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GEOGRAPHICAL RESEARCH >

2017 , Vol. 36 >Issue 9: 1742 - 1754

DOI: https://doi.org/10.11821/dlyj201709011

Articles

Spatial and temporal variation analysis of ecosystem water use efficiency in Central Asia and Xinjiang in recent 15 years

  • ZOU Jie , 1 ,
  • DING Jianli , 1 ,
  • YANG Shengtian 1, 2
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  • 1. College of Resources and Environment Sciences, Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China
  • 2. College of Water Sciences, Beijing Normal University, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing 100875, China

Received date: 2017-03-04

  Request revised date: 2017-07-11

  Online published: 2017-09-15

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《地理研究》编辑部
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Abstract

It is a great significance to study the carbon-water cycle which accurately evaluates the temporal and spatial variabilities of ecosystems water use efficiency (WUE). In this study, the linear regression method and Mann-Kendall test were used to study the variabilities of spatial pattern of GPP, ET and WUE in the five Central Asian countries and Xinjiang from 2000 to 2014, then, the results of parameter tests of GPP, ET and WUE were combined and classified to analyze the causes of changes of WUE. The results showed that: (1) GPP, ET and WUE in the study area had no significant changes in time series. The spatial distribution of WUE had significant increases in the northern part of Kazakhstan, Ili Valley and alpine region in Kyrghyzstan, and had decreases in the south Xinjiang and the irrigated area of Uzbekistan. (2) The main land cover types which led to changes of WUE were farmland and grassland, and area with the medium density population had the great changes of WUE. (3) The​increased WUE was resulted from the increased GPP and the decreased ET. The increased GPP was due to the increased precipitation and the Green for Grain Project, and the decreased ET was due to the response of vegetation to drought stress; the decreased WUE was mainly due to the changes of crops planted and unreasonable water use in the irrigated agricultural area in Central Asia and Xinjiang. This study on the basis of the variabilities of spatial pattern of WUE can provide a theoretical basis for the successful implementation of the "Belt and Road Initiative".

Key words： water use efficiency; five Central Asian countries; Xinjiang; trend characteristics

Cite this article

ZOU Jie , DING Jianli , YANG Shengtian . Spatial and temporal variation analysis of ecosystem water use efficiency in Central Asia and Xinjiang in recent 15 years[J]. GEOGRAPHICAL RESEARCH, 2017 , 36(9) : 1742 -1754 . DOI: 10.11821/dlyj201709011

1 引言

植被是陆地生态系统的主体,在土壤圈、水圈和大气圈的物质循环和能量流动中起到桥梁作用,尤其是在调节陆地生态系统碳水平衡和全球气候变化等方面发挥了重要作用。陆地生态系统绿色植物通过光合作用来吸收大气的CO2,同时通过叶片蒸腾作用散失体内水分,植物通过这一过程来调节叶片与大气之间的物质能量循环。每单元碳吸收所损失的水分比率叫做水分利用效率（Water Use Efficiency,WUE）[1],WUE是理解陆地生态系统新陈代谢的重要参数[2,3]。叶片碳水量的变化与大尺度的生态系统有着密切关系[4]。在田间尺度上,关于植物个体吸收CO2、蒸腾损失的水分已有大量研究,且已深入到生理生态学上[5-7]。本文使用生态系统WUE进行计算,生态系统碳吸收使用总初级生产力（Gross Primary Production,GPP）,水分损失定义为植被冠层的蒸腾作用和土壤中的蒸发作用损失的水分总和。叶片尺度上的WUE受制于气孔导度,而生态系统尺度上WUE受制于蒸散发（evapotranspiration,ET）和植被生态学和形态学。随着气候变化和人类活动的加剧,全球生态系统发生巨大变化,对生态系统WUE的深入了解有助碳水循环过程研究和优化水资源管理。
过去几十年里,中亚地区土地利用/覆盖经历了重大而频繁的变化[8]。苏联时期,哈萨克斯坦北部地区的大面积草原转变成了农田,苏联解体后一部分农田又被废弃,变成了荒地[9,10]。乌兹别克斯坦部分土地退化,主要由土壤次生盐渍化引起[11]。除了农田废弃外,中亚地区从1990年以来,因为局部地区退耕还草政策而导致牲畜数量的下降也影响着土地覆盖和土地利用变化[12]。此外,大量研究还得出结论,中亚地区夏季降水的减少和冬季降水的增加影响着水资源的再分配,影响中亚植物的生长和空间格局分布[13,14]。中亚地区人口分布高度异质化,大部分地区人口极稀疏,而部分地区人口非常密集,在人口密集区未来将会面临巨大的人口增长压力[15]。
近年来,大量学者利用遥感数据进行生态系统WUE研究。例如,Tang等基于遥感数据对全球WUE时空变化分析得出,土地利用/覆盖变化是导致了全球WUE的下降的主要原因[16]。Yang等通过比较全球不同陆地生态系统WUE对干旱的响应,讨论了生态系统应对干旱的响应机制[17],Huang等利用1982-2008的遥感数据,预测了CO2浓度增加、气候变化、氮沉降等情景模式下的全球WUE变化,得出WUE在这3种情景下均会增加[18]。Huang等分析全球WUE对于气候变化的季节响应时,得出北半球春天WUE增加的原因是温度的上升促进了GPP的增长[19]。Tian等通过分析2000-2010年间黄土高原的WUE时空变化,不同植被类型WUE的影响因子不同[20]。Zhang等通过研究气候变化下东亚WUE变化,总结出东亚地区WUE的高值区,低值区等[21]。
本文在已有的大量研究基础上,分析中亚五国及新疆生态系统WUE的时空变化,同时将变化结果分成不同国家、不同人口密度、不同植被类型进行讨论,最后结合GPP、ET、WUE趋势检验值将研究区WUE进行分类,同时分析中亚生态系统的动态变化及其影响因素,以期通过分类深入了解WUE变化规律及其主要影响因素,为区域经济环境发展和生态环境保护提供理论基础和实践条件。

2 研究方法与数据来源

2.1 研究区概况

本文主要集中在苏联学者定义的中亚五国,即哈萨克斯坦（Kazakhstan,KAZ）、土库曼斯坦（Turkmenistan,TKM）、乌兹别克斯坦（Uzbekistan,UZB）、吉尔吉斯斯坦（Kyrgyzstan,KGZ）、塔吉克斯坦（Tajikistan,TJK）与中国新疆地区。在这6个地区中,哈萨克斯坦面积最大为272.7万km2,塔吉克斯坦面积最小为14.2万km2。研究人口密度分异较大,在乌兹别克斯坦人口从每5人/km2至7000人/km2之间分布。研究区海拔高度自西向东逐渐升高,从土库曼斯坦和哈萨克斯坦西部的里海地区向东部山区逐渐升高,在新疆两大盆地下降。气候类型自北向南从半干旱区向干旱区过渡。该地区冬季寒冷,且气温自北向南逐渐增加。中亚五国北部地区主要是雨养农业,而在南部有大面积的灌溉区,新疆农业主要集中在山前冲积平原,且多为灌溉农业。

2.2 数据来源

本文研究时间跨度为2000-2014年,所采用的数据均来自MODI产品数据,包括GPP（MOD17A2）,ET（MOD16A2）产品数据。数据选择每年植被生长的4-10月,数据空间分辨率为1 km。
土地覆盖类型产品数据MCD12Q1数据,空间分辨率为1 km,时间分辨率为1年。本文将稀疏灌木林和郁闭灌木林组合为1类。通过计算得出中亚五国及新疆主要的土地覆盖分类比例为：草地（26.91%）,荒漠（24.61%）,灌木林（11%）,农田（9.34%）,森林（13.21%）,本文分析数据排除荒漠分类,因为在ET产品上,大部分荒漠上没有数据。
人类直接影响其周围的生态系统,可以对生态系统变化造成巨大影响。采用Ellis等于2008年提出的人类学生物群落数据[22]划分出人口密集区,住宅区和偏远区来分析计算结果,根据其定义住宅区每平方公里多于10人,人口密集区每平方公里多于1人少于10人,偏远地区每平方公里少于1人,将这3种分类重新定义为高人口密度区、中人口密度区、低人口密度区。数据来自于http://ecotope.org/anthromes/v2/data/,选择离研究时间最近的2000年数据。
应用全球人类影响指数（Global Human Influence Index,HILL）[23]来评价人类活动对中亚地区陆地生态系统WUE的影响。数据空间分辨率为1 km,全球HILL的数值范围为0~64,0代表没有人类影响,64代表可能的最大人类影响。本文中HILL的最大值为60,但仅占研究区0.01%面积,HILL为5的所占面积最大,占研究区13.6%。研究区面积的85%区域HILL值小于18。

2.3 研究方法

2.3.1 非参数趋势检验 评估时间序列下WUE变化的时空规律,通过Mann-Kendall方法逐象元计算Z值。大量研究使用Mann-Kendall方法进行趋势分析,该方法主要分析变量的变化趋势和确定长时间序列下变量变化的显著性,该方法主要步骤如下：
Z c = s - 1 var s , s > 0 0 , s = 0 s - 1 var s , s < 0 （1）
s = ∑ i = 1 n - 1 ∑ k = i + 1 n sign x k - x i （2）
var ( s ) = n ( n - 1 ) ( 2 n + 5 ) 18 （3）
sign ( x k - x i ) = 1 , x k - x i > 0 0 , x k - x i = 0 - 1 , x k - x i < 0 （4）
式中：xk 、xi表示研究样本（GPP、ET和WUE）的时间序列的数据集合;n是数据集合的长度; sign 为符号函数。在给定显著性水平α下,当|Zc|>u1-α/2时,表示研究的时间序列数据在α水平上显著的变化,其中,±Z1-α/2是标准正态偏差。Z=±2.576表示显著性水平α=0.01,Z=±1.96表示显著性水平α=0.05。一般取α=0.05,当|Zc|>1.96时表示时间序列置信水平α<0.05,研究样本在时间序列上有显著性变化。
2.3.2 WUE分类 根据Mann-Kendall方法计算出GPP、ET、WUE长时间序列下的非参数检验值,将WUE在时间序列分成增加和下降两类,再根据GPP与ET的检验值,将WUE细分成6类,具体分类见表1。表中U代表上升,D代表下降,字母分类简写中,第一个字母代表WUE变化,第二个字母代表GPP变化,第三个字母代表ET变化,例如UUU代表WUE、GPP、ET同时上升。
Tab. 1 The classification of WUE

表1 WUE分类方法

WUE GPP ET 分类简写
上升 上升 上升 UUU
上升 下降 UUD
下降 下降 UDD
下降 下降 下降 DDD
下降 上升 DDU
上升 上升 DUU
2.3.3 不同国家、土地覆盖、人类生态群落趋势结果统计分析 因为遥感数据的数量巨大,为了避免各数据的自相关性,本文没有采用差异性分析来比较不同分组之间的差异。参考Foody等提出的方法[24,25],通过等式来比较不同分组间的差异。具体方法如下：
H ~ 0 : P 1 - P 2 ≥ 0.05 （5）
将H~0分解为两部分：
H ~ 01 : P 1 - P 2 ≥ 0.05 H ~ 02 : P 1 - P 2 ≤ - 0.05 （6）
式中：P1、P2分别为不同组间变化象元占该组总象元的百分比。例如,P1为农田WUE显著增加的象元数占农田总象元数的比例,P2为草地WUE显著增加的象元数占草地总象元数的比例,通过P1与P2的差值来判定不同分组间的差异。当结果满足H~0时,两组间有显著性差异,当拒绝H~01和H~02时,说明两组间没有显著性差异。

3 结果分析

3.1 中亚五国及新疆地区WUE的时间变化

为研究中亚五国及新疆WUE随时间的变化的规律,选取2000-2014年间GPP、ET、WUE的月平均值进行时序分析。由图1可知,研究区WUE在2000-2014年间整体无明显变化。15年中,2000-2006年WUE保持在一定水平上且变化不大,2007-2011年间值较小,其中2007年较2006年下降29.07%。2012-2014年开始上升,2012年较2011年增加122.48%,增加显著。WUE年内变化趋势具有一定的规律性,从4月开始逐渐增加,增加到最大值,快速下降,呈现倒“V”字变化。15年间WUE达到最大值的月份不同,大部分集中在7-8月,但也有少数年份WUE最大值出现在6月和9月。
Fig. 1 The variation of WUE in five Central Asian countries and Xinjiang region from 2000 to 2014

图1 2000-2014年中亚5国及新疆地区WUE的变化

研究区GPP与WUE变化趋势相似。其中2012-2014年间GPP值较大。年内变化同样呈现倒“V”字变化,最大值集中在5-6月。ET整体呈现下降趋势,其中2002-2007年之间ET值高于其他年份。ET年内变化规律为“N”字型变化,从春季到夏季持续上升,到达最大值后开始下降,9月到达最小值,10月略有回升。

3.2 中亚五国及新疆地区WUE的空间格局变化

由图2可以看出,研究区GPP变化呈现一定规律性,GPP显著增加的区域为新疆天山北坡一带,哈萨克斯坦东部地区以及巴尔喀什湖周边地区,吉尔吉斯斯坦中部地区。GPP显著下降的区域哈萨克斯坦西南部的里海沿岸低地,乌兹别克斯坦东部、南部阿姆河上游部分地区,阿姆河下游沿岸灌溉区,新疆天山以南的喀什绿洲。图中白色区域代表的GPP无显著变化。
Fig. 2 The changes of GPP in five Central Asian countries and Xinjiang region

图2 中亚五国及新疆地区GPP变化趋势

中亚五国及新疆ET的空间变化如图3所示,整体上研究区ET下降区域面积显著大于ET增加区域面积。ET显著下降的区域主要有3个部分,哈斯克斯坦西部地区的图尔盖高原;哈萨克丘陵的北部地区;新疆伊犁河谷的大面积区域。ET显著增加的主要区域是新疆的山前绿洲（渭干河—库车河绿洲、阿克苏绿洲、喀什绿洲）。
Fig. 3 The changes of ET in five Central Asian countries and Xinjiang region

图3 中亚五国及新疆地区ET变化趋势

由图4可以看出,2000-2014年15年间中亚五国及新疆生态系统WUE发生了巨大的变化。整体上WUE显著上升区域面积大于显著下降区域面积,说明15年间研究区WUE呈现增加趋势。WUE增加的区域包括哈萨克斯坦北部大面积区域,吉尔吉斯斯坦,中国伊犁河谷及天山北坡。WUE下降区域面积虽然较小,但也具有一定的规律性,主要集在中国新疆南部阿克苏绿洲、喀什 地区,乌兹别克斯坦东南部、塔吉克斯坦西南部以及土库曼斯坦东南部 地区。
Fig. 4 The changes of WUE in five Central Asian countries and Xinjiang region

图4 中亚五国及新疆地区WUE变化趋势

表2表示的是不同国家GPP、ET、WUE变化面积占该国面积的百分比。吉尔吉斯斯坦GPP增加最为明显,该国23.4%区域GPP有明显上升趋势。乌兹别克斯坦GPP下降比例最大。各国ET上升的面积比例并不大且各国间无差异,但ET下降面积比例差异明显,ET下降比例最大的是国家是哈萨克斯坦,该国27.5%区域显著下降。各国WUE上升比例差异较大,吉尔吉斯斯坦上升比例最大（71.7%）且显著高于其他国家,WUE下降面积比例最大的乌兹别克斯坦,这说明该国大部分区域近15年间有不合理用水现象,导致水资源浪费。土库曼斯坦WUE显著下降面积比例也是中亚五国及新疆中最大的,说明该国也存在着水资源利用不合理现象。整体上看,中亚五国及新疆的GPP增加的面积比例大于GPP下降的比例,ET下降区域大于增加区域,WUE增加的区域大于下降的区域。
Tab.2 The percentage of the area where WUE changed obviously in five Central Asian countries and Xinjiang region (%)

表2 中亚5国和新疆地区WUE显著变化面积的百分比（%）

GPP ET WUE
显著上升 显著下降 显著上升 显著下降 显著上升 显著下降
XJ 9.2BC 0.9A 2.7A 6.7B 19.2B 2.0AB
UZB 1.6AB 13.1B 0.8A 3.5AB 5.1A 7.0B
TKM 0.4A 4.9A 0.4A 1.1A 0.5A 3.3AB
TJK 8.3BC 1.3A 1.1A 0.5A 24.0B 5.2B
KGZ 23.4D 0.3A 0.5A 2.7AB 71.7D 0.0A
KZA KZA 2.2A 0.4A 27.5C 63.0C 0.1A

注：大写字母代表不同分组间的等值比较,例如第一列相同字母代表不同国家GPP显著上升的比例相同,不同字母代表不同国家GPP上升比例有差异,下同。

人口密度是影响全球陆地变化的主要因子。为了更好地了解人类对WUE的影响,本文通过高、低、中密度人口区的分组来比较GPP、ET、WUE的变化结果。由表3中可以看出,低密度人口区GPP变化最为剧烈,低密度人口区人类干扰少,其GPP变化的主要驱动力是气候变化。GPP变化最小的是中密度人口区。高密度人口区ET上升比例最大,ET下降最明显的是中密度人口区。整体上WUE上升面积均高于下降面积,增加最为明显的是中密度人口区,其55.4%的区域显著上升。高密度人口9.2%区域WUE显著下降,其下降比例高于中、低密度人口区。
Tab.3 The percentage of the area where WUE changed obviously in each population density (%)

表3 不同人口密度WUE显著变化面积百分比（%）

GPP ET WUE
显著上升 显著下降 显著上升 显著下降 显著上升 显著下降
高密度人口区 18.7B 7.9B 7.4B 11.8A 41A 9.2B
低密度人口区 44.5C 19.4C 0.3A 14.2A 36.5A 0.4A
中密度人口区 8.3A 2.4A 0.9A 23.5B 55.4B 1.1A
图5表示的是不同人类影响因子与GPP、ET、WUE变化之间的关系,其中纵坐标代表的是变化象元占总象元的百分比。从图5a可知,WUE上升比例显著高于GPP与ET上升比例,这说明WUE变化更为剧烈,GPP与ET变化更为平缓,且HILL为15~30时WUE变化出现峰值。由图可知,人类影响因子范围是30~50时,GPP与WUE出现下降峰值,这说明人类活动剧烈区,GPP与WUE下降最为明显,人类影响因子范围是5~30时,ET下降程度最大,且下降峰值高于GPP与WUE下降峰值。结合图5可以看出,WUE上升与ET下降的变化趋势一致,这说明研究区WUE上升主要受ET的影响。由图b可知WUE下降趋势与GPP下降趋势一致。综上,在人类影响因子低中等范围内,研究区WUE上升最为明显,且主要受ET下降的影响;在高等人类影响因子范围内WUE下降最为明显,且主要受相同人类影响因子区GPP下降的影响。
Fig.5 The percentage of WUE under different HILLs

图5 不同人类影响因子下WUE变化的百分比

由表4可以得出,草地GPP增加最为明显,上升面积比例为9.2%,下降面积仅为2%,农田虽然GPP上升比例很高（8.5%）,但下降也很显著（6.3%）。各土地覆盖类型的ET上升区域均不大,且互相之间差异不显著,ET下降区域面积差异显著,下降面积比例最大的是草地（23.8%）,其次是农田（22.1%）。WUE增加最为明显的是农田（75.5%）和草地（54.2%）,而WUE下降面积比例最大的是农田,为5.1%。
Tab.4 The percentage of WUE which changed obviously under different land cover patterns (%)

表4 不同土地覆盖类型下WUE显著变化的百分比（%）

GPP ET WUE
显著上升 显著下降 显著上升 显著下降 显著上升 显著下降
灌木 2.9A 5.3A 1.1A 4.5A 14.0A 4.8A
草地 9.2B 2.0A 1.0A 23.8B 54.2C 0.3A
农田 8.5B 6.3A 1.9A 22.1B 75.5D 5.1A
森林 3.8AB 1.9A 0.3A 5.1A 41.6B 0.5A
整体上,GPP上升面积比例高于下降面积比例,GPP增加面积比例最多的是草地,农田GPP上升与下降面积比例相当,ET下降面积比例高于上升面积比例,下降面积比例最大的是草地和农田,WUE上升面积比例高于下降面积比例。

3.3 中亚五国及新疆WUE分类空间格局变化

为了进一步准确描述WUE格局的变化过程,将WUE分成上升和下降两大类,结合GPP、ET和WUE的变化结果,再细分为六小类。从图6可以看出,WUE增加的主要区域——哈萨克斯坦被分成了三个不同的变化部分,即图6中的1区域~区域3。区域1位于巴尔喀什湖北部地区,WUE的增加是GPP与ET共同增加的结果,而GPP的增加高于ET的增加量。区域2在该国中北部,WUE的增加是GPP增加与ET降低的结果,区域3在该国西部,GPP与ET共同下降,结合图1~图3,该地区GPP下降不显著,但ET下降显著,GPP下降的程度低于ET下降的程度导致WUE的增加。区域4位于阿姆河下游地区,该地区的GPP、ET均下降。区域5位于新疆南疆地区,该地区GPP显著下降与ET显著增加共同导致了WUE的显著下降。区域6位于新疆北疆沿天山一带,是GPP与ET共同增加的结果,但GPP增加的程度低于ET增加的程度,因在本文中面积较小,将不参与讨论。
Fig. 6 The changes of different classes of WUE in five Central Asian countries and Xinjiang region

图6 中亚五国及新疆地区不同分类WUE趋势变化

4 讨论

4.1 不确定分析

本文中基于遥感手段获得的中亚和新疆GPP或ET存在一定的不确定性。首先,本文没有考虑研究区的放牧强度,从理论上GPP、ET的计算应该加上被动物啃食的部分,因此GPP与ET值可能被低估,其结果WUE的评估值或许可反映实际情况。其次,本文WUE值的计算来自MODIS的GPP和ET产品,GPP的计算是用简单的线性公式,其值高度依赖输入参数,尤其是最大光能利用效率,不同植被类型的光能利用效率值是一个固定值,没有考虑因为土壤类型,气候等因素造成光能利用效率值差异;另外计算GPP、ET值时,输入的气象尺度和MODIS数据尺度不一致,这样也会造成数据的不确定性。在干旱区,由于植被稀疏,地表裸露,基于遥感获得NDVI并没有真实反映地表植被状况,基于NDVI估算的GPP和ET存在一部分估算值与现实不符。本文在计算中去除了植被覆盖稀疏的荒漠生态系统,增加了结果的可靠性。
Tang等利用MODIS成品数据和通量塔实测数据计算全球生态系统WUE,其中通过遥感数据计算出全球WUE平均值为1.71 g C/kg H2O,通过通量塔得出全球WUE平均值为1.89 g C/kg H2O;同时还利用通量塔数据验证了不同植被类型遥感数据计算结果的可靠性,通过拟合不同植被类型的遥感数据与实测数据,R2值均高于0.7,其中草地R2值0.96,农田R2值为0.74,实测数据与遥感数据具有高度一致性[16]。本文中,15年间生态系统WUE平均值为2.65 g C/kg H2O,高于全球平均值。同时将本文不同植被类型的WUE与已有研究对比从图7中可以看出,本文灌木和草地的WUE均高于其他研究[21,26]。这是由于干旱区植被普遍受到水分胁迫,通常会很珍惜利用水分,具有较高的WUE,农田WUE较低主要与干旱区农业灌溉方式有关。
Fig. 7 The comparison of WUE among different studies

图7 不同研究WUE的比较

4.2 WUE空间格局成因分析

15年间GPP呈显著上升趋势,与很多研究结果得出中亚植被整体改善的研究结果一致[27,28]。近十几年来,中亚地区干旱气候与人类活动均发生了明显的时空变化,这些变化通过不同的作用过程对生态系统产生影响,气候的暖湿化和干旱化引起植被生长的改善和退化[29],人类活动改变土地利用方式进而引起生态系统的变化。发生GPP增加的主要区域是新疆北疆地区、巴尔喀什湖周围、吉尔吉斯斯坦与塔吉克斯坦等高山地区。新疆（尤其是北疆）降水的增加[30],植被显著变绿[31],同时,在新疆退耕还林还草政策的实施也促进了植被的改善。中亚东南部高海拔山区,降水多气温低,植被生长主要受制于温度[32],因此,近年来的中亚地区温度的增加促进了该地区植被的生长[33]。巴尔喀什湖周边植被的改善得益于禁牧行为。乌兹别克斯坦GPP下降最为明显,限制该地区GPP变化的主要因素的水资源减少。全球变暖的大背景下,世界上河流的径流量均有所下降[34],阿姆河上游地区大力建造水利设施,修建大坝,减少下游灌溉区和生态系统的用水[35-37]。在植物生长季,上游大坝拦水发电时,下游国家河流流量将会较少全年径流量的10%,径流量的下降严重影响了农业的发展,加快了该地区GPP的下降[38]。本文中,ET上升均不明显,显著下降的区域主要是为自然植被区,通过不同植被类型比较可以得出,ET下降的区域主要是草地。有研究得出,近20年来,中亚地区ET显著下降而自然植被区对ET的下降贡献大于农田,2000-2009年北部低山丘陵区—平原区ET显著下降[39]。本文将研究区WUE变化分为6类,具体讨论如下：
（1）区域1：UUU。区域1位于哈萨克斯坦东北部的巴甫洛达尔地区,GPP、ET、WUE在15年间有着相同的变化趋势,三者均有增加,由图2可以看出,该地区GPP有显著上升,ET虽然有所增加,但无显著性水平（图3）。该地区主要植被覆盖类型是草地,有研究得出,该地区部分区域湿度有显著增加的趋势[40],Wright等在2014年研究发现这一特殊区域温度与4-6月北大西洋涛动指数呈现负相关关系,降雨与植被指数呈现正相关,同时在过去15年间4-6月北大西洋涛动指数呈现下降趋势,这也就说明该地区在过去15年间温度是有所上升的[10]。降水的增加和温度的升高同时促进了该地区植被的生长,加之前文中提到的禁牧行为共同作用增加了GPP。同时该地区影响植被生长的主要因子是水分,且水分的影响程度高于温度的影响,温度的升高虽然增加了ET,但增加不明显,GPP增加的程度大于ET增加程度,这也是导致该地区WUE上升的原因。
（2）区域2：UUD。区域2位于哈萨克斯坦的中北部,土地利用方式的改变是该地区WUE发生变化的主要原因。自从苏联解体后,哈萨克斯坦北部雨养农业区发生了巨大的变化,因为人口压力的减少,在过去十年间该地区雨养农业耕地面积持续减少[41,42]。该地区大面积土地退耕,由雨养农田退耕成林地和草地,因此,GPP呈现上升趋势,同时,近来来该地区降水的增加和温度的升高,促进了植被的生长。植被的改善降低了土壤被阳光直射的面积,减少了土壤蒸散发量,自然植被的蒸腾速率低于同等条件下的农作物。因此生态系统ET的下降是土壤蒸发和植物蒸腾共同下降的结果。综上,退耕还林还草可以提高生态系统的WUE,在相同水分条件的情况下生态系统生产力增加更为显著。
（3）区域3：UDD。区域3位于哈萨克斯坦的西北部,属于典型干旱区,WUE增加同时GPP与ET共同下降。通过资料调查,过去15年间该地区遭遇了重大的旱灾[43,44]。当遭遇干旱时,干旱区自然植被在多年的进化中具有一定的抵抗力,通过自身生理变化和形态变化应对逆境,植被根系长度及叶片气孔导度的变化是植被应对干旱的主要表现形式,当干旱发生时,植被通过增加地下根系长度来吸收更深土壤的水分保证基本生长所需水分,同时植被通过降低叶片气孔导度,来降低蒸腾耗水与呼吸消耗。植被蒸腾的下降与土壤水分的下降（降水的减少,土壤深层水分被植被利用）导致ET快速下降。WUE的上升也正是草地生态系统应对干旱的适应对策。在干旱区,这种物种相对单一的生态系统应对逆境的抵抗力稳定性很高,但恢复力稳定性较弱,若干旱没有到达生态系统所能承受的上限阈值,生态系统将会通过自身调节保持稳定,一旦逆境突破抵抗力的上限,生态系统将会很难恢复。因此,当有重大气候事件发生时,应该重点保护恢复力稳定性低的生态系统,减少人为破坏,实现生态可持续发展。
（4）区域4：DDD。该区域位于咸海南部的乌兹别克斯坦和土库曼斯坦的灌溉区,WUE下降的是GPP与ET同时下降（图2、图3）,GPP下降的程度更高。解释这一现象可能的原因是农作物种类的变化,在过去20年间,为了缓解粮食危机,冬小麦耕地面积及产量持续增加,大面积棉花地已转换成小麦地,2003年之前,棉花产量高于小麦产量,2003年以后小麦产量已与棉花产量相当,乌兹别克斯大约有1.44万km2冬小麦,1.31万km2棉花[45],冬小麦现在已经是该地区的最主要农作物。其次,冬小麦相比棉花耗水量更低,在该地区有研究得出,棉花的需水量大于9000 m3/hm2,而冬小麦的需水量为5400 m3/hm2[46]。冬小麦耗水量小,且面积不断增加,该地区WUE应该增加,本文研究结果与此结论相反。究其原因,该地区冬小麦在秋季播种,早春收割,而本文研究时间是4-10月,正是冬小麦的休耕期,所以导致本文主要监测的是处于生长期的棉花,棉花面积的减少降低导致了GPP的下降。研究时间的选择导致小麦节水的特性没有体现出来,ET下降程度低于GPP的下降程度,最终导致该地区在4-10月WUE下降。但这并不是该地区WUE变化的真实情况,因此在今后的该地区生态系统及植被变化研究中,应该注意冬季植被变化研究。
（5）区域5：DDU。该区域位于新疆南疆绿洲,WUE显著下降因为GPP的下降和ET上升造成的,该区有大面积的棉田。棉花种植面积及灌溉方式的改变可能是WUE下降的主要原因。2000年以后,新疆在绿洲农业区由大水漫灌、沟灌发展到膜下滴灌。春季播种覆膜,膜下除了棉花幼苗以外的所有植被幼苗很难破膜而出,而棉花幼苗叶片无法完全覆盖地面,裸土与幼苗组成的混合象元导致春季GPP下降,而棉花面积逐年扩大[47],该区春季GPP的下降是该地区GPP呈下降趋势。棉花属于高蒸腾高耗水植物,夏季的生长需要大量的水分来维持,ET值的增加一部分来源于棉花的高蒸腾。面积日益增加绿洲农业灌溉用水占用内陆河的生态用水以及大量开发地下水,绿洲外围荒漠生态系统生态用水减少抑制了荒漠植物的生长,一方面导致研究区GPP的下降,另一方面植被的减少致使大量裸地暴露,夏季高温环境,土壤的增散发量增加ET值。综上,GPP的减少由春季棉田和绿洲外围GPP共同贡献,而ET的增加由于棉花的高蒸腾以及绿洲外围裸土蒸散发共同作用的。

5 结论

（1）研究区GPP、WUE季节内呈现倒“V”字变化,ET季节内呈现“N”字变化,GPP、ET、WUE在15年间无显著变化;WUE空间变化分布差异明显,整体上WUE显著上升面积大于显著下降面积;其中显著增加的区域为哈萨克斯坦北部,新疆伊犁河谷和吉尔吉尔斯坦高山地区,下降区域为新疆南疆绿洲以及乌兹别克斯坦灌溉区。
（2）吉尔吉斯斯坦WUE上升比例最大（71.7%）且显著高于其他国家,WUE下降面积比例最大的乌兹别克斯坦（7%）;研究区WUE变化的主要土地覆盖类型是农田和草地;WUE发生变化较大的区域为中密度人口区;在人类影响因子低中等范围内,研究区WUE上升最为明显,在高等人类影响因子范围内WUE下降最为明显,且主要受相同人类影响因子区GPP下降的影响。
（3）研究区不同分类下的WUE时空变化成因各不相同,WUE上升主要由于受到全球气候变化下降水增加、政府政策导向退耕还林还草导致的GPP增加,以及干旱胁迫下植被生理抗逆导致的ET显著下降,WUE下降主要由于农作物类型转变及灌溉农业区不合理用水情况造成的。
致谢：论文的数据处理、修改和英文润色得到了新疆大学资源与环境科学学院戴岳老师、王飞老师和中科院成都生物研究所丁俊祥博士的大力帮助,在此表示感谢！

The authors have declared that no competing interests exist.

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[Guo Ying, Han Ruilian, Liang Zongsuo.Effect of soil drought on growth and water use efficiency characteristics of four native gramineous grasses in Loess Plateau. Acta Prataculturae Sinica, 2010, 19(2): 21-30.]

[3]
Jassal R S, Black T A, Spittlehouse D L, et al.Evapotranspiration and water use efficiency in different-aged Pacific Northwest Douglas-fir stands. Agricultural & Forest Meteorology, 2009, 149(6-7): 1168-1178.We used the eddy-covariance technique to measure evapotranspiration ( E) and gross primary production (GPP) in a chronosequence of three coastal Douglas-fir ( Pseudotsuga menziesii) stands (7, 19 and 58 years old in 2007, hereafter referred to as HDF00, HDF88 and DF49, respectively) since 1998. Here, we focus on the controls on canopy conductance ( g c), E, GPP and water use efficiency (WUE) and the effect of interannual climate variability at the intermediate-aged stand (DF49) and then analyze the effects of stand age following clearcut harvesting on these characteristics. Daytime dry-foliage Priestley–Taylor α and g c at DF49 were 0.4–0.8 and 2–6 mm s 611, respectively, and were linearly correlated ( R 2 = 0.65). Low values of α and g c at DF49 as well at the other two stands suggested stomatal limitation to transpiration. Monthly E, however, showed strong positive linear correlations to monthly net radiation ( R 2 = 0.94), air temperature ( R 2 = 0.77), and daytime vapour pressure deficit ( R 2 = 0.76). During July–September, monthly E (mm) was linearly correlated to monthly mean soil water content ( θ, m 3 m 613) in the 0–60 cm layer ( E = 453 θ 61 21, R 2 = 0.69), and GPP was similarly affected. Annual E and GPP of DF49 for the period 1998–2007 varied from 370 to 430 mm and from 1950 to 2390 g C m 612, respectively. After clearcut harvesting, E dropped to about 70% of that for DF49 while ecosystem evapotranspiration was fully recovered when stand age was 6512 years. This contrasted to GPP, which varied hyperbolically with stand age. Monthly GPP showed a strong positive linear relationship with E irrespective of the stand age. While annual WUE of HDF00 and HDF88 varied with age from 0.5 to 4.1 g C m 612 kg 611 and from 2.8 to 4.4 g C m 612 kg 611, respectively, it was quite conservative at 655.3 g C m 612 kg 611 for DF49. N-fertilization had little first-year response on E and WUE. This study not only provides important results for a more detailed validation of process-based models but also helps in predicting the influences of climate change and forest management on water vapour and CO 2 fluxes in Douglas-fir forests.

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[4]
Keenan T F, Hollinger D Y, Bohrer G, et al.Increase in forest water use efficiency as atmospheric carbon dioxide concentrations rise. Nature, 2013, 499(7458): 324-327.Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata-small pores on the leaf surface that regulate gas exchange-to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation-climate models.

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[5]
王鹏勃, 李建明, 丁娟娟, 等. 水肥耦合对温室袋培番茄品质、产量及水分利用效率的影响. 中国农业科学, 2015, 48(2): 314-323.

[Wang Pengbo, Li Jianming, Ding Juanjuan, et al.Effect of water and fertilizer coupling on quality, yield and water use efficiency of tomato cultivated by organic substrate in bag. Scientia Agricultura Sinica, 2015, 48(2): 314-323.]

[6]
邢英英, 张富仓, 吴立峰, 等. 基于番茄产量品质水肥利用效率确定适宜滴灌灌水施肥量. 农业工程学报, 2015, 31(S1): 110-121.研究滴灌施肥条件下水肥组合对温室番茄根系生长、产量品质和水肥利用效率的影响,并运用多元回归分析和空间分析相结合的方法,寻求满足单目标最大的灌水施肥制度,以及综合评价产量品质和水分利用效率的水肥调控效应,提出同时满足高产优质高效的最接近的灌水施肥制度。通过小区试验,设灌水和施肥(N-P2O5-K2O)2因素,3个滴灌水量(高水:100%ET0、中水:75%ET0、低水:50%ET0,ET0是参考作物蒸发蒸腾量)和3个施肥水平(高肥:240-120-150 kg/hm2、中肥:180-90-112.5 kg/hm2、低肥:120-60-75 kg/hm2)。结果表明,番茄产量、水分利用效率、肥料偏生产力和品质受灌水和施肥影响显著。产量与灌水量和施肥量正相关;减小灌水量和增大施肥量,水分利用效率增大;增大灌水量和降低施肥量,肥料偏生产力增大。维生素C和番茄红素随施肥量的增加先增大后降低(中水除外),可溶性糖随施肥量增加而降低(中肥除外),可溶性固形物和糖酸比分别在中水与低水、高水与低水之间差异显著(P0.05)。根质量、根长、根表面积及根体积与产量有显著的线性正相关关系。通过多元回归分析和空间分析得出,灌水量为159 mm,施肥量为479.4、404.4和382.8 kg/hm2时,水分利用效率、番茄红素和糖酸比最大;灌水量为279 mm,施肥量为510 kg/hm2时,产量最大;灌水量为262 mm,施肥量为225 kg/hm2时,肥料偏生产力最大。产量和品质同时达到大于等于85%最大值的灌水施肥区间大约为210~230 mm和385~453 kg/hm2,产量、水分利用效率和品质同时达到大于等于85%最大值的最接近灌水施肥区间为198~208 mm和442~480 kg/hm2。此研究为当地温室番茄滴灌施肥生产过程中水肥科学管理提供指导依据。

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[Xing Yingying, Zhang Fucang, Wu Lifeng, et al.Determination of optimal amount of irrigation and fertilizer under drip fertigated system based on tomato yield, quality, water and fertilizer use efficiency. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(S1): 110-121.]

[7]
于文颖, 纪瑞鹏, 冯锐, 等. 不同生育期玉米叶片光合特性及水分利用效率对水分胁迫的响应. 生态学报, 2015, 35(9): 2902-2909.利用大型移动防雨棚开展了玉米水分胁迫及复水试验,通过分析玉米叶片光合数据,揭示了不同生育期水分胁迫及复水对玉米光合特性及水分利用效率的影响。结果表明:水分胁迫导致玉米叶片整体光合速率、蒸腾速率和气孔导度下降以及光合速率日变化的峰值提前;水分胁迫后的玉米叶片蒸腾速率、光合速率和气孔导度为适应干旱缺水均较对照显著下降,从而提高了水分利用效率,缩小了与水分充足条件下玉米叶片的水分利用效率差值;在中度和重度水分胁迫条件下,玉米叶片的水分利用效率降幅低于光合速率、蒸腾速率和气孔导度的降幅, 有时甚至高于正常供水条件下的水分利用效率;适度的水分胁迫能提高玉米叶片的水分利用效率,从而增强叶片对水分的利用能力,抵御干旱的逆境;水分亏缺对玉米光合速率、蒸腾速率及水分利用效率的影响具有较明显滞后效应,干旱后复水,光合作用受抑制仍然持续;水分胁迫时间越长、胁迫程度越重,叶片的光合作用越呈不可逆性;拔节-吐丝期水分胁迫对玉米叶片光合作用的逆制比三叶-拔节期更难恢复。

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[Yu Wenyin, Ji Ruipeng, Feng Rui, et al.Response of water stress on photosynthetic characteristic and water use efficiency of maize leaves in different growth stage. Acta Ecologica Sinica, 2015, 35(9): 2902-2909.]

[8]
Klein I, Gessner U, Künzer C.Generation of Up to Date Land Cover Maps for Central Asia.Novel Measurement and Assessment Tools for Monitoring and Management of Land and Water Resources in Agricultural Landscapes of Central Asia .Switzerland :Springer International Publishing, 2014.

[9]
De Beurs K M, Henebry G M. Trend analysis of the Pathfinder AVHRR Land (PAL) NDVI data for the deserts of central Asia. IEEE Geoscience & Remote Sensing Letters, 2004, 1(4): 282-286.of deserts and semideserts in the selected central Asian ecoregions, a significant upward trend in NDVI is evident during the tenure of NOAA-11 (1989-1994). This trend is not found during any other period. We argue that the data from the PAL NDVI dataset for NOAA-11 will pose problems for land surface change analyses, if these significant sensor-related artifacts are ignored. We do not find these artifacts in data from the other three satellites (NOAA-7, NOAA-9, and NOAA-14). We suggest that the comparison of data from any combination of these three AVHRRs can be used for land surface change analyses, but that the inclusion of NOAA-11 AVHRR NDVI data in trend analyses may result in the detection of spurious trends.

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[10]
Wright C K,De Beurs K M, Henebry G M. Land surface anomalies preceding the 2010 Russian heat wave and a link to the North Atlantic oscillation. Environmental Research Letters, 2014, 9(9): 124-239.The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April–May–June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to a warmer-than-normal early growing season was consistent with a persistently negative phase of the North Atlantic oscillation (NAO). Regression analyses showed that early season vegetation productivity in the EWB is a function of both the winter (December–January–February; DJF) and AMJ phases of the NAO. Land surface anomalies preceding the heat wave were thus consistent with highly negative values of both the DJF NAO and AMJ NAO in 2010. (letter)

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[11]
Sommer R, Glazirina M, Yuldashev T, et al.Impact of climate change on wheat productivity in Central Asia. Agriculture Ecosystems & Environment, 2013, 178(2): 78-99.Climate change (CC) may pose a challenge to agriculture and rural livelihoods in Central Asia, but in-depth studies are lacking. To address the issue, crop growth and yield of 14 wheat varieties grown on 18 sites in key agro-ecological zones of Kazakhstan, Kyrgyzstan, Uzbekistan and Tajikistan in response to CC were assessed. Three future periods affected by the two projections on CC (SRES A1B and A2) were considered and compared against historic (1961鈥1990) figures. The impact on wheat was simulated with the CropSyst model distinguishing three levels of agronomic management. Averaged across the two emission scenarios, three future periods and management scenarios, wheat yields increased by 12% in response to the projected CC on 14 of the 18 sites. However, wheat response to CC varied between sites, soils, varieties, agronomic management and futures, highlighting the need to consider all these factors in CC impact studies. The increase in temperature in response to CC was the most important factor that led to earlier and faster crop growth, and higher biomass accumulation and yield. The moderate projected increase in precipitation had only an insignificant positive effect on crop yields under rainfed conditions, because of the increasing evaporative demand of the crop under future higher temperatures. However, in combination with improved transpiration use efficiency in response to elevated atmospheric CO 2 concentrations, irrigation water requirements of wheat did not increase. Simulations show that in areas under rainfed spring wheat in the north and for some irrigated winter wheat areas in the south of Central Asia, CC will involve hotter temperatures during flowering and thus an increased risk of flower sterility and reduction in grain yield. Shallow groundwater and saline soils already nowadays influence crop production in many irrigated areas of Central Asia, and could offset productivity gains in response to more beneficial winter and spring temperatures under CC. Adaptive changes in sowing dates, cultivar traits and inputs, on the other hand, might lead to further yield increases.

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[12]
Karnieli A, Gilad U, Ponzet M, et al.Assessing land cover change and degradation in the Central Asian deserts using satellite image processing and geostatistical methods. Journal of Arid Environments, 2008, 72(11): 2093-2105.Soil and vegetation degradation around watering points has been observed in many drylands around the world. It can be recognized in spaceborne imagery as radial brightness belts fading as a function of distance from the water wells. The primary goal of the study was to characterize spatial and temporal land degradation/rehabilitation in the Central Asian drylands. Tasseled Cap's brightness index was found to be the best spectral transformation for enhancing the contrast between the bright-degraded areas close to the wells and the darker surrounding areas far from and in-between these wells. Semi-variograms were derived to understand the spatial structure present in the spaceborne imagery of two desert sites and in three key time periods (mid-late 1970s, around 1990, and 2000). A geostatistical model, namely the kriging interpolation technique, was applied for smoothing brightness index values extracted from 30 to 80 m spatial resolution images in order to assess spatial and temporal land-cover patterns. Change detection analysis, based on the kriging prediction maps, was performed to assess the direction and intensity of changes between the study periods. These findings were linked to the socio-economic situation before and after the collapse of the Soviet Union that influenced the grazing pressure and hence the land-use/land-cover state of the study sites. The study found that degradation occurred in some areas due to recent exploration and exploitation of the gas and oil reserves in the region. Another area was subject to rehabilitation of the rangeland due to a dramatic decrease in the number of livestock due to socio-economical changes after the independence of Kazakhstan in 1991.

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[13]
Beurs K M D, Henebry G M. Vegetation Phenology in Global Change Studies. Phenology: An Integrative Environmental Science. Milwaukee: Springer Netherlands, 2013.

[14]
Zonn I S, Kostianoy A G.The Turkmen Lake Altyn Asyr. The Turkmen Lake Altyn Asyr and Water Resources in Turkmenistan, 2013, 28: 159-175.Abstract Pharmaceutical compounds comprise a widely employed group of therapeutic agents now considered as emerging micropollutants. This chapter summarizes the state of the art in the degradation of pharmaceuticals by fungi in liquid matrices (with emphasis on white-rot fungi), including the use of both whole cells and fungal enzymes. The identification of the metabolites produced as well as the proposed degradation pathways available for some drugs are discussed. The information is organized according to the activity of the pharmaceutical compounds, grouped in: anti-inflammatory/analgesic drugs, psychiatric drugs, lipid regulators, antibiotics and other antimicrobial agents, 尾-blockers, estrogens, and iodinated contrast media. Considering the interest in potential application of fungal treatments in future real scale bioremediation of effluents, the ecotoxicology of the process is included when available.

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[15]
Siegfried T, Bernauer T, Guiennet R, et al.Will climate change exacerbate water stress in Central Asia?. Climatic Change, 2012, 112(3): 1-19.How much will climate change damage the European economy? Which geographical areas would be the most affected? Which sectors are most vulnerable? Where and why will there be gains from climate change? How sectoral policies should be changed to consider climate impacts and adaptation? These questions are relevant for designing and prioritising adaptation strategies, as stressed by the European Commission White Paper on Adaptation (European Commission 2009 ). Within that context, the main motivation of the PESETA research project (Projection of Economic impacts of climate change in Sectors of the European Union based on boTtom-up Analysis) has been to contribute to a better understanding of the possible physical and economic impacts induced by climate change in Europe over the 21st century, paying particular attention to the sectoral and geographical dimensions of impacts (Ciscar et al. 2009 ; Ciscar et al. 2011a ). There are two approaches in the literature used to estimate the economic imp ...

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[16]
Tang X, Li H, Desai A R, et al.How is water use efficiency of terrestrial ecosystems distributed and changing on Earth?. Scientific Reports, 2013, 4: 7483-7483.A better understanding of ecosystem water-use efficiency (WUE) will help us improve ecosystem management for mitigation as well as adaption to global hydrological change. Here, long-term flux tower observations of productivity and evapotranspiration allow us to detect a consistent latitudinal trend in WUE, rising from the subtropics to the northern high-latitudes. The trend peaks at approximately 516N, and then declines toward higher latitudes. These ground-based observations are consistent with global-scale estimates of WUE. Global analysis of WUE reveals existence of strong regional variations that correspond to global climate patterns. The latitudinal trends of global WUE for Earth鈥檚 major plant functional types reveal two peaks in the Northern Hemisphere not detected by ground-based measurements. One peak is located at 206,306N and the other extends a little farther north than 516N. Finally, long-term spatiotemporal trend analysis using satellite-based remote sensing data reveals that land-cover and land-use change in recent years has led to a decline in global WUE. Our study provides a new framework for global research on the interactions between carbon and water cycles as well as responses to natural and human impacts

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[17]
Yang Y, Guan H, Batelaan O, et al.Contrasting responses of water use efficiency to drought across global terrestrial ecosystems. Scientific Reports, 2016, 6: 1-8.Abstract Krabbe disease (KD) is a neurodegenerative disorder caused by the lack of 脦虏- galactosylceramidase enzymatic activity and by widespread accumulation of the cytotoxic galactosyl-sphingosine in neuronal, myelinating and endothelial cells. Despite the wide use of Twitcher mice as experimental model for KD, the ultrastructure of this model is partial and mainly addressing peripheral nerves. More details are requested to elucidate the basis of the motor defects, which are the first to appear during KD onset. Here we use transmission electron microscopy (TEM) to focus on the alterations produced by KD in the lower motor system at postnatal day 15 (P15), a nearly asymptomatic stage, and in the juvenile P30 mouse. We find mild effects on motorneuron soma, severe ones on sciatic nerves and very severe effects on nerve terminals and neuromuscular junctions at P30, with peripheral damage being already detectable at P15. Finally, we find that the gastrocnemius muscle undergoes atrophy and structural changes that are independent of denervation at P15. Our data further characterize the ultrastructural analysis of the KD mouse model, and support recent theories of a dying-back mechanism for neuronal degeneration, which is independent of demyelination.

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[18]
Huang M, Piao S, Sun Y, et al.Change in terrestrial ecosystem water use efficiency over the last three decades. Global Change Biology, 2015, 21(6): 2366-2378.Abstract Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.000102g C02m61202mm61102yr611 under the single effect of rising CO2 (‘CO2’), climate change (‘CLIM’) and nitrogen deposition (‘NDEP’), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (610.000502g C02m61202mm61102yr611), which differs from process-model (0.006402g C02m61202mm61102yr611) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt, GPP×VPD/TR) in response to rising CO2, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon–water interactions over terrestrial ecosystems under global change.

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[19]
Huang M, Piao S, Zeng Z, et al.Seasonal responses of terrestrial ecosystem water use efficiency to climate change. Global Change Biology, 2016, 140(6): 2704-2710.Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions, and is largely attributed to the physiological effects of rising CO2. The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET) and transpiration-based WUE (WUEt, the ratio of GPP and transpiration), is analyzed from 0.5掳 gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m-2 mm-1 yr-1 for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2 and NDEP.

[20]
Tian Z, Jian P, Wei L, et al.Spatial-temporal patterns of water use efficiency and climate controls in China's Loess Plateau during 2000-2010. Science of the Total Environment, 2016, 565: 105-122.Accurate assessments of spatial–temporal variations in water use efficiency (WUE) are important for evaluation of carbon and water balances. In this study, the spatial and temporal patterns of WUE and associated climate controls in China's Loess Plateau are investigated over 2000–2010 by utilizing remote sensing data and multiple statistical methods; which provides a greater understanding about how WUE changed after the Grain to Green Program (GTGP) launched. Carbon sequestration (i.e., net primary productivity, NPP) is estimated with the CASA model and water consumption (i.e., evapotranspiration, ET) is obtained from the MODIS product (i.e., MOD16). Our results identify an increasing trend in the regional mean NPP that amounted to 7.59302g02C/m 2 ·yr with an average value of 310.03502g02C/m 2 ·yr. Changes in ET are segmented into three stages, the growth (20000261022003), decline (2004–2006) and stable (2007–2010) stages. Regional WUE is measured at 0.91502g02C/mm·m 2 and shows an upward trend at a rate of 0.02702g02C/mm·m 2 ·yr. Spatially, significant regional heterogeneity is found in both NPP and WUE with gradients decreasing from the southeast to the northwest, but sharp rises detected in northern Shaanxi. At the biome level, the annual average WUE of the four groups decrease in the order of grasslands02>02woodlands02>02shrublands02>02croplands. Moreover, all biomes in the grassland ecosystems exhibit a growth in WUE as does the arid desert zone in the northwestern region, suggesting that vegetation in moderately water-deficient areas may have a higher tolerance to drought. Among different meteorological factors, precipitation and drought severity index (DSI) in the Loess Plateau show a latitudinal zonality and influences the WUE, which indicated that the moisture rather than temperature would be the major control factor of the regional WUE. Finally, significant variation in vegetation WUE sensitivity in response to meteorological factors is noted. Temperature is found to be the dominant driving factor of shrublands WUE, whereas precipitation primarily influenced the WUE of grasslands, croplands, and woodlands.

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[21]
Zhang F, Ju W, Shen S, et al.How recent climate change influences water use efficiency in East Asia. Theoretical and Applied Climatology, 2014, 116(1): 359-370.Water use efficiency (WUE), defined as the ratio of gross primary productivity to evapotranspiration, is an important indicator of the trade-off between water loss and carbon gain. We used a biophysical process-based model to examine the relative importance of climate-induced changes in meteorological factors and leaf area index (LAI) on the changes in WUE in East Asia. Validation showed that our simulation could capture the magnitudes and variations of WUE at 18 flux sites in Asia. Regional results indicated that the highest WUE occurred in boreal forests at high latitudes and the lowest WUE in desert areas of China. Changes in meteorological factors negatively affected WUE in the northwestern, northern, and eastern study regions. Changes in LAI had determinant impacts on changes in WUE in most areas except for those with sparse or low-density vegetation (e.g., western interior China, southeast island countries) where meteorological factors dominated. We conclude that, aside from the impact of meteorological factors on WUE, climate-induced changes in LAI may play a prominent role in regulating WUE changes.

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[22]
Ellis E C, Ramankutty N.Putting people in the map: anthropogenic biomes of the world. Front, Ecol, Environ., 6: 439-447. Frontiers in Ecology & the Environment, 2008, 6(8): 439-447.

[23]
Sanderson E W, Jaiteh M, Levy M A, et al.The Human Footprint and the Last of the Wild: The human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards, of nature, whether we like it or not. BioScience, 2002, 77(10): 891-904.

[24]
Foody G M.Classification accuracy comparison: Hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority. Remote Sensing of Environment, 2009, 113(8): 1658-1663.The comparison of classification accuracy statements has generally been based upon tests of difference or inequality when other scenarios and approaches may be more appropriate. Procedures for evaluating two scenarios with interest focused on the similarity in accuracy values, non-inferiority and equivalence, are outlined following a discussion of tests of difference (inequality). It is also suggested that the confidence interval of the difference in classification accuracy may be used as well as or instead of conventional hypothesis testing to reveal more information about the disparity in the classification accuracy values compared.

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[25]
Robinson A P, Froese R E.Model validation using equivalence tests. Ecological Modelling, 2004, 176(3-4): 349-358.Model validation that is based on statistical inference seeks to construct a statistical comparison of model predictions against measurements of the target process. Previously, such validation has commonly used the hypothesis of no difference as the null hypothesis, that is, the null hypothesis is that the model is acceptable. This is unsatisfactory, because using this approach tests are more likely to validate a model if they have low power. Here we suggest the usage of tests of equivalence, which use the hypothesis of dissimilarity as the null hypothesis, that is, the null hypothesis is that the model is unacceptable. Thus, they flip the burden of proof back onto the model. We demonstrate the application of equivalence testing to model validation using an empirical forest growth model and an extensive database of field measurements. Finally we provide some simple power analyses to guide future model validation exercises.

DOI

[26]
Yang Y, Guan H, Shang S, et al.Toward the use of the MODIS ET product to estimate terrestrial GPP for nonforest ecosystems. IEEE Geoscience & Remote Sensing Letters, 2014, 11(9): 1624-1628.Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data (MOD17), based on the light-use-efficiency algorithm, have been widely used to assess large-scale carbon budgets. However, systemic errors of this product have been reported, particularly for nonforest ecosystems. Here, we test a simple and operational way to estimate GPP in nonforest ecosystems by inverting the MODIS evapotranspiration (ET) product (MOD16) using ecosystem water use efficiency (WUE = GPP/ET) . Field measurements from 17 nonforest AmeriFlux sites of GPP were used for validation. Results show that the inverted GPP from MOD16 (MOD16 GPP) agrees better with the observed GPP than MOD17 does. The overall root-mean-square error (RMSE) and mean bias of MOD16 GPP are 19.63 g C/m2/8-day and -4.06 g C/m2 /8-day, respectively, which are lower than the corresponding values of MOD17 GPP ( RMSE = 23.82 g C/ m2/8-day and mean bias = -9.07 g C/m2/8-day). This finding suggests the potential to achieve a better assessment of GPP for nonforest ecosystems with a fine resolution.

DOI

[27]
Propastin P A.Inter-annual changes in vegetation activities and their relationship to temperature and precipitation in Central Asia from 1982 to 2003. Journal of Environmental Informatics, 2008, 12(2): 75-87.ABSTRACT. We analyzed inter-annual trends in annual and seasonal vegetation activities in Central Asia from 1982 to 2003 and their correlation to climate variability using the NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) dataset and a gridded climate dataset. The results indicate a significant increase in NDVI with a value of 11.35% over the growing season during the 22-year period. Totalled over the entire vegetated area, about 35% of all pixels exhibited significant upward trend in growing season NDVI. We found that NDVI increase in spring was the main contributor to the general upward trend, the spring NDVI increased in more than 50% of all pixels and showed an average value of 13.58%. Correlation analysis indicated a gradual rise in temperature as the only factor controlling trend in spring NDVI. Significant increase in vegetation activity was also identified for summer season, but its amplitude (9.23%) and comprising area (25.13% of all vegetated pixels) were less than for spring. Downward trends in growing season NDVI occurred in 2.17% of the total vegetated area. The greening trends of spring, growing season and summer NDVI strongly related with the climatic parameters: for each land cover type, we found significant correlation with spring temperature and total precipitation; 75% of all upward trends in growing season NDVI were explained by the combination of these both variables. We found that the NDVI trends and their climatic correlates demonstrate great spatial variability at the scale of individual land cover types and at per-pixel scale and proofed that the land use change caused by the constitutional change in the 1991 has substantial control on the vegetation trends. Increased vegetation growth indicated through the analysis of NOAA AVHRR NDVI time-series suggests an increasing carbon stock in biomass of ecosystems in Central Asia.

DOI

[28]
索玉霞, 王正兴, 刘闯, 等. 中亚地区1982年至2002年植被指数与气温和降水的相关性分析. 资源科学, 2009, 31(8): 1422-1429.本文利用1982年~2002年间AVHRR-NDVI数据和气候研究组（CRU）降水与气温数据，分析了中亚5国21年来NDVI年际与季节变化特征及其与气候因子的相关关系。结果表明：①在植被生长季，53%地区NDVI年变化率 <±0.0005NDVI/a（无变化），40%地区NDVI年变化率>0.0005 NDVI/a（增加），6%地区NDVI年变化率< -0.0005 NDVI/a（下降）；按照植被覆盖类型，除常绿林、高山草甸年均NDVI呈一定的上升趋势，变化率分别为0.0014 NDVI/a（p<sub>0.05</sub>=0.001），0.0009 NDVI/a（p<sub>0.05</sub>=0.001），落叶林、草原、作物、草原化荒漠NDVI没有显著变化（p<sub>0.05</sub>>0.05）；②年均NDVI与降水、温度相关性分析结果表明，49.00%的地区年均NDVI与年降水量呈正相关，52.33%的地区NDVI与春季降水量正相关，33.69%的地区NDVI与夏季降水量正相关，70.00%的地区年均NDVI与各季气温弱相关，仅17.78%的地区年均NDVI与年均气温正相关；6种植被类型NDVI与降水、气温相关关系为，常绿林、高山草甸年均NDVI与年均气温分别低度、显著正相关性，相关系数分别为0.432（p<sub>0.05</sub>=0.05）、0.557（p<sub>0.05</sub>=0.009）；草原、作物与年降水量分别显著、低度正相关，相关系数分别为0.511（p<sub>0.05</sub>=0.018）、0.476（p<sub>0.05</sub>=0.029）；落叶林NDVI与夏、冬季降水量低度正相关，相关系数分别为0.415（p<sub>0.05</sub>=0.061）、0.461（p<sub>0.05</sub>=0.035）；草原化荒漠NDVI与春季降水量正相关但不显著，相关系数为0.415（p<sub>0.05</sub>=0.061）。

[Suo Yuxia, Wang Zhengxing, Liu Chuang, et al.Relationship between NDVI and precipitation and temperature in middle Asia during 1982-2002. Resources Science, 2009, 31(8): 1422-1429.]

[29]
孙鹏, 张强, 白云岗, 等. 基于马尔科夫模型的新疆水文气象干旱研究. 地理研究, 2014, 33(9): 1647-1657.在气象干旱SPI和水文干旱SRI的二维变量干旱状态的研究基础上,通过一阶马尔科夫链模型对二维变量干旱状态进行频率、重现期和历时分析,并预测未来非水文干旱到水文干旱的概率,研究表明:1开都河、和田河在干旱形成中危害大,阿克苏河在干旱演变中危害大,开都河和叶尔羌河在干旱持续中危害大。开都河和叶尔羌河主要以气象水文干旱为主,和田河和阿克苏河以水文干旱为主。2开都河连续湿润或者干旱的概率最大,状态2(气象、水文湿润)与状态4(气象、水文干旱)、状态5(气象湿润、水文干旱)的相互转移概率低,和田河和开都河状态4不能一步转移到状态2。3在长期干旱预测中,塔河流域从状态2达到状态4或者状态5的概率最低,开都河(或和田河)从非水文干旱状态到状态4的概率最大(或最小),从非水文干旱状态到状态5的概率最小(或最大)。

DOI

[Sun Peng, Zhang Qiang, Bai Yungang, et al.Transitional behaviors of hydrometeorological droughts in Xinjiang using the Markov chain model. Geographical Research, 2014, 33(9): 1647-1657.]

[30]
陈晨, 郑江华, 刘永强, 等. 近20年中国阿尔泰山区冰川湖泊对区域气候变化响应的时空特征. 地理研究, 2015, 34(2): 270-284.and both the number and area of glacial lakes increased during the past two decades. (2) The responses of ice-scour lakes and moraine-dammed lakes to climate change were totally different. (3) With temperature rising, the peak of profit and loss of ice-scour lakes reached a higher altitude, and the variation of moraine-dammed lakes became more unstable. (4) Westerly circulation had a significant influence on the glacial lakes, the precipitation on the west-facing slope was sufficient, therefore the west-facing ice-scour lakes varied little, while the west-facing moraine-dammed lakes kept expanding as the profit constantly overmatched the loss. (5) Owing to the lower elevation, glacial lakes in this region were sensitive to climate change than other alpine-plateau areas in western China over the past two decades, both surplus and deficit of water were of high quantity, resulting in few net increment after lake water balance. (6) The magnitude of temperature rise and precipitation reduction during 1992-2002 were larger compared with the period 2002-2013, and the quantity of water surplus and deficit of glacial lakes in spatial units of each size was greater compared with the 2002-2013 period. There is a positive correlation between water surplus and deficit of glacial lakes and the range of temperature rise and precipitation reduction.

DOI

[Chen Chen, Zheng Jianghua, Liu Yongqiang, et al.The response of glacial lakes in the Altay Mountains of China to climate change during 1992-2013. Geographical Research, 2015, 34(2): 270-284.]

[31]
杜加强, 赵晨曦, 贾尔恒·阿哈提, 等. 近30a新疆月NDVI动态变化及其驱动因子分析. 农业工程学报, 2016, 32(5): 172-181.不同生长阶段的植被对水热条件的需求、对气候变化的敏感性可能不同。监测不同月份植被动态变化及其对气候变化的响应，对于深入理解植被与气候的关系具有重要意义。基于MODIS NDVI数据集拓展的AVHRR GIMMS NDVI时间序列，该文研究了近30 a新疆生长季各月植被生长的动态变化，分析了气候变化和人类活动的可能影响。结果表明，已有研究指出的1982－2006年的植被生长显著增加（P＜0.05）在后续几个时段仍然持续，但5－10月区域平均NDVI增加量随时段长度的延长而显著减少（P＜0.05），除11月外，其他月份多存在1998年或1997年前后，NDVI由增加到减少的逆转现象。但在像元尺度，显著增加和显著减少的区域多随时段延长呈极显著增加趋势（P＜0.01），尤其是显著减少区域在各月中均快速增加，导致区域尺度NDVI增加趋势的放缓。各月份NDVI对气候变化的响应不同：生长季开始的3－6月和生长季结束的9－11月NDVI对气温、蒸散发等与热量有关的因子变化更敏感，而7－8月则与降水量、湿润指数等水分因子的相关性更强。3－5月农田NDVI的显著减少除气候因素外，种植结构和灌溉方式的改变也是重要原因。时段长度不同得出的结果有所差异，延长时段长度、注重变化过程分析是未来植被动态监测的重要研究内容。

[Du Jiaqiang, Zhao Chenxi, Jiaerheng Ahati, et al.Analysis on spatio-temporal trends and drivers in monthly NDVI during recent decades in Xinjiang, China based two datasets. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(5): 172-181.]

[32]
Mohammat A, Wang X, Xu X, et al. 1 Drought and spring cooling induced recent decrease in vegetation growth in Inner Asia. Agricultural & Forest Meteorology, 2013,78-179(5): 21-30.The response of vegetation growth to current climate change in Inner Asia (35–55°N, 45–120°E) was investigated by analyzing time series of the Normalized Difference Vegetation Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) from 1982 to 2009. We found that at the regional scale, the greening trend observed during the 1980s was stalled in the 1990s. Different seasons, however, show different changes and mechanisms. Among the three seasons (spring, summer and autumn), summer has the earliest turning point (from greening to non-greening) in the early 1990s, as a result of summertime droughts, as indicated by Palmer Drought Severity Index (PDSI). Consistent with the change in summer NDVI, summer PDSI and precipitation significantly increased in the 1980s, but strongly decreased since the early 1990s at the regional scale. The negative effect of summer drought is particularly significant over dry regions such as eastern Kazakhstan, Mongolia and Inner Mongolia. However, in high altitude or high latitude regions (>50°N), summer vegetation growth is more strongly correlated with summer temperature rather than with summer PDSI. In spring, changes in vegetation growth are closely linked with temperature changes rather than droughts. Both spring temperature and spring NDVI, for instance, increased until the late 1990s and then decreased. Statistical analyses also show that spring NDVI is significantly correlated with spring temperature at the regional scale ( P 02<020.05), implying that temperature is the dominant limiting factor for spring vegetation growth in most regions of Inner Asia except Turkmenistan and Uzbekistan, where spring PDSI shows significant positive correlation with spring NDVI. Further analyses of the response of vegetation to extreme high spring temperature in 1997 and extreme summer drought in 2001 exhibit a highly heterogeneous pattern.

DOI

[33]
张琪, 袁秀亮, 陈曦, 等. 1982-2012年中亚植被变化及其对气候变化的响应. 植物生态学报, 2016, 40(1): 13-23.lt;p>归一化植被指数(<em>NDVI</em>)能够反映植被生长状况, 被广泛应用于区域乃至全球的植被变化研究中。该文利用1982&ndash;2012年GIMMS-<em>NDVI</em>数据, 通过基于像元的线性趋势分析、偏相关分析, 基于场域的经验正交分解(EOF)、奇异值分解(SVD), 综合时间和空间两个维度上的信息, 研究了近31年来中亚植被的变化及其变化中的区域差异, 分析了植被对气候变化的响应关系。线性趋势分析发现, 34%的中亚植被<em>NDVI</em>显著增长(<em>p</em> &lt; 0.05), 山区植被<em>NDVI</em>的增长速率可达到每年0.004。偏相关分析表明, 63%的中亚植被受到降水的显著影响(<em>p</em> &lt; 0.05, 仅4%为负相关), 而32%的植被受到气温的显著影响(<em>p</em> &lt; 0.05, 仅9%为正相关)。EOF分析发现, 中亚植被<em>NDVI</em>的变化表现出较大的空间差异: 山区及东北部的植被<em>NDVI</em>变化主要分为3个阶段, 即先增长(1982&ndash;1994年)、后波动(1994&ndash;2002年)、然后继续增长(2002&ndash;2012年); 而西北部平原区的植被<em>NDVI</em>变化主要表现为两个阶段, 即先增长(1982&ndash;1994年)而后减少(1994&ndash;2012年)。SVD分析表明: 1982&ndash;2012年间中亚植被受到降水和气温的共同影响, 植被<em>NDVI</em>的空间变化特征与降水的空间变化特征较为一致, 但西北部和山区的植被<em>NDVI</em>对气温的响应存在差异。</p>

DOI

[Zhang Qi, Yuan Xiuliang, Chen Xi, et al.Vegetation change and its response to climate change in Central Asia from 1982 to 2012. Chinese Journal of Plant Ecology, 2016, 40(1): 13-23.]

[34]
郑明国, 孙莉英. 气候变化和人类活动影响下澧水流域径流及其不同组分的变化. 地理研究, 2014, 33(2): 237-250.目前径流变化相关研究较少涉及径流的不同组分。利用湖南省澧水流域4个水文站点长序列观测资料,不仅分析了2007-2011年相对于1985年以前径流总量及其历时曲线的变化,也分析了地表径流和基流及其历时曲线的变化。与1985年以前比,流域年降雨量保持不变,最显著的变化为森林覆盖率的增加和大量水库的修建。这些人类活动没有造成年径流总量、年基流量和年地表径流量的显著变化,但在日时间尺度上对径流过程产生了重要影响。地表径流和地下径流对人类活动存在差异性响应,2007年以后地表径流在洪峰期流量变小而其他时段变大,而地下径流汇水受人类活动影响较小,基流流量除枯水期外与1985年以前基本一致。本文所揭示的规律可能在中国南方具有一定的代表性。

DOI

[Zheng Mingguo, Sun Liying.Recent change of runoff and its components of baseflow and surface runoff in response to climate change and human activities for the Lishui watershed of southern China. Geographical Research, 2014, 33(2): 237-250.]

[35]
Bekchanov M, Lamers J P A. Economic costs of reduced irrigation water availability in Uzbekistan (Central Asia). Regional Environmental Change, 2016, 16: 2369-2387.Reduced river runoff and expected upstream infrastructural developments are both potential threats to irrigation water availability for the downstream countries in Central Asia. Although it has been recurrently mentioned that a reduction in water supply will hamper irrigation in the downstream countries, the magnitude of associated economic losses, economy-wide repercussions on employment rates, and degradation of irrigated lands has not been quantified as yet. A computable general equilibrium model is used to assess the economy-wide consequences of a reduced water supply in Uzbekistan—a country that encompasses more than half of the entire irrigated croplands in Central Asia. Modeling findings showed that a 10–20 % reduction in water supply, as expected in the near future, may reduce the areas to be irrigated by 241,000–374,000 hectares and may cause unemployment to a population of 712–868,000, resulting in a loss for the national income of 3.6–4.3 %. A series of technical, financial, and institutional measures, implementable at all levels starting from the farm to the basin scale, are discussed for reducing the expected water risks. The prospects of improving the basin-wide water management governance, increasing water and energy use efficiency, and establishing the necessary legal and institutional frameworks for enhancing the introduction of needed technological and socioeconomic change are argued as options for gaining more regional water security and equity.

DOI

[36]
Bo L, Orolbaev E, Steklov Y.Water and energy crisis in Central Asia. China and Eurasia Forum Quarterly, 2008, 6(3): 9-20.ABSTRACT A Cold Winter in Central Asia After a very cold winter in Central Asia in 2007-2008 followed by a dry spring and summer, the water and energy situation in the region is critical and political relations strained. The situation is so serious that it was addressed to at an extraordinary meeting of Central Asian Heads of State held in Bishkek early in October 2008. The extensive use of hydropower in Kyrgyzstan during the winter resulted in a very low level of water in the major Toktogul Reservoir on the Naryn, a principal tributary of the Syr Darya. As a consequence, the downstream countries Uzbekistan and Kazakhstan have not received as much water from the Syr Darya for irrigation in the spring and summer as they need. The winter also had severe consequences in energy-poor Tajikistan, with significant losses of lives and livestock. Basic services such as heating and water supply were not available for days even in the capital, Dushanbe. This was the coldest winter in several decades, and demonstrated the need to develop reliable energy supplies. Further significant power shortages are expected in Kyrgyzstan and Tajikistan over the forthcoming winter.

[37]
Eshchanov B R, Stultjes M G P, Salaev S K,et al. Rogun dam-path to energy independence or security threat?. Sustainability, 2011, 3(9): 1573-1592.The revitalization of the Rogun hydropower station project and launch of an Initial Public Offering has led the water-energy disputes between Tajikistan and Uzbekistan to a new stage. While two riparian states advocate their positions from their own perspective, it gives the impression of being a “prisoners’ dilemma” case from a regional cooperation point. This paper aims to review the decision of project revitalization from the unconventional security perspective, focusing mainly on its impact on Tajikistan. The scope will be limited to economic, energy, social and political security. The paper attempts to reveal the existing unconventional security threats and suggest possible solutions for the arising problems.

DOI

[38]
Jalilov S M, Desutter T M, Leitch J A.Impact of Rogun Dam on downstream Uzbekistan Agriculture. Lap Lambert Academic Publishing, 2011.

[39]
李超凡, 罗格平, 李均力, 等. 近20a中亚净初级生产力与实际蒸散发特征分析. 干旱区地理, 2012, 35(6): 919-927.

[Li Chaofan, Luo Geping, Li Junli, et al.Net primary productivity and actual evapotranspiration of Central Asia in recent 20 year. Arid Land Geography, 2012, 35(6): 919-927.]

[40]
Beurs K M D, Henebry G M, Owsley B C, et al. Using multiple remote sensing perspectives to identify and attribute land surface dynamics in Central Asia 2001-2013. Remote Sensing of Environment, 2015, 170: 48-61.

[41]
Propastin P A.Inter-annual changes in vegetation activities and their relationship to temperature and precipitation in Central Asia from 1982 to 2003. Journal of Environmental Informatics, 2008, 12(2): 75-87.

[42]
Lioubimtseva E, Henebry G M.Climate and environmental change in arid Central Asia: Impacts, vulnerability, and adaptations. Journal of Arid Environments, 2009, 73(11): 963-977.

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De Beurs K M, Henebry G M. Northern annular mode effects on the land surface phenologies of Northern Eurasia. Journal of Climate, 2008, 21(17): 4257-4279.

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Beurs K M D, Henebry G M, Derksen C, et al. A land surface phenology assessment of the northern polar regions using MODIS reflectance time series. Canadian Journal of Remote Sensing, 2014, 36(S1): 87-110.

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Camurri A, Volpe G.Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan. Global & Planetary Change, 2013, 110(4): 88-98.

[47]
Wessels K J, Bergh F V D, Scholes R J,.Limits to detectability of land degradation by trend analysis of vegetation index data. Remote Sensing of Environment, 2012, 125(1): 10-22.

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