中国东北植被时空动态变化及其对气候响应研究

发布时间：2017-12-27 13:18

本文关键词：中国东北植被时空动态变化及其对气候响应研究　出处：《东北师范大学》2016年博士论文　论文类型：学位论文

【摘要】：全球气候变化已经不仅仅是自然生态系统问题,而逐渐成为人们关心的一个重大社会问题。中国东北地区是全球气候变化最敏感区域之一,研究该地区的植被动态变化及其对全球气候变化的响应具有重要的指示作用。本研究利用长时间序列GIMMS3g数据集,提取能够反映植被时空动态变化的植被遥感参数指标(NDVI、NPP和物候期),并结合东北地区降水、气温等气象要素,对东北地区植被遥感参数指标时空动态变化特征及其对气候变化的响应进行了研究。首先对获取的GIMMS3g数据集进行高质量数据重建,剔除噪声影响,同时对东北地区气象站点数据(温度、降水、太阳辐射等)进行空间化,获得与遥感数据相同空间分辨率和投影系统的栅格数据;其次,利用1982?2013年NDVI数据,分析了不同植被类型季节性和年际变化特征,并分析了不同植被类型NDVI对温度和降水变化的响应特征;第三,采用CASA模型(光能利用效率模型),计算了东北地区植被NPP(植被净初级生产力),并使用MOD17A3数据进行验证,探讨了东北地区不同植被类型NPP的时空变化特征及对气候变化的响应;最后,采用不对称高斯模型建立拟合函数,对长时间序列GIMMS NDVI数据进行拟合,获取东北地区植被物候最佳参数,提取植被生长季开始时间和生长季结束时间,分析不同类型植被物候时空变化、及其对温度和降水响应特征。本研究使用响应气候变化的三个植被遥感参数指标,从不同的角度分析东北地区不同植被类型时空变化及其气候变化的响应,为预测东北植被变化趋势提供了科学依据。本文主要得出的结论如下:(1)东北地区植被在过去32年里NDVI趋势主要以负向变化为主;在不同季节中植被NDVI变化特征存在着差异,冬季、春季和夏季主要以负的变化趋势,而秋季是正的变化趋势。东北地区不同植被类型NDVI的变化趋势不同,草丛在过去32年里呈现显著的增加趋势(0.0013单位/年,P0.001);草甸、高山植被、阔叶林、沼泽植被等植被NDVI值呈显著降低的变化趋势,其变化速率分别为-0.0004 单位/年(P0.001),-0.0009 单位/年(P0.001),-0.0004 单位/年(P0.05),-0.0007单位/年(P0.001);草原、灌丛、栽培植被、针阔混交林、针叶林等植被NDVI值没有显著变化;在1982?1999年时间段内,所有植被类型变化均为增加的趋势,而在2000?2013年时间段内,除了草甸和草原有显著增加趋势以外,其他植被类型没有显著变化趋势,因此在近14年里,东北地区植被NDVI呈现下降的趋势。(2)东北地区植被森林覆盖区域春季NDVI与年均温度之间主要表现出了正相关的趋势,而与降水相关性不显著;夏季NDVI与年均温度和降水都不显著,秋季NDVI与温度相关性也不显著,而与降水呈现出相关性,且相关性主要分布在山区;冬季温度对东北地区植被NDVI的影响主要表现在显著正相关性,而与降雨呈现负相关关系。(3)东北地区植被平均NPP 为 499.75 gC/m~2/yr,总 NPP 为 601.85× 1012 gC/yr。东北地区NPP空间分布的基本特点是西部、西南部低,东部、北部高,从东北向西南呈逐级递减趋势。不同植被类型年均NPP、总NPP差异明显。东北地区不同植被类型年均NPP排序为针阔叶混交林阔叶林沼泽针叶林灌丛高山植被草甸栽培植被草丛草原。(4)东北地区过去32年里草丛、草甸、草原、灌丛、阔叶林、栽培植被、沼泽、针叶林年均NPP均表现为增大的趋势,其中:草丛NPP的增速趋势为6.63gC/m~2/yr2(P＜0.01),草甸 NPP 的增速趋势为 3.26gC/m~2/yr2(P0.05),草原NPP 的增速趋势为 3.9gC/m~2/yr2(P0.05),灌丛 NPP 的增速为 2.91gC/m~2/yr(P0.01),阔叶林NPP的增速趋势为2.73gC/m~2/yr2(P0.05),栽培植被NPP的增速趋势为3.32gC/m~2/yr2(P0.05),沼泽NPP的增速趋势为4.91gC/m~2/yr2(P0.01),针叶林NPP的增速趋势为4.32gC/m~2/yr2(P＜0.05)。但是,NPP的增长并不是一个直线向上的过程,在某些气候异常的年份,不同的植被类型对不同的气候因子反应的敏感程度差异很大。(5)不同植被类型NPP与温度和降水的相关性不同。春季10种植被NPP与温度变化全部呈正相关。夏季除草原外,其他植被NPP与温度变化均呈正相关。秋季10种植被与温度变化全部呈正相关,草甸、灌丛、阔叶林、栽培植被呈正相关显著,其他植被类型呈正相关不显著。冬季10种植被与温度变化全部呈负相关,草甸、沼泽呈负相关显著,其他植被类型均呈负相关不显著。全年来看,草丛、草甸、草原NPP与温度呈正相关,其他植被类型呈负相关,正负相关性均不显著。(6)在空间上来看,研究区SOS(植物生长开始期)南到北逐渐推迟,EOS(植物生长结束期)逐渐提前,平原地区植被SOS明显晚于山地地区。在32年中不同植被的SOS、EOS变化趋势特征是不同的,草丛、草甸、草原、灌丛、沼泽、针叶林的SOS出现提前的趋势,高山植被、阔叶林、栽培植被、针阔混交林出现了推迟的趋势。所有的植被类型EOS均出现了推迟的趋势,其中趋势最为明显的是针阔混交林和针叶林,草丛、草甸、草原、灌丛、沼泽、高山植被、阔叶林、栽培植被等变化的趋势相对较缓。(7)从时间上来看,春季植被SOS与温度呈负相关,温度升高可以导致植物SOS提前。夏季和秋季植被EOS与温度呈正相关,温度升高可以导致植物EOS推迟。在森林区域温度升高促使SOS提前的现象更为明显,而在草原区没有显著相关性。SOS对降水具有一定的滞后响应,而对同期的温度响应更为强烈。温度对EOS具有一定滞后性影响,但起决定性作用的时间为9-11月份。
[Abstract]:Global climate change is not only a problem of natural ecosystems, but has gradually become a major social problem that people are concerned about. Northeast China is one of the most sensitive regions of global climate change. It is important to study the dynamic change of vegetation and its response to global climate change. This study uses GIMMS3g data long time sequence set, vegetation parameters can reflect the dynamic extraction of vegetation change (NDVI, NPP and phenology), and combined with the meteorological factors such as precipitation and temperature in Northeast China, the northeast region vegetation parameters temporal change characteristics and its response to climate change were studied. The obtained GIMMS3g data set with high quality data reconstruction, eliminate noise, and the site of Northeast China Meteorological Data (temperature, precipitation and solar radiation, etc.) of space, grid data and remote sensing data to obtain the same spatial resolution and projection system; secondly, the use of 1982? NDVI data in 2013, analysis of the different vegetation the type of seasonal and interannual variations, and the analysis of the response characteristics of different vegetation types in NDVI on the variation of temperature and precipitation; third, using the CASA model (light use efficiency model), vegetation NPP in Northeast China were calculated (net primary productivity), and verified using MOD17A3 data, discusses the temporal and spatial variations of different vegetation types NPP in Northeast China and its response to climate change; finally, a fitting function based on the asymmetric Gauss model to fit the long time sequence of GIMMS by NDVI data Take the best parameters of vegetation phenology in Northeast China, extract the beginning time of vegetation growing season and the end time of growing season, analyze the spatio-temporal change of phenology and its response to temperature and precipitation of different vegetation types. In this study, three vegetation remote sensing parameter indicators that respond to climate change were used to analyze the temporal and spatial variation of different vegetation types and their responses to climate change in Northeast China from different angles, which provided a scientific basis for predicting the trend of vegetation change in Northeast China. In this paper, the main conclusions are as follows: (1) the vegetation in Northeast China in the past 32 years NDVI trend mainly negative changes; in different seasons in different NDVI characteristics, winter, spring and summer is mainly negative trend, and the autumn is the trend of positive. The different change trend of different types of vegetation NDVI in Northeast China, the grass showed a significant increasing trend in the past 32 years (0.0013 units / year, P0.001); meadow, alpine vegetation, broad-leaved forest, swamp vegetation and other vegetation NDVI value showed a trend of decrease, the rate of change was -0.0004 per year (P0.001), -0.0009 per year (P0.001), -0.0004 per year (P0.05), -0.0007 per year (P0.001); grassland, shrub and cultivated vegetation, coniferous forest, coniferous forest vegetation NDVI value had no significant change; in 1982? 1999 period, all vegetation types were all increased the trend, while in the 2000? 2013 period, in addition to meadow and steppe had a significant increase trend, other vegetation types had no significant change trend, so in the past 14 years, vegetation NDVI in Northeast China showed a downward trend. (2) the northeast forest vegetation area between spring NDVI and annual average temperature mainly showed a trend of positive correlation, but not significant correlation with precipitation in summer; NDVI and mean annual temperature and precipitation are not significant, the fall of NDVI also has no significant correlation with temperature and precipitation, and showing a correlation, and the correlation is mainly distributed in the mountainous area; influence of winter temperature on vegetation NDVI in Northeast China is mainly reflected in the significant positive correlation, and negatively correlated with rainfall. (3) the average NPP of the vegetation in Northeast China is 499.75 gC/m~2/yr, and the total NPP is 601.85 x 1012 gC/yr. The basic characteristics of the spatial distribution of NPP in Northeast China are the west, the southwest, the East and the north, and the trend of decreasing from the northeast to the southwest. The annual average NPP and total NPP of different vegetation types were distinct. The annual average NPP of different vegetation types in the northeast region is the coniferous broadleaf broadleaf forest swamp coniferous forest shrubs and alpine vegetation meadow vegetation grasslands. (4) in Northeast China in the past 32 years, the grass meadow, grassland, shrub and broadleaf forest, coniferous forest and swamp vegetation cultivation, annual NPP showed increasing trend, the growth trend of NPP is: grass 6.63gC/m~2/yr2 (P < 0.01), the growth trend is 3.26gC/m NPP meadow (P0.05), the growth rate of ~2/yr2 the trend of grassland is 3.9gC/m~2/yr2 NPP NPP (P0.05), shrub growth rate of 2.91gC/m~2/yr (P0.01), the growth rate of NPP for the 2.73gC/m~2/yr2 trend of broad-leaved forest (P0.05), the growth rate trend of cultivated vegetation is 3.32gC/m~2/yr2 NPP (P0.05), the growth trend for 4.91gC/m~2/yr2 swamp NPP (P0.01), the growth trend of coniferous forest was 4.32gC/m~2/yr2 (NPP P < 0.05). However, the growth of NPP is not a straight upward process. In some climate abnormal years, the sensitivity of different vegetation types to different climate factors is quite different. (5) the correlation between NPP of different vegetation types and temperature and precipitation is different. The 10 planting in spring was positively correlated with the change of NPP and temperature. In summer, the other vegetation NPP was positively correlated with the change of temperature. In autumn, 10 planting was positively correlated with temperature change. There was a positive correlation between meadow, shrub, broad-leaved forest and cultivated vegetation. In winter, 10 plants were negatively correlated with temperature changes, and meadow and swamps were negatively correlated, and other vegetation types were negatively correlated. Throughout the year, the grass, meadow and grassland NPP were positively correlated with the temperature, and the other vegetation types were negatively correlated, and the positive and negative correlations were not significant. (6) in terms of space, SOS (plant growth start stage) gradually postponed from south to north, and EOS (plant growth end stage) progressively advanced. SOS in plain area was obviously later than that in mountainous area.
【学位授予单位】：东北师范大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：Q948.1

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