Quantitative assessment of carbon sequestration service supply and demand and service flows: A case study of the Yellow River Diversion Project South Line
YANGLiwen1,2,, DONGLiqing2, ZHANGLiwei3, HEBingyu4,, ZHANGYongqing2 1. Shanxi Energy Institute, Jinzhong 030600, China2. College of Geographical Science, Shanxi Normal University, Linfen 041000, China3. School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China;4. College of Resource and Environment Sciences, Xinjiang University, Urumqi 830046, China 通讯作者:通讯作者: 何秉宇,E-mail: BYhe718@163.com 收稿日期:2018-08-10 修回日期:2018-12-18 网络出版日期:2019-03-20 版权声明:2019《资源科学》编辑部《资源科学》编辑部 基金资助:国家自然科学基金青年科学基金项目（41601182）; 山西省“1331工程”重点学科建设计划项目 作者简介: -->作者简介:杨丽雯,女,新疆乌鲁木齐人,博士,副教授,主要研究方向为生态系统服务流。E-mail: beautifullife2133@163.com
关键词：SPANs模型;固碳服务;供需平衡;服务流;引黄入晋南线 Abstract Ecosystem service flows establish connections between the supply and demand sides of ecosystem services across space and time. Understanding the transmission paths and flows of ecosystem services are conducive to the accurate assessment of ecosystem service values. Wanjiazhai Yellow River Diversion Project South Line is very important in terms of solving the water shortage problem in Taiyuan. Since a good environmental condition is essential for the sustainability of the project, quantitative research on the supply-demand balance and service flow of carbon sequestration service can provide an indicator for the environmental condition. Service Path Attribution Networks (SPANs) model is designed for the simulation and mapping of ecosystem service flows from the supply areas to the beneficiary areas. It has broad application prospects and was used in this study. To better evaluate the ecosystem carbon sequestration serve of Yellow River Diversion Project South Line, based on the SPANs model, according to the prevailing wind path in study area, the carbon sequestration service flow was quantified and mapped. The results show that the supply of carbon sequestration service remained stable, whereas the demand increased dramatically, resulting in a gradual decrease in the surplus value of supply. Therefore, the balance between the supply and demand of the service was also decreased. The stability of carbon sequestration service supply was mainly due to the small land use change rates. The total demand of carbon sequestration service and the difference between supply and demand were primarily impacted by the continuous increase in carbon emissions of thermal power plants in the area. This study revealed the change pattern and influencing factors of the balance between the supply and demand of carbon sequestration service and provided data support for local ecological environment management. Meanwhile, it can also serve as a case study of using SPANs model to analyze the carbon sequestration service flow.
Keywords：Service Path Attribution Networks;carbon sequestration service;balance between supply and demand;service flow;the Yellow River Diversion Project South Line -->0 PDF (16025KB)元数据多维度评价相关文章收藏文章 本文引用格式导出EndNoteRisBibtex收藏本文--> 杨丽雯, 董丽青, 张立伟, 何秉宇, 张永清. 固碳服务供需平衡和服务流量化评估——以引黄入晋南干线为例[J]. 资源科学, 2019, 41(3): 557-571 https://doi.org/10.18402/resci.2019.03.13 YANGLiwen, DONGLiqing, ZHANGLiwei, HEBingyu, ZHANGYongqing. Quantitative assessment of carbon sequestration service supply and demand and service flows: A case study of the Yellow River Diversion Project South Line[J]. RESOURCES SCIENCE, 2019, 41(3): 557-571 https://doi.org/10.18402/resci.2019.03.13
1 引言
生态系统固碳服务（以下简称“固碳服务”）将大气中捕获的碳固定起来,可以抵消人类向大气中排放的部分CO2,从而起到调节气候的作用,是生态系统服务中调节服务的重要组成部分[1],是生态系统服务研究领域最受关注的问题[2]。固碳服务供给量化与制图一直广受关注[3,4,5,6],然而大多数研究缺少考虑区域供需空间平衡关系和服务流传输,导致评价结果无法为决策提供可靠依据[7,8,9]。近年来一些国内外者开始关注区域间固碳服务供需平衡和服务流传输,如Sahle等[10]和年蔚等[11]分析了区域固碳服务空间平衡关系并制图,Zank等[12]和Bagstad等[13]分析了固碳服务的受益者,Schröter等[14]提出了服务流流量计算依据,李婷等[15]绘制了服务流传递示意图。上述研究均未绘制出具体的服务流传输路径图,也没有量化服务流流量,但这些工作对进一步研究固碳服务从供给到需求的传递动态非常重要。 生态系统服务流能够有效地耦合具有空间异质性特征的生态系统服务的供需,生态系统服务流的定量化是解决当前生态系统服务价值评估不精确的突破口[16]。近几年,美国佛蒙特大学基于生态系统服务人工智能（Artificial Intelligence for Ecosystem Services,ARIES）项目提出了“服务路径属性网络”（Service Path Attribution Networks,SPANs）模型[17,18]。SPANs模型集成生态学和地理学常用的模拟模型,旨在模拟生态系统服务从供给区到需求区的流动过程并绘制空间图。该模型扩展了生态系统服务的研究视角,具有广泛的应用前景,但由于模型开发和使用的时间较短,覆盖的生态系统服务类型尚不全面,且应用案例主要集中在北美洲和欧洲,案例数量有限[19]。目前利用SPANs模型来模拟某项具体的生态系统服务空间流动的案例十分缺乏[9]。 万家寨引黄入晋工程通过总干线、南干线、联接段每年向太原供水6.4亿m3,为太原市经济、社会、环境的可持续发展提供了可靠的水资源保障[20]。巩固引黄入晋工程的成果,必须有良好的生态环境支持,而固碳服务供需平衡和服务流的量化研究可作为科学依据。本文利用遥感影像、气象、水文和土地利用类型等数据,探讨固碳服务的供需时空平衡状况及影响因素,并运用SPANs模型,以主风向风场图为基础,分析服务流传输路径并量化服务流流量,以期为当地的生态环境管理决策提供支撑。
万家寨引黄入晋工程从黄河万家寨水库取水,分别向太原、大同和朔州供水。工程由总干线、南干线、联结段和北干线4部分组成。引黄入晋工程南干线位于东经111°07′35″-112°45′53″,北纬38°08′11″-39°45′21″,包括偏关县、河曲县、五寨县、神池县、宁武县、静乐县和朔城区（图1）,区域总面积1.16×104 km2。研究区属于温带大陆性气候,多年平均气温9.9℃,年降水量为415.4 mm,全年以北风和西北风为主[38]。地貌类型复杂多样,水土流失严重,植被覆盖率较低,生物多样性贫乏[39,40]。 显示原图|下载原图ZIP|生成PPT 图1研究区地理位置与高程 -->Figure 1Location and digital elevation model of the study area -->
3 结果与分析
3.1 供给
固碳服务的供给源主要为植被和土壤[12]。植被在研究区的中部地区较为丰富（图2）,主要包括五寨县、宁武县和神池县。碳储量高值主要分布于宁武县境内,神池县和五寨县次之。这些区域林地面积较大,植被类型主要为落叶阔叶林。碳储量较高的宁武县,主要植被类型为寒温性针叶林,境内有5.45万hm2原始次生林,森林覆盖率超过38%。研究区的西部以针叶林和针阔叶混交林为主,面积较大,东部以阔叶林为主。西部沿黄区域的河曲县属于典型的黄土丘陵沟壑区,土质疏松,沟壑纵横,植被稀疏。植被类型主要为蒿类草丛、白羊草和黄背草草丛,森林覆盖率仅为14.6%,水土流失严重[41],故其固碳服务供给量较低。 显示原图|下载原图ZIP|生成PPT 图2研究区2000年和2015年固碳服务供给区 -->Figure 2The supply areas of carbon sequestration service in the study area, 2000 and 2015 -->
2000—2015年,研究区地上部分、地下部分和土壤碳储量在固碳服务供给总量中所占比例分别为7.85%~7.93%、7.91%~7.93%和84.16%~84.23%,由此可见,土壤碳库是影响固碳服务供给总量的主要因素。 由于研究区1999年以来大力推行退耕还林还草政策,林地的面积维持稳定,水土流失状况得到控制,2000—2015年研究区固碳服务供给总量仅下降0.44%（图3）,主要是由于土壤碳储量下降引起的。土壤碳储量变化主要受碳库密度和土地利用类型影响。2000—2015年研究区的土壤碳储量下降0.49%。运用综合土地利用动态度（S）揭示土地利用/土地覆被类型的年变化率[42,43]。研究区S值为15.90%,表明土地利用类型的变化速率较小,因此固碳服务供给总量变化微弱。根据土地利用图计算得知,研究区农田面积减少了100 hm2,主要转化为居民建设用地。 显示原图|下载原图ZIP|生成PPT 图3研究区2000年、2005年、2010年和2015年固碳服务供给量空间分布 -->Figure 3Spatial distribution of the supply of carbon sequestration service in the study area, 2000, 2005, 2010 and 2015 -->
3.2 需求
需求区包括居民区、牲畜养殖场、农田和工厂（图4）。研究区中,朔城区的居民区分布较密集;养殖场主要分布在朔城区和静乐县;农田在各个县均有分布,其中朔城区分布较为集中;火力发电厂和热力公司各县均有分布,但神池县规模较小。 2000—2015年研究区固碳服务需求总量呈上升趋势,高等级需求区域逐渐增加,变化较快的是朔城区和宁武县（图5）。 显示原图|下载原图ZIP|生成PPT 图5研究区2000年、2005年、2010年和2015年固碳服务需求等级图 -->Figure 5The demand rank map of carbon sequestration service in the study area, 2000, 2005, 2010 and 2015 -->
时间（年份）、火力发电厂碳排放量、供暖碳排放量和居民呼吸碳排放量与固碳服务需求总量有显著相关关系（表1）,而牲畜呼吸碳排放量和农业碳排放量与需求总量无显著相关关系。随着时间的延长,固碳服务需求总量有进一步增加的趋势。 Table 1 表1 表1研究区固碳服务需求总量与其影响因素的回归方程 Table 1Regression equations for carbon sequestration service demand and influencing factors
固碳服务需求总量
相关系数
R
F
Sig.
回归方程
火力发电厂碳排放量
0.999**
0.999
655.94
0.001
Y=1.29X+231.52
供暖碳排放量
0.981*
0.981
51.68
0.019
Y=12.25X+1018.20
居民呼吸碳排放量
0.951*
0.953
20.02
0.047
Y=e(88.43-341.69/X)
时间
0.995**
0.995
181.54
0.005
Y=22.54X-43990.19
备注：时间是指2000、2005、2010和2015四个年份。 新窗口打开 朔城区人口增长和城市化水平提高较快,导致供暖面积稳定增加,由于研究区大部分地区由热力公司供暖,所以对电力的需求增加;另一方面,随着工业化水平逐年提高,为满足工业用电需求,火力发电量快速增加,因此朔城区固碳服务需求量增长在7个县区中最显著。火力发电厂碳排放量增加是固碳服务需求量增长最显著影响因素,其次是居民呼吸和牲畜呼吸碳排放量增加（表2）。 Table 2 表2 表2研究区各县区固碳服务需求量构成情况表 Table 2Composition of carbon sequestration service demand in each county
2000—2015年期间研究区内固碳服务需求总量持续快速增长,而供给总量则保持基本稳定,所以固碳服务供需盈余持续减少,但因供给量一直大于需求量,因此供需整体处于平衡状态。研究区对固碳服务供需平衡关系贡献较大的3个县分别为神池县、静乐县和五寨县,上述3个县固碳服务供给量基本稳定,同时需求变化幅度不显著,所以供需平衡维持较好,供需盈余额较大。 研究区固碳服务供给总量与火力发电厂碳排放量、供暖碳排放量、居民呼吸碳排放量、牲畜呼吸碳排放量、农业碳排放量、需求总量和供需差都无显著的相关性,表明人类的生产和生活没有充分考虑生态系统固碳服务的供给能力。回归分析显示,固碳服务总需求与供需差的相关系数为-1.00,表明供需差主要由需求决定。火力发电厂碳排放量与固碳服务需求总量之间呈显著的线性正相关,表明随着火力发电厂碳排放量的增加,固碳服务需求总量有增加的趋势。由于火力发电厂碳排放量是影响需求最显著的因素,而供需差主要由需求决定,所以火力发电厂碳排放量显著影响固碳服务的供需差,进而影响供需平衡关系。回归分析表明：火力发电厂碳排放量与固碳服务供需差之间呈显著的线性负相关,因此随着火力发电厂碳排放量的增大,供需缺口将进一步加大。农业碳排放量与固碳服务需求总量无显著关联性,表明农业生产产生的碳排放量不是显著影响研究区固碳服务供需平衡关系的因素（表1,表3,表4）。牲畜呼吸碳排放量在五寨县、神池县和静乐县是固碳服务需求量主要影响因子,然而在研究区固碳服务供需平衡关系中不具有显著作用。综上所述,工业发展是影响研究区固碳服务供需平衡的最显著因子。 Table 3 表3 表3研究区固碳服务供需平衡关系影响因素相关系数矩阵 Table 3Correlation matrix of influencing factors that affect the balance between supply and demand
时间
供给
A
B
C
D
E
需求
供需差
时间
-0.419
0.998**
0.995**
0.960*
0.653
-0.406
0.995**
-0.994**
供给
-0.419
1
-0.424
-0.332
-0.599
-0.663
-0.035
-0.469
-0.480
A
0.998**
-0.424
1
0.990*
0.946
0.698
-0.467
0.999**
-0.998**
B
0.995**
-0.332
0.990*
1
0.941
0.589
-0.387
0.981*
-0.979*
C
0.960*
-0.599
0.946
0.941
1
0.608
-0.196
0.951*
-0.953*
D
0.653
-0.663
0.698
0.589
0.608
1
-0.764
0.729
-0.733
E
-0.406
-0.035
-0.467
-0.387
-0.196
-0.764
1
-0.473
0.471
需求
0.995**
-0.469
0.999**
0.981*
0.951*
0.729
-0.473
1
-1.000**
供需差
-0.994**
-0.480
-0.998**
-0.979*
-0.953*
-0.733
0.471
-1.000**
1
注：①A代表火力发电厂碳排放量,B代表供暖碳排放量,C代表居民呼吸碳排放量,D代表牲畜呼吸碳排放量,E代表农业碳排放量。② **表示0.01水平上显著,*表示在0.05水平上显著。③ 时间是指2000、2005、2010和2015四个年份。 新窗口打开 Table 4 表4 表4研究区时间、火力发电厂碳排放量与固碳服务供需差的回归方程 Table 4Regression equations for time, carbon emissions of thermal power plants and the difference between carbon sequestration service supply and demand
固碳服务供需差
F
Sig.
回归方程
火力发电厂碳排放量
455.41
0.002
Y=-1.30X+1239.44
时间
159.96
0.006
Y=-22.67X+45708.61
注：① 回归方程的常数项和一次项系数均通过了0.05水平上的t检验。② 时间是指2000、2005、2010和2015四个年份。 新窗口打开 时间（年份）与固碳服务供给总量没有显著的相关性,这可能是因为研究区大力推行退耕还林还草工程等措施,使得林地的面积维持较稳定,水土流失得到有效治理,生态系统固碳服务的供给量稳定性较好,不随着时间而明显变动。时间与固碳服务需求总量呈正相关,与供需差呈显著负相关,表明：随着时间的推移,需求有进一步增加的趋势,而供需盈余会逐渐减少,供需平衡关系有变弱趋势（表4）。 2000—2015年河曲县和偏关县的固碳服务供需一直处于不平衡状态。其中,河曲县供需缺口问题比较突出。河曲县属于典型的黄土丘陵沟壑区,水土流失严重,森林覆盖率较低,虽然国家大力推行退耕还林还草和移民并村等措施,但是由于管护问题,经济林成活率低,长势普遍较差[44],故其固碳服务供给能力也较低。由于火力发电厂碳排放量较大,固碳服务供给量小于火力发电厂碳排放量,同时牲畜呼吸碳排放量、居民呼吸碳排放量和供暖产生的碳排放量稳定增加,使得供需缺口持续增加。偏关县林地和草地合占全县总面积的21.31%,境内丘陵起伏,沟壑纵横,受风沙和水土流失双重危害的土地面积占土地总面积的80.6%,强度以上侵蚀占水土流失总面积的80%以上,由于没有天然森林,乔木林都是人工林,以杨树为主[45],因而其固碳服务供给量较低。自1999年退耕还林还草工程实施以来,林地和草地面积稳定增加,土壤侵蚀得到控制,强度以上侵蚀降至水土流失区域总面积的70%[46],因此其固碳服务供给量较为稳定。固碳服务需求的增加主要是由火力发电厂碳排放量、供暖产生的碳排放量和牲畜呼吸碳排放量的增加引起的。朔城区2000年固碳服务供给量大于需求量,2005年、2010年和2015年均处于供不应求状况,且供需缺口持续增加（表5）。宁武县供需平衡在2000—2005年维持较好,2005—2010年逐渐变差,2015年供需失去平衡。 Table 5 表5 表5研究区2000年、2005年、2010年和2015年固碳服务供需平衡表/万t Table 5Balance between supply and demand of carbon sequestration service in the study area, 2000, 2005, 2010 and 2015 (10 thousand t)
3.4.1 服务流路径 2000年,研究区内固碳服务供给量小于需求量的县区主要为河曲县和偏关县。偏关县未被当地植被固定和土壤储存的碳,随大气运动,被输送到神池县和五寨县。由于偏关县未被固定的碳量为28.54万t,远小于神池县和五寨县固碳服务供给的盈余量,所以偏关县固碳需求缺口可能由神池县和五寨县来弥补,同时可能有一部分未被固定的碳随风运动到河曲县。由于河曲县固碳服务供给量小于需求量,所以从偏关县输送到河曲县的碳,与河曲县没有被当地固定的碳混合在一起,一部分可能被风输送到五寨县,被五寨县的植被和土壤所提供的固碳服务所消耗,另一部分可能被风输送到研究区以外。 2005年,研究区固碳服务供不应求的区域有朔城区、河曲县和偏关县。朔城区未被当地植被固定和土壤储存的碳,随风运动到神池县和宁武县。由于神池县和宁武县固碳服务的供给量大于需求量,其盈余量为198.23万t,远高于朔城区固碳服务需求量缺口,所以朔城区固碳服务需求量缺口被神池县和宁武县的植被和土壤所提供的固碳服务供给量平衡。偏关县未被当地植被固定和土壤储存的碳,一部分被风输送到了神池县和五寨县。由于偏关县固碳服务需求量缺口为39.40万t,远低于神池县消耗朔城区输送的碳量后剩余的固碳服务供给量,同时五寨县固碳服务供给也有盈余量,所以偏关县固碳服务需求缺口一部分可能被神池和五寨的固碳服务供给盈余量所平衡,另外一部分则可能被风输送到河曲县。河曲县固碳服务的供给量小于需求量,未被当地植被固定和土壤储存的碳,一部分被风输送到五寨县,被五寨县固碳服务供给赢余量所消耗,另一部分与偏关县输送来的碳一起,随北风流动到研究区外。 2010年,研究区固碳服务供不应求的区域有朔城区、河曲县和偏关县。朔城区未被本地植被固定和土壤储存的碳,被风输送到神池县和宁武县。由于神池县和宁武县固碳服务供给量大于需求量,其盈余量为分别为124.25万t和7.23万t,大于朔城区固碳服务需求量缺口,所以朔城区固碳服务需求量缺口可被神池县和宁武县2个县的固碳服务供给盈余量所平衡。偏关县未被当地植被固定和土壤储存的碳,可分为以下2部分：①一部分被风输送到了神池和五寨县。由于偏关县固碳服务需求量缺口为28.59万t,小于神池县消耗朔城区输送的碳量后剩余的固碳服务供给量,同时五寨县固碳服务供给也有盈余量,因而偏关县固碳服务需求缺口一部分可能被神池县和五寨县固碳服务供给盈余量所平衡。②一部分可能随风运动到河曲县。由于河曲县的固碳服务供给量小于需求量,从偏关县输送到河曲县的碳与河曲县的未被当地植被固定和土壤储存的碳一起运动,主要有以下2种路径：一部分被风输送到五寨县,为五寨县生态系统固碳服务供给盈余量所平衡;另一部分被北风输送到研究区以外。 2015年,研究区固碳服务供不应求的区域有朔城区、宁武县、河曲县和偏关县。朔城区未被当地植被固定和土壤储存的碳,一部分被风输送到神池县和宁武县,一部分被风输送到研究区外。神池县固碳服务供给量大于需求量,其盈余量为112.29万t,略大于朔城区输送的碳量。朔城区固碳服务需求量缺口可被神池县固碳服务供给盈余量所消耗。偏关县未被当地植被固定和土壤储存的碳,可分为以下2部分：①一部分被风输送到神池县和五寨县。由于偏关县固碳服务需求量缺口为46.23万t,小于五寨县和神池县固碳服务供给盈余量,所以偏关县固碳服务需求缺口的一部分可能被神池县和五寨县固碳服务的供给盈余量填补。②一部分可能被风输送到河曲县。由于河曲县的固碳服务供给量小于需求量,从偏关县输送到河曲县的碳,与河曲县没有被当地植被固定和土壤储存的碳一起运动,主要有以下2种路径：一部分可能被输送到五寨县,被五寨县的植被和土壤提供的固碳服务所固定;另一部分可能被风输送到研究区以外。宁武县未被当地植被固定和土壤储存的碳量为31.57万t,一部分可能被风输送到静乐县,被静乐县植被和土壤提供的固碳服务所固定;另一部分可能被风输送到研究区以外（图6）。 显示原图|下载原图ZIP|生成PPT 图6研究区2000年、2005年、2010年和2015年主风向图 -->Figure 6Prevailing wind directions in the study area, 2000, 2005, 2010 and 2015 -->
3.4.2 服务流流量 2000—2015年,研究区朔城区、河曲县、宁武县和偏关县固碳服务流流量较大,神池县、五寨县和静乐县流量较小。偏关县固碳服务流流量基本稳定,而河曲县和五寨县服务流流量略有下降,其他各县服务流流量显著上升,其中服务流流量上升较快的是神池县和朔城区（表6）。 Table 6 表6 表6研究区2000年、2005年、2010年和2015年固碳服务流流量/（t/km2） Table 6Flow rate of carbon sequestration service in the study area, 2000, 2005, 2010 and 2015 (t/km2)
HeC, ZhangD, HuangQ, et al. Assessing the potential impacts of urban expansion on regional carbon storage by linking the LUSD-urban and InVEST models [J]. Environmental Modelling & Software, 2016, 75(C): 44-58. [本文引用: 1]
[34]
WuH, GuoZ, PengC.Distribution and storage of soil organic carbon in China [J]. Global Biogeochemical Cycles, 2003, 17(2): 1048-1058. [本文引用: 1]
[35]
NiJ.Carbon storage in terrestrial ecosystems of China: Estimates at different spatial resolutions and their responses to climate change [J]. Climatic Change, 2001, 49(3): 339-358. [本文引用: 1]
[National Natural Science Foundation of China, National Earth System Science Data Platform, Scientific Data Platform for Cold and Dry Areas. The Vegetation Map of China(1: 4000000) [EB/OL]. (2017-04-20)[2018-09-10]. .]URL [本文引用: 1]
[national Natural Science Foundation of China, National Earth System Science Data Platform, Scientific Data Platform for Cold and Dry Areas. A China Soil Characteristics Dataset [EB/OL]. (2017-04-20)[2018-09-10]. .]URL [本文引用: 1]
[Yuan YY, Liu SJ.The necessity and feasibility of building reserve water resource of south main line of Wanjiazhai Yellow River Diversion Project [J]. Shanxi Water Resources, 2005, 21(5): 65-66. ] [本文引用: 1]
MA(Millennium Ecosystem Assessment). Ecosystems and Human Well-Being Synthesis[M] . Washington DC: Island Press, 2005. [本文引用: 1]
[2]
Tubiello FN, SalvatoreM, GolecR D C, et al. Agriculture, forestry and other land use emissions by sources and removals by sinks: 1990-2011 analysis [J]. Acta Oto-laryngologica, 2014, 4(7): 375-376. [本文引用: 1]
[39]
[Ma KP, Huang JH, Yu SL.Plant community diversity in Dongling mountain, Beijing, China: Ⅱspecies richness, evenness and species diversity [J]. Acta Ecologica Sinica, 1995, 15(3): 268-277.] [本文引用: 1]
[Wang PT, Zhang LW, Li YJ, et al. Spatio-temporal characteristics of the trade-off and synergy relationships among multiple ecosystem services in the Upper Reaches of Hanjiang River Basin [J]. Acta Geographica Sinica, 2017, 72(11): 2064-2078. ] [本文引用: 1]
[40]
[Jia YC, ZhangF.Species diversity of plant community alongside Wanjiazhai Yellow River Diversion Project, Shanxi [J]. Journal of Wuhan Botanical Research, 2008, 26(3): 282-287.] [本文引用: 1]
[LiuH, WuJ, Chen XL.Study on spatial-temporal change and trade-off/synergy relationships of ecosystem services in the Danjiangkou water source area [J]. Acta Ecologica Sinica, 2018, 38(13): 1-16. ] [本文引用: 1]
[41]
[Jia NF, Duan JN, Li XL, et al. Multidimensional gray forecasting for compositive effect of combating desertification: Taking Hequ County in northwest of Shanxi Province as example [J]. Journal of Desert Research, 2005, 25(5): 711-715.] [本文引用: 1]
[Li JG, WangH, WangJ, et al. Impact of urbanization on terrestrial ecosystem production using Linear Modeling for Jiangsu [J]. Resources Science, 2018, 40(1): 32-43. ] [本文引用: 1]
[Shang EP, Xu EQ.Temporal and spatial variation of main ecosystem services in Guizhou and Guangxi Karst Mountainous region [J]. Resources Science, 2017, 39(10): 2000-2015. ] [本文引用: 1]
[42]
[Liu XN, Feng ZM, Jiang LG, et al. Spatial-temporal pattern analysis of land use and land cover change in Xishuangbanna [J]. Resources Science, 2014, 36(2): 233-244.] [本文引用: 1]
[Li SC, Zhang CY, Liu JL, et al. The tradeoffs and synergies of ecosystem services: Research progress, development trend, and themes of geography [J]. Geographical Research, 2013, 32(8): 1379-1390. ] [本文引用: 1]
[43]
[Wang XL, Bao YH.Study on the methods of land use dynamic change research [J]. Progress in Geography, 1999, 18(1): 81-87.] [本文引用: 1]
[HeP.Study on problems and countermeasures in Grain for Green Project in Hequ County [J]. Shanxi Forestry Science and Technology, 2016, 4(1): 59-60.] [本文引用: 1]
[Pang QW.A Study on Suitable Site, Rational Density and Biomass of the Energy Plantations of Caragana Microphylla Lam in Loess Hilly Region of the Northwest Shanxi Province[D] . Beijing: Beijing Forestry University, 2009.] [本文引用: 1]
[XiaoY, Xie GD, Lu CX, et al. Involvement of ecosystem service flows in human wellbeing based on the relationship between supply and demand [J]. Acta Ecologica Sinica, 2016, 36(10): 3096-3102. ] [本文引用: 3]
[10]
SahleM, SaitoO, FürstC, et al. Quantification and mapping of the supply of and demand for carbon storage and sequestration service in woody biomass and soil to mitigate climate change in the socio-ecological environment [J]. Science of the Total Environment, 2017, 624: 324-354. [本文引用: 3]
[46]
[Zhang BH.Relational Analysis between Returning Farmland to Forest (Grass) Engineering and Local Economic Development in Pianguan County[D] . Taiyuan: Shanxi University, 2011.] [本文引用: 1]
[NianW, Chen YM, Gao JX, et al. Relationship between provision and reception of ecological service of carbon fixation and oxygen release Beijing-Tianjin-Hebei Region [J]. Journal of Ecology and Rural Environment, 2017, 33(9): 783-791. ] [本文引用: 2]
[47]
[ZhangY, Xie YC, Qi SS, et al. Carbon storage and spatial distribution characteristics in the Bailongjiang Watershed in Gansu based on InVEST model [J]. Resources Science, 2016, 38(8): 1585-1593.] [本文引用: 1]
ZankB, Bagstad KJ, VoigtB, et al. Modeling the effects of urban expansion on natural capital stocks and ecosystem service flows: A case study in the Puget Sound, Washington, USA [J]. Landscape & Urban Planning, 2016, 149: 31-42. [本文引用: 3]
[13]
Bagstad KJ, VillaF, BatkerD, et al. From theoretical to actual ecosystem services: Mapping beneficiaries and spatial flows in ecosystem service assessments [J]. Ecology & Society, 2014, 19(2): 706-708. [本文引用: 3]
[48]
[LiY, Chen GK, Lin DM, et al.Carbon storage and its distribution of forest ecosystems in Zhejiang Province, China [J]. Chinese Journal of Plant Ecology, 2016, 40(4): 354-363. ] [本文引用: 2]
SchröterM, Barton DN, Remme RP, et al. Accounting for capacity and flow of ecosystem services: A conceptual model and a case study for Telemark, Norway [J]. Ecological Indicators, 2014, 36(1): 539-551. [本文引用: 1]
[Zhu HJ.Research on Land Use Forecast and Valuation of Carbon Sequestration Ecosystem Service in Costal Zone of Poyang Lake[D] . Nanchang: Nanchang University, 2013. ] [本文引用: 2]
[LiT, LiJ, Wang YZ, et al. The spatial flow and pattern optimization of carbon sequestration ecosystem service in Guanzhong-Tianshui economical region [J]. Scientia Agricultura Sinica, 2017, 50(20): 3953-3969. ] [本文引用: 3]
[YangL, ZhenL, PanY, et al. Ecosystem services supply and consumption: A case in Yellow River watershed, China [J]. Journal of Arid Land Resources and Environment, 2012, 26(3): 131-138.] [本文引用: 2]
[51]
StürckJ, PoortingaA, Verburg PH.Mapping ecosystem services: The supply and demand of flood regulation services in Europe [J]. Ecological Indicators, 2014, 38(3): 198-211. [本文引用: 1]
[16]
[Liu HM, Liu LY, Ren JY, et al. Progress of quantitative analysis of ecosystem service flow [J]. Chinese Journal of Applied Ecology, 2017, 28(8): 2723-2730. ] [本文引用: 1]
[17]
VillaF, BagstadK, VoigtB, et al. Artificial Intelligence for Ecosystem Services[EB/OL]. (2016-06-07)[2018-09-10]. .URL [本文引用: 1]
[18]
Bagstad KJ, Johnson GW, VoigtB, et al. Spatial dynamics of ecosystem service flows: A comprehensive approach to quantifying actual services [J]. Ecosystem Services, 2013, 4: 117-125. [本文引用: 1]
BaróF, PalomoI, ZulianG, et al. Mapping ecosystem service capacity, flow and demand for landscape and urban planning: A case study in the Barcelona metropolitan region [J]. Land Use Policy, 2016, 57: 405-417. [本文引用: 1]
[Deng MF.A Study for Ecosystem Service Balance between Supply and Demand in Yulin City[D]. Xi'an: Northwest University, 2016.] [本文引用: 1]
[54]
Serna-Chavez HM, Schulp C JE, Van Bodegom PM, et al. A quantitative framework for assessing spatial flows of ecosystem services [J]. Ecological Indicators, 2014, 39: 24-33. [本文引用: 2]
[55]
CostanzaR.Ecosystem services: Multiple classification systems are needed [J]. Biological Conservation, 2008, 141(2): 350-352. [本文引用: 2]
[56]
VrebosD, StaesJ, VandenbrouckeT, et al. Mapping ecosystem service flows with land covers coring maps for data-scarce regions [J]. Ecosystem Services, 2015, 13: 28-40. [本文引用: 1]
[20]
[MengJ.Study on water resources real time monitoring and dispatching system for water supply area of south main line of Wanjiazhai Yellow River Diversion Project [J]. Water Resources and Hydropower Engineering, 2010, 41(7): 1-5. ] [本文引用: 1]
[Zhao WW, LiuY, FengQ, et al. Ecosystem services for coupled human. Ecosystem services for coupled human and environment systems [J]. Progress in Geography, 2018, 37(1): 139-151]. [本文引用: 1]
[21]
[Liu KR, Wang SQ, Cao MK.Carbon storage of vegetation and soil in China [J]. Science in China, 2003, 33(1): 72-80. ] [本文引用: 1]
[Xie XL, SunB, Zhou HZ, et al. Soil carbon stocks and their influencing factors under native vegetations in China [J]. Acta Pedologica Sinica, 2004, 41(5): 687-699. ] [本文引用: 2]
[HuangM, Ji JJ, Cao MK, et al. Modeling study of vegetation shoot and root biomass in China [J]. Acta Ecologica Sinica, 2006, 26(12): 4156-4163. ] [本文引用: 2]
[24]
Jackson RB, CanadellJ, Ehleringer JR, et al. A global analysis of root distributions for terrestrial biomes [J]. Oecologia, 1996, 108(3): 389-411. [本文引用: 1]
[Institute of Geography and Resources, Chinese Academy of Sciences, Resource and Environment Science Data Center of Chinese Academy of Sciences, Resource and Environment Data Cloud Platform . Remote Sensing Monitoring Data of Land Use Status in China [EB/OL]. (2017-04-20)[2018-09-10]. .]URL [本文引用: 1]
[26]
ShenQ, ChenQ, Tang BS, et al. A system dynamics model for the sustainable land use planning and development [J]. Habitat International, 2009, 33(1): 15-25. [本文引用: 2]
[27]
ZhaoC, Sander HA.Quantifying and mapping the supply of and demand for carbon storage and sequestration service from urban trees [J]. Plos One, 2015, 10(8): e0136392. [本文引用: 1]
[28]
MyhreG, ShindellD, Bréon FM.et al.Anthropogenic and Radiative Forcing [A]. IPCC. Climate Change 2013: The Physical Science Basis . Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge: Cambridge University Press, 2013. [本文引用: 2]
[Guo LJ, Gu YG.The relation between power generation capacity and power generation [J]. Science Technology and Industry, 2012, 12(12): 71-73. ] [本文引用: 1]
[General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, China National Standardization Management Committee. General Principles for Calculation of Total Production Energy Consumption (GB/T 2589-2008) [EB/OL].(2008-02-03)[2018-09-10]. .]URL [本文引用: 1]
[Climate Change Division of National Development and Reform Commission. Guidelines for the Preparation of Provincial Greenhouse Gas Inventories(Proposed Regulations) [EB/OL].(2011-05)[2018-09-10]. URL [本文引用: 1]
[32]
Villamagna AM, Angermeier PL, Bennett EM.Capacity, pressure, demand, and flow: A conceptual framework for analyzing ecosystem service provision and delivery [J]. Ecological Complexity, 2013, 15(5): 114-121 [本文引用: 1]
, 董丽青
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