【作者】 王亚萍；

【导师】 王开运；

【作者基本信息】 华东师范大学 ， 生态学， 2009， 硕士

【摘要】 植被作为陆地生态系统中不可或缺的一部分,在全球变化研究中占有举足轻重的地位。植被净第一性生产力(NPP)的研究有助于碳循环、碳动态和碳平衡的研究,其敏感性对全球气候系统有着重要的影响。随着RS,GIS和计算机技术的快速发展,利用遥感数据进行植被NPP的研究日趋成熟,成为研究的主导方向。这些技术的综合应用,不仅实现了植被NPP大范围快速监测,而且可以正确评价植物群落在自然条件下的生产能力,以便为有关部制定宏观调控政策及应急政策提供科学依据。本文以过程机理模型为主要研究手段对上海城市植被生态系统净第—性生产力(NPP)的时空格局变化进行了动态模拟估算(以2006年为例),旨在通过研究探索上海城市植被生态系统NPP时空格局。依据这一研究目的,我们在GIS支持下通过上海市航片的解译和实地植被调查等步骤建立了上海城市植被数据库,参考TREEDYN模型和TREEDEV模型运用VB语言编写了光合生产模型,应用此数据库和模型,对2006年上海城市植被生态系统NPP的时空分布格局进行了较为全面的定量估算。利用Kriging插值法,在地理信息系统技术的支持下,对上海城市植被NPP状况进行了模拟估算。通过研究,主要得到以下几方面的结论:1、研究区航片植被分布情况和功能的解译,植被的解译工作是本文的前期基础工作。运用ArcGIS9.2数字化比例尺为1:5700的航片图统计分析得到上海市城市绿地总面积为139.11km~z,占研究区域总面积的20.2%;其中公园绿地、居住区绿地、单位附属绿地、道路绿地、沿岸绿地、生产绿地面积分别为18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2,占全部绿地面积的百分比分别为13.27%、24.6%、40.46%、11.62%、2.41%、7.63%。2、以上海城市植被参数为状态变量,多年平均气候数据作为驱动变量运用光合生产模型对上海城市植被净第一性生产力状况进行了估算,模拟所选物种均为各群落类型的建群种,分别是香樟、悬铃木、水杉、雪松、夹竹桃、红叶李和竹。从单位面积NPP来讲,不同植被类型的NPP差异明显,其年NPP随常绿针叶林、落叶针叶林、落叶灌丛、常绿阔叶林、落叶阔叶林、常绿灌丛、竹灌丛依次上升。就上海市年内NPP来讲,年NPP总量为35.5Mt C,平均值为2552.98tC/(ha~*y)。其中,常绿阔叶林、落叶阔叶林、常绿针叶林、落叶针叶林、常绿灌丛、落叶灌丛、竹灌丛NPP总量依次为16.1Mt C/y、11.77Mt C/y、0.23Mt C/y、0.64Mt C/y、5.34Mt C/y、0.97Mt C/y、0.47Mt C/y,占总年NPP的比例分别为45.3%、33.1%、0.6%、1.8%、15%、2.7%、1.3%。对上海城市植被全年NPP的贡献率来讲,常绿阔叶林和落叶阔叶林贡献最多,二者占78.4%,其次为常绿灌丛,其余的四种植被共贡献了6.6%,贡献最小。3、上海城市植被年NPP分布情况是:年单位面积NPP为2552tC/(ha~*y),在对全年NPP的贡献率上,上海城市植被的净第一性生产力区域差异明显,最小值和最大值分别为459tC/(ha~*y)和2769tC/(ha~*y)。在宝山区东北部、浦东新区北部和东南部以及南汇区东北部最大,宝山区西南部、普陀区东北部、闸北区南部、虹口区西南部及浦东新区东北角的小部分区域为NPP,总量低值范围。4、上海城市植被生态系统NPP的季节变化很明显,季节时空格局存在较大差异。在对全年NPP的贡献率上,主要体现在夏季,NPP极大值为16.4821MtC,占全年净初级生产力的46.4%。四季NPP依次为:夏季)秋季)春季)冬季,NPP分别为:16.4821MtC、10.7655MtC、7.448MtC、0.8188MtC,占全年净初级生产力的比例依次为:46.4%、30.3%、20.9%、2.3%。从空间分布来讲,四季NPP变化也同样显著。四季的单位面积NPP季节平均值分别为535.41tC/ha、1184.84tC/ha、773.89tC/ha、58.87tC/ha。其中,宝山区东北角和与其相邻的浦东新区西北角地区、浦东新区东南部和南汇区的外环以内部分是上海城市植被中净第一性生产力较高的区域,均大于各季节的平均值。而NPP最小的地区则为宝山区西南部、普陀区东北部以及普陀区和闸北区邻接处,四个季节的NPP都是整个研究区域内最小的,而且年内的NPP季节变化较其它区域也变化较小。更多还原

【Abstract】 Vegetation,as an indispensable factor of the terrestrial ecosystem,plays an important role in global change. Vegetation Net Primary Productivity(NPP) is helpful to studying carbon cycle、carbon trend and carbon balance on the earth , and its sensitivity is also important to global climate. With the rapid development of RS,GIS and cyber-technology,the study by using remote sensing for NPP hastens maturely. It can monitor NPP of vegetation in a large scale fast and evaluate the productivity of the plant community in natural environment combined with these technology. So it can provides important basic information for decision department .This study aimed to explore NPP tempo-spatial patterns of Shanghai urban vegetation ecosystem by process-based model as 2006 for example. For the research purposes,Shanghai urban vegetation database have been set up,and a photosynthesis-production model have been made by VB process language consulting with TREEDYN model and TREEDEV model. With supports of database and photosynthesis-production model , net primary production (NPP)of Shanghai urban vegetation ecosystem have been quantified generally and quantificationally. With the support of the GIS technology, the kriging interpolation method was used to calculate Shanghai urban vegetation NPP .The estimated results have suggested that:1. The vegetation’s digital map of different function region of Shanghai has been made,this is a basic work of this thesis. This paper used ArcGIS Desktop 9.2 software to interpret Shanghai aerial imagemap which scale is 1:5700 .The result shows that: the green land area of Shanghai is 139.11km~2, the percentage is 20.2%;the area of park green land, residential green land, accessory green land, road green land, water-side green land and procreative green land is 18.46km~2、34.22km~2、56.28km~2、16.17km~2、3.36km~2、10.62km~2 respectively,the percentage is 13.27%、24.6%、40.46%、11.62%、2.41%、7.63% respectively.2. Based on the vegetation parameters in Shanghai as state variables , several years average weather data as driving variables , urban vegetation NPP in Shanghai was calculated using Photoproduction simulation model. The species which was used in simulating was constructive species of every community types and they are Cinnamomum camphora、Platanus acerifolia、Metasequoia glyptostroboides、Cedrus deodara、Nerium indicum、Prunus cerasifera、bamboo respectively. The NPP of unit area varys depending on different vegetation. NPP of seven vegetations increase in turn:evergreen coniferous forest<deciduous coniferous forest<deciduous bush-woods<evergreen broadleaved forest<deciduous broadleaved forest<evergreen bush-woods<bamboo bush-woods. The total year’s NPP in Shanghai is 35.5Mt C, the average value is 2552.98t C/(ha*y),in which , NPP of evergreen broadleaved forest, deciduous broadleaved forest、evergreen coniferous forest、deciduous coniferous forest、evergreen bush-woods、deciduous bush-woods is 16.1Mt C/y、11.77Mt C/y、0.23Mt C/y、0.64Mt C/y、5.34Mt C/y、0.97Mt C/y、0.47Mt C/y respectively;the percentage accounting for total NPP is 45.3%、33.1%、0.6%、1.8%、15%、2.7%、1.3%.The contribution rate of evergreen broadleaved forest and deciduous broadleaved forestis is maximum in total year’s NPP, the percentage is 78.4%, the next is evergreen bush-woods,the rest vegetation’contribution rate is minimum and the percentage is 6.6%.3. The distribution trend of year’s NPP in Shanghai is :the average value of unit area in a year is 2552t C/(ha*y), the contribution rate for total NPP has obvious diversity in different area. The maximum and minimum values is 2769t C/(ha*y) and 459t C/(ha*y).The maximum areas contain the northeastern Baoshan , northern and southeastern Pudong、northeastern Nanhui ,the minimum areas contain southwestern Baoshan , northeastern Putuo、southern Zhabei、southwestern Hongkou and northeastern corner of Pudong.4. The seasonal change of vegetation’s NPP in Shanghai is remarkable,spatio-temporal situation has obvious diversity in different season. The contribution rate of summer’s NPP for total year’s NPP is maximum in all seasons, the value is 16.4821Mt C and the percentage is 46.4% accounting for total year’s NPP. NPP of four seasonal increase in turn:winter<spring<autumn<summer, the NPP is 0.8188MtC、7.448MtC、10.7655Mt C、16.4821Mt Cin turn, and the percentage is 2.3%、20.9%、46.4%、30.3% respectively.The seasonal change of NPP in spatial distribution is visible too. The average NPP values per unit in four seasons are 535.41t C/ha、1184.84t C/ha、773.89t C/ha、58.87t C/ha respectively. NPP is higher in Northeastern corner of Baoshan、northwestern corner and southeastern of Pudong and Nanhui district which part is in Shanghai Outer Loop Line than other parts of study area. NPP’s minimum areas contain southwestern Baoshan、northeastern Putuo and the joinning part of Putuo and Zhabei district. NPP values of four seasons are minimum in all study area. Besides,the seasonal change of annual NPP is lower than other parts of study area.更多还原