年疫灾县数的变化。明代疫灾与震灾在时间分布上具有显著正相关关系,相关系数为0.643,震灾较重时疫灾也较为严重,反之亦然。具体来说,在增长趋势上具有统计学上显著的完全正相关关系,相关系数为1,在周期分布上不具有显著的相关性。在空间分布上具有统计学上的显著性的低度正相关关系,相关系数为0.390,疫灾与震灾同时都较严重的地区包括北直隶北部京师地区、山西省中部太原府地区、南直隶东部应天府地区及陕西省西南部西安府地区等。二者的因果关系符合回归方程y=0.383x+6.354,十年震灾县数每增加1个,十年疫灾县数平均增加0.383个,十年震灾县数可以解释29%的十年疫灾县数的变化。疫灾的环境机理可以理解为影响疫灾的环境要素、影响程度及其作用机理。气候冷暖变迁、水灾、旱灾、蝗灾、震灾等5种要素是对明代疫灾变化具有影响的主要自然环境要素。5种环境要素对疫灾变化的影响程度从高到低依次为“旱灾(74.1%)蝗灾(46.4%)水灾(33.1%)震灾(29%)气候冷暖变迁(23%)”。环境要素影响疫灾的作用机理,从本质上是通过对传染源、传播途径和易感人群这三个环节施加影响而体现的,如果多种灾害同时叠加发生,就会造成严重疫灾。
[Abstract]:The epidemic is one of the top natural disasters associated with human being . It is necessary to provide historical reference for epidemic prevention and control of epidemic diseases . It can provide historical reference for prevention and control of infectious diseases . It is based on historical materials , climatic change data and natural disasters historical materials , and studies the characteristics of space - time distribution and its environmental mechanism of epidemic prevention in Ming Dynasty .
In the seasonal distribution , spring and summer are the high season of the plague , autumn is the season of the epidemic , and the winter epidemic is the least ;
In the trend cycle , the overall increase trend , the number of epidemic counties increased 9.5 in every decade , there were fluctuation periods of 100 years and 50 years , and in the 100 - year scale period , about 5 " light - weight " conversion cycles were experienced , and approximately 8 " light - weight " conversion cycles were experienced in the 50 - year scale period ;
At the provincial level , the epidemic of the Ming Dynasty presented the general trend of decreasing from the northeast to the southwest , and the more severe provinces were located in the north - east region , including the provinces of Zhili , North Zhili , Zhejiang and so on . The epidemic in Guangdong , Guangxi , Yunnan , Guizhou , Sichuan and other provinces in southwest China were generally lighter ;
At the county level , there are 1009 counties with epidemic diseases , in which the frequency of the epidemic is the highest in Wuxian County , Zhili County , up to 8.3 % , followed by 7.94 % in North Zhili and Datong County , and there are 542 counties with no plague , and the frequency of plague is 0 ;
In the cold spot distribution , the hot spots are mainly distributed in three regions of the north - east , and the cold spots are mainly distributed in the three regions of the southwest ;
In the Ming Dynasty , there were 10 special epidemic years , which could be summarized into five major epidemic processes . In the Ming Dynasty , there was a significant negative correlation between climate warming and epidemic trend .
There was a negative correlation between the temperature of East China and the epidemic trend of the local epidemic , and had statistical significance . The causal relationship between them was consistent with the regression equation y = - 0.429 x - 0.001 , the normalized value of the temperature was decreased by 1 unit , the standardized value of epidemic disaster counties increased by 0.429 units , and the climate warming change could explain the epidemic change of 15.4 % ;
In the eastern part of the Ming Dynasty , there was a significant positive correlation between the dry and wet changes in the eastern part of the Ming Dynasty . The correlation coefficient was 0 . The results show that there are significant positive correlations in the spatial distribution , the correlation coefficient is 0 . 555 , that is , there is a significant positive correlation between plague and plague in the north - east region .
【学位授予单位】：华中师范大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：K248
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本文编号：1903755