Knowledge Resource Center for Ecological Environment in Arid Area
| 干旱-半干旱地区生态系统服务价值评估方法与应用 | |
| 其他题名 | Methodology and Application of Ecosystem Services Value Assessment in Arid and Semi-arid Areas |
| 李丽 | |
| 出版年 | 2018 |
| 学位类型 | 博士 |
| 导师 | 胡玉昆 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 生态系统服务价值是衡量区域生态资源环境和生态发展状况的基础，反映了生态系统服务对人类生存及社会经济可持续发展的重要程度。科学认识生态系统服务，合理评估生态系统服务价值，是改善生态环境，资源持续利用，区域可持续发展的关键，能够为绿色GDP的构建及区域发展提供决策依据。但是，目前干旱-半干旱地区生态系统服务价值评估多套用植被覆盖度较高地区的生态系统服务价值评估指标与方法，导致评估结果不准确甚至低估。本文选择新疆、甘肃、宁夏作为我国干旱-半干旱地区的典型区，从生态系统服务普遍性和特殊性的角度开展干旱-半干旱地区生态系统服务价值评估研究，并开展了生态系统服务特殊性应用研究。对于生态系统服务的普遍性，开展了研究区内生态系统普遍服务价值评估研究。根据当量价值法，对研究区内的11项生态系统服务开展了价值评估研究。利用多元数据，基于改进的模型、空间分析方法实现了调节因子的遥感反演。利用反演得到的调节因子调整了全国生态系统服务价值当量，构建了2015年研究区内生态系统普遍服务价值当量表，实现了研究区内生态系统的普遍服务价值评估，结果表明：普遍服务价值总体上呈现西北、东南高，中间低的特点，价值较高的区域主要分布在植被覆盖度较高、水热条件较好的区域。从生态系统角度来看，草地生态系统的普遍服务价值总量最大，水域生态系统次之，农田最低，水体的单位面积普遍服务价值最高，湿地生态系统次之，裸地生态系统最低。从行政区划角度来看，新疆的普遍服务价值总量最高，甘肃次之，宁夏最低，甘肃单位面积普遍服务价值最高，宁夏次之，新疆最低。 对于生态系统服务的特殊性，开展了研究区内生态系统特征服务价值研究。选取风能和太阳能作为研究区内生态系统特征服务价值评估的两项主要指标，丰富了生态系统服务价值评估指标体系。通过引入地形因子、气象因子等，发展了特征服务价值评估方法，开展研究区内生态系统特征服务价值评估，结果表明：风能潜力服务价值呈现两端低中间高的特点，2015年，研究区内生态系统的风能潜力服务价值总量是我国2015年用电总量所消耗服务价值的一倍多。由于地形因素和未利用土地的面积影响，新疆和甘肃比宁夏更适于风能资源的开发；太阳能潜力服务价值呈带状分布，主要分布在天山南缘、瓜州、敦煌地区以及塔里木盆地北缘和昆仑山东端。2015年，研究区内的太阳能潜力服务价值约为我国2015年全国用电总量消耗服务价值的10倍。新疆、甘肃和宁夏等地的太阳能潜力服务价值均比较高，适于太阳能资源的开发。在综合服务价值评估方面，系统分析了综合服务价值的空间分布及其在各县/市的分布，结果表明：研究区具有非常高的生态系统服务价值，其中特征服务价值占有不可忽略的地位。较高的综合服务价值区主要分布在新疆东部和西北角、天山山脉一线、塔里木盆地北缘、昆仑山南缘、甘肃东北部和西南部、宁夏南部。中低服务价值区主要为普遍服务价值，中、中高和高服务价值区主要为特征服务价值，其中中服务价值区主要为风能潜力服务价值，中高和高服务价值区主要为太阳能潜力服务价值。本研究系统的分析了特征服务价值的应用，结果表明：新疆、甘肃的风能潜力比宁夏高出许多，更适宜风能潜力的开发，新疆东部和甘肃的西北部是开发首选地区。太阳能开发适宜区分布广泛，新疆、甘肃和宁夏都具有较高的太阳能潜力，新疆的若羌县和哈密，甘肃的瓜州县和肃北蒙古族自治县，宁夏的盐池和同心县是太阳能开发的首选地区。本文以新疆、甘肃和宁夏作为干旱-半干旱地区的典型代表，开展生态系统服务价值的评估方法与应用研究，以风能和太阳能为主要评估指标的特征服务价值和普遍服务价值共同揭示了新疆、甘肃、宁夏地区生态系统服务价值的空间分布，为干旱-半干旱地区生态系统服务价值评估提供了方法借鉴，为干旱-半干旱地区特征服务价值的开发利用提供了科学参考，对我国西部干旱-半干旱地区的生态保护、资源开发及其可持续发展具有重要意义。 |
| 英文摘要 | Ecosystem service value (ESV) is the basis of measuring regional ecological resources and development. It reflects the importance of ecosystem services to human survival and socio-economic sustainable development. Perceiving and assessing ecosystem services scientifically and reasonably, is the key to improving ecological environment, sustainable utilization of resources and regional sustainable development. It also can provide decision-making basis for the green GDP construction and regional development. However, the ecosystem services value assessment in arid and semi-arid areas is more applicable to the ecosystem services value evaluation indicators and methods in higher vegetation coverage areas, which may leads to inaccurate or even underestimated. This paper chooses Xinjiang, Gansu, Ningxia as the typical area in arid and semi-arid area of China, from the commonness and characteristics aspect, to carry out the ecosystem services value assessment in semi-arid areas, and also carry out the application of the feature service study.For the universality of ecosystem services, the ecosystem common services value assessment in the study area was carried out. According to the equivalent value method, eleven ecosystem services value were assessed. Based on multiple sources of data, improved model and spatial analysis method, the adjustment factors was simulated. Based on these simulated regulation factors, the national ecosystem service value equivalent factor were adjusted to construct the ecosystem common service value equivalent factor of research area in 2015 and realized the ecosystem common services value assessment in research area. The result shows that the common service value is high in northwest and southeast of the research area and is low in middle. The high common service value often distribute in the area of high vegetation coverage and better hydrothermal conditions. From the perspective of ecosystem, grassland has the largest common service total value, water body is in second place, and farmland is the lowest. Water body has the highest common service unit value, wetland is in second place, and bareland is the lowest. From the perspective of administrative district, Xinjiang has the largest common service total value, Gansu is in second place, and Ningxia is the lowest. Gansu has the highest common service unit value, Ningxia is in second place, and Xinjiang is the lowest.For the specialization of ecosystem services, this study conducted the ecosystem feature service value assessment in arid and semi-arid area. Wind and solar energy was selected as the two key evaluation indicators of ecosystem features service in the research area, which are enriched the indicators system of the ecosystem service evaluation. A feature service value assessment method was developed through introducing the topographic and meteorological factors and the feature service value was assessed in the research area. The results show that the wind potential service value is high in amphi and low in middle. The total wind potential service value in the research area is more than the service value of total electricity consumption of China in 2015. Due to topographic factors and the large unused land area, Xinjiang and Gansu, are more suitable for wind energy development than Ningxia. The solar potential services value are zonal distribution. They are mainly distributed in the southern margin of the Tianshan Mountain, Guazhou, and Dunhuang, the northern margin of the Tarim Basin and the east of Kunlun Mountain. The total solar potential services value in the study area are ten times of total electricity consumption service value of China in 2015. Xinjiang, Gansu and Ningxia all have high solar potential energy services value, which are suitable for the solar energy development.On the aspect of the integrated service value assessment, the distribution characteristics of integrated service value in counties / cities are systematically analyzed. The results show that there are very high ecosystem services value in the arid and semi-arid area, where the feature service value share an important status which can not be ignored. The higher integrated service value area are mainly distributed in the east and northwest of Xinjiang, Tianshan Mountain, the northern margin of Tarim Basin, the southern margin of Kunlun Mountain, the northeast and southwest of Gansu, and southern Ningxia. The common services value are mainly distributed in the mid-low value areas. The feature services value are mainly distributed in the middle, mid-high and high value areas, where the wind potential services value are distributed in the middle value areas, the solar potential services value are distributed in the mid-high and high value areas.This study also systematically analyzed the application of the feature service value. The results show that the wind energy potential in Xinjiang and Gansu is much higher than in Ningxia, which are more suitable for the wind energy development. Eastern Xinjiang and northwestern Gansu is the preferred development area. The areas which are suitable for solar energy development are widely distributed. Xinjiang, Gansu and Ningxia all have high solar potential. Hami and Ruoqiang County in Xinjiang, Guazhou and Subei Mongolian Autonomous County in Gansu, Yanchi and Tongxin County in Ningxia are preferred areas of solar energy development.This study conducted the ecosystem services value assessment in Xinjiang, Gansu and Ningxia, which are typical area in arid and semi-arid areas. The feature and common services value revealed the spatial distribution characteristics of the ecosystem services value in Xinjiang, Gansu and Ningxia, provides reference for the ecosystem service value assessment and feature services value development. It is also have great significance on ecological protection, resource development and sustainable development in arid and semi-arid areas of Western China. |
| 中文关键词 | 干旱-半干旱区 ; 生态系统服务价值 ; 普遍服务 ; 特征服务 |
| 英文关键词 | Arid and Semi-arid areas Ecosystem Services Value Common Services Feature Services |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 地图学与地理信息系统 |
| 来源机构 | 中国科学院遥感与数字地球研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/288054 |
| 推荐引用方式 GB/T 7714 | 李丽. 干旱-半干旱地区生态系统服务价值评估方法与应用[D]. 中国科学院大学,2018. |
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