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亚洲中部内陆地区陆地水储量时空变化研究
No full text亚洲中部内陆地区水资源使用存在诸多问题，气候变化对全球水资源的影响逐渐加剧，使得该地区水资源纷争进一步激化。利用 GRACE 重力卫星对亚洲中部内陆区陆地水储量进行研究突破了传统方法的时空局限性，使监测大范围地区陆地水储量的变化成为可能。本研究采用 2002 年 4 月至 2014 年 12 月 GRACE（Gravity Research and ClimateExperiment）时变重力场反演的陆地水储量数据，陆地同化模型系统 GLDAS（GlobalLand Data Assimilation System）土壤水分含量数据，热带降水测量卫星 TRMM（Tropical Rainfall Measuring Mission）降水数据，全球降水气候中心 GPCC（GlobalPrecipitation Climatology Centre）降水再分析数据，全球的数字高程模型 GOTOPO30DEM 数据，GIMMS（Global Inventory Modelling and Mapping Studies）NDVI 月数据，GlobCover2009 全球陆地覆盖数据，以及相应地区的河网分布矢量图。通过趋势分析、分区统计分析、空间上的相关性分析、EOF（Empirical Orthogonal Function）经验正交函数分析以及定性分析，研究亚洲中部内陆区土壤水分含量、降水量、陆地水储量的时空变化，分析比较研究区内土壤水分含量和降水量与陆地水储量的相关性，分析亚洲中部山区陆地水储量的时空变化，总结影响亚洲中部内陆区陆地水储量的自然因素以及人为因素及其影响机理，比较各个山区降水对陆地水储量的影响程度。本研究的主要结论如下：1、亚洲中部内陆区土壤水分含量年际变化：新疆在山区增加，在盆地减少；中亚五国在沙漠区增加，在研究区中南部地区高速率减少，在 2008-2009 年和 2011 年存在两个极值点。年内变化除新疆南疆个别地区增加，其余地区减少，中亚五国呈现增加-减少-增加的过程，极值点在 4、8 月，新疆呈现增加-减少的单峰趋势最大值点在 6 月。2、亚洲中部内陆区降水量年际变化：在山区及哈萨克斯坦北部和塔吉克斯坦东部增加，在研究区中南部地区高速率减少，在 2008 年降至最低。年内变化在研究区中南部地区高速率减少，中亚五国呈现增加-减少-增加的过程，极值点在 4、9 和 11月，新疆呈现增加-减少的单峰趋势最大值点在 7 月。3、亚洲中部内陆区陆地水储量年际变化：新疆昆仑山山区增加，准噶尔盆地减少；中亚五国呈现自东向西减少速率逐渐增加，且均存在 2005、2008、2010 年三个极值点。年内在新疆昆仑山东段增加，向西北方增加速率逐渐递减，在哈萨克斯坦中部向西北方向和南部地区陆地水储量减少速率增大，中亚五国和新疆呈现增加-减少-增加的过程，中亚五国极值点在 3、10 月，新疆极值点在 7、10 月。4、年际变化土壤水分含量与降水量的空间分布一致，陆地水储量与二者一致地区集中在新疆昆仑山东段均呈现较高速率增加。三者年际变化均呈现减少的趋势，在2008 年降至最低；年内变化土壤水分含量、降水量以及陆地水储量空间分布均在研究区中南部地区呈现较高速率的下降趋势，中亚五国年内变化呈现增加-减少-增加的过程，极值点在 3-4 月和 9-10 月，新疆呈现增加-减少的过程极大值点在 6-7 月。5、土壤水分含量对陆地水储量的影响相对于降水的影响范围更大，两者在研究区中南部地区均与陆地水储量呈现较强的相关性，且土壤水分含量相关性更大，天山以南地区陆地水储量受到降水的影响大于土壤水分含量。6、亚洲中部内陆区地势较高的地区受人类活动的影响较小，以自然影响因素为主。河网分布稠密地区陆地水储量变化由于径流补给等作用，对相应地区陆地水储量减少有一定缓冲作用，但随着冰雪量的减少导致径流量下降最终该地区陆地水储量减少速率将会大幅度增加。亚洲中部内陆区耕地主要沿河流在山前平原分布较多，人类活动对陆地水储量的影响主要集中在开垦耕地过程中引水灌溉，加剧水资源蒸散发，同时部分地区抽取地下水用于灌溉以及生活，使陆地水储量的减少趋势更加明显。但是总体上，影响该地区陆地水储量的主要因素仍是自然因素。7、阿尔泰山区陆地水储量变化最剧烈，变化幅度随时间呈现增加的趋势，降水对阿尔泰山区陆地水储量的变化影响较小；西天山和东天山山区，喀喇昆仑山与昆仑山山区由于地理位置较为接近，陆地水储量变化趋势相似。东天山比西天山陆地水储量变化受到降水量变化的影响更大，后两个地区陆地水储量受降水的影响均较小。祁连山山区陆地水储量变化是唯一呈现明显的增加趋势的研究区，受到降水强度的影响较大
基于遥感和景观指标的 NYUNGWE-KIBIRA 公园森林覆盖变化和破碎度监测
No full text本文以跨越卢旺达和布隆迪的自然保护区的 Nyungwe-Kibira 公园为研究区域，评估研究区 1986 年至 2015 年间森林覆盖率变化及森林退化情况，分析 Nyungwe-Kibira公园保护区和周边 5 公里对照缓冲区域变化过程的相似性和差异性，定量描述人类活动对其变化的影响。本研究以 30 m 空间分辨率的 Landsat TM，ETM +和 8OLI 数据作为主要数据源，借助地理信息系统（GIS）进行土地覆盖制图与变化检测，并使用 FRAGSTATS 软件计算景观指数，分析森林覆盖和景观格局的分类与变化情况。研究结果显示，1986 年至 2015 年期间，在公园内考虑的 5 种土地覆被类型中，高覆盖率的林地占主导，面积为整个公园区域面积的 70％以上。而在对照缓冲区内，开垦耕地和开放土地更占主导地位，面积占 90％以上。变化检测显示，1986~2015 年间，在 Nyungwe-Kibira 公园区域内，森林每年大约消失了 0.27％（4.97 km2），而年再生率仅为 0.07％（1.22 km2），表明森林的消失速率远大于其恢复速率。在景观类型水平的四个景观指数研究结果表明公园内的林地分散分布，对照缓冲区内的破碎度很高。这些统计结果与木材能源消耗赤字均表明非法砍伐带来的森林减少和森林退化给公园的生态环境带来了很大的压力，这种退化发展趋势对 Nyungwe-Kibira 公园的可持续性形成了极大的威胁。研究结果可为公园的决策者和管理者提供参考，为其采取迅速有效的措施，减少森林的消失，遏制森林的退化，避免生态系统的退化，改善和维持生态系统的自我平衡能力提供科学依据。建议的措施包括：减少公园边界的社区依赖，在缓冲区再造林，通过在农田边界和可用的非森林地区应用农林业等。根据分类结果和映射结果的准确性，本文的结果可能具有一些误差和可改进的地方，为了进一步提高分析的准确性，可采用更高分辨率的遥感数据和更加详细的地面勘测弥补这方面的缺陷，以提高研究精度。然而，为保障森林管理的适宜性，有必要开展综合和常规的的评估工作。最后，建议至少每五年对自然保护区森林的时空格局进行一次分析，以此明晰森林自然再生现象等具体特征，因为在森林砍伐区，在没有其他土地利用类型存在的情况下，森林的这些特征通常会受到热带气候的影响
氮肥管理措施对新疆膜下滴灌棉田温室气体排放的影响
No full textAs the dominant cultivation system for cotton production in arid northwesternChina, the plastic mulching with drip irrigation system has many advantages such aswater conservation, soil warming and improving soil physical characteristics. Exploring "4R" fertilizer nitrogen (N) stewardship to improve fertilizer N useefficiency and reduce soil greenhouse gas emissions under such cultivation system isan important and urgent research topic in the area of arid land resources andenvironment. In this study, a field experiment was conducted at a cotton field underplastic mulching and drip irrigation at the Xinjiang National Grey Desert Soil Stationin 2015 and 2016. Static chamber-gas chromatography method was used to monitornitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4) emissions underdifferent N fertilizer management practices over the growing season. Meteorologicaldata and soil environmental factors were collected and used to identify the drivingfactors of soil greenhouse gas emissions from cotton fields under such a cultivationsystem. The effects of N fertilizer management practice on plant biomass, nitrogenuptake, yield and fiber quality of cotton were also evaluated. The main results were asfollow:(1) Emission peaks of soil N2O mainly occurred within one month after theapplication of basal fertilizer. Applications of in-season fertilizers with irrigation(fertigation) for urea (U) and urea with urease inhibitor and nitrification inhibitor (UI) treatments, however, did not induce N2O emission peaks. The cumulative N2Oemissions was greatest for polymer-coated urea (ESN) treatment (473 g N2O-N hm-2), which was 1.4~1.8 times greater than those of other treatments. N2O emission factorsof fertilizer treatments were only 0.008~0.089% in this study, which wereconsiderably lower than those reported in other studies. Cumulative emissions of CO2and CH4, global warming potential and greenhouse gas intensity differed betweenyears but were not significantly affected by N treatments. (2) The low soil water-filled pore space (WFPS) and significantly positivecorrelation between cumulative N2O emission and nitrate intensity (R2=0.299，P<0.01)indicated that nitrification was the dominant process for N2O production in cottonfield under plastic mulching and drip irrigation in the arid region. The significantcorrelations of soil CO2 emission with soil temperature (R=0.788, P<0.01) or soilWFPS (R=0.378, P<0.01) implied that the difference of soil CO2 emissions betweenyears were possibly caused by the variations of soil temperature and moisture. (3) UI did not significantly affect the plant biomass, N uptake and N allocationsinto different parts of cotton compared to U. In 2015, applying ESN increased theplant biomass due to the high precipitation and air temperature. However, ESN didnot significantly affect N uptake and N allocations into different parts of cotton. Theplant biomass, N uptake, N allocation rates of cotton stalk and seed variedconsiderably between years. The plant biomass and N uptake were 1.4~2.3 and1.4~2.0 times greater in 2016 than in 2015, respectively. N allocation rate into cottonstalk was 49.2% higher in 2016 than in 2015, while N allocation rate into cotton seedwas 19.4% lower in 2016 than in 2015. (4) Seed cotton yield, lint cotton yield, lint percentage and fiber quality were notaffected by fertilizer N treatments in this study. By contrast, seed cotton yield, lintpercentage and most of the fiber quality indexes including fiber upper half meanlength, uniformity, strength, short fiber ratio, micronaire and spinning consistencyindex differed between years. For example, short fiber ratio and micronaire weregreater in 2015 than in 2016, while the other quality indexes were greater in 2016 than in 2015
柽柳灌丛沙堆风沙动力学过程的风洞实验
No full textThe study took the Tamarix nebkhas and interdune plants, which are widelydistributed in oasis-desert ecotone at the southern rim of the Taklimakan desert, as theresearch prototype to make five sets of nebkhas model with background vegetationcoverage of 0%, 4%, 10%, 16% and 26% respectively to conduct the simulationexperiment of airflow patterns and erosion and accumulation change rule in the windtunnel. The wind flow field, surface alteration, surface aerodynamics, sedimenttransport rate and sand flow structure of Tamarix nebkhas had been systematicallystudied so as to further understand land degradation causes and processes of oasis-deserttransition zone, and provide theoretical basis for oasis security and nebkhasconservation. The results showed that:(1) The three-dimensional airflow structure of Tamarix ramosissima nebkhas canbe divided into six regions: the deceleration zone before nebkhas, the accelerationregion of nebkhas windward, the high speed zone on both sides of nebkhas, the strongvortex area on leeward side of nebkhas, the recovery zone after nebkhas and the mixedacceleration zone above nebkhas. The influence region of nebkhas on airflow patternswas -10H~14H in horizontal direction and width of side influence zone was less than3/4 of nebkhas width. In vertical direction, the airflow patterns were significantlyaffected by nebkhas height, the maximum influence height was less than 2H. Thebackground vegetation coverage played an important role in affecting the airflowpatterns. With increase of background vegetation coverage, the deceleration zone atfront of nebkhas and recovery zone behind nebkhas were expanded, meanwhile thestrong vortex zone on lee side and high speed zone at both sides of nebkhas shrinked.The wind velocity was significantly reduced at the layer where the backgroundvegetation existed. The airflow acceleration rate at each region of nebkhas showed anearly exponential decay with background vegetation coverage. When the coverage ismore than 16% the acceleration rate tended to be steady.(2) With increase of background vegetation coverage from 0%, to 4%, to 10% , to16% and to 26%, the threshold wind velocity of sand-driving on interdune was 4.4 m·s-1, 5.4 m·s-1, 5.8 m·s-16.2 m·s-1and 7.2 m·s-1respectively, while on nebkhas they were3.2 m / s, 4.4 m·s-1, 5.0 m·s-1, 5.2 m·s-1, 5.4 m·s-1respectively. The threshold wind speedat interdune is about 1 m·s-1higher than that on nebkhas surface, which suggest thatnebkhas surface is more prone to wind erosion than the interdune. Tamarix ramosissimanebkhas and interdune can be divided into six regions. They are named theaccumulation area before nebkhas, the erosion area on windward slope of nebkhas, theerosion area on both sides of the nebkhas, the vortex flow sediment area on leewardside of nebkhas, the wake accumulation area after nebkhas and the no affected area,respectively. Both wind velocity and background vegetation coverage played animportant role in affecting the erosion distribution. With increase of wind velocity,the accumulation area before nebkhas and the wake accumulation area after nebkhasare narrowed, while the erosion area on both sides of the nebkhas are expandedsignificantly. The erosion area ratio, erosion intensity and wind erosion rate at nebkhasand interdune decreased exponentially with increase of background vegetationcoverage. When the vegetation coverage is low the influence of wind velocity on theerosion intensity is obvious. The nebkhas on the bare sand can aggravate wind erosion,but nebkhas can block sand flow even sparse vegetation existing on the interdune.(3) The surface aerodynamic parameters were significantly correlated with thebackground vegetation coverage. With the increase of vegetation coverage, theaerodynamic roughness length (z0) and the drag coefficient (cd) increased exponentially,the friction wind speed (u*) increased logarithmically, while the sediment transport fluxdecreases exponentially. There was a significant correlation between surfaceaerodynamic parameters and the sediment transport flux. The sediment transport fluxdecreased exponentially with the increasing of roughness length (z0), friction windspeed (u*) and drag coefficient (cd).(4) Based on the analysis of the correlation of the acceleration rate, the winderosion rate, the sediment transport flux and the background vegetation coverage, it was found that there was a good correlation between the acceleration and erosion intensityof nebkhas. The total wind erosion rate and sediment transport flux on Tamarix shruband its interdune showed exponentially law with background vegetation coverage, thechange was not obvious when the vegetation coverage was>16%. It is inferred that themaintenance of no less than 16% of the background vegetation cover should be theprerequisite for scientific conservation of nebkhas in oasis-desert ecotone
新疆天山中段南坡种子植物多样性垂直分布格局研究
No full text植物多样性垂直分布格局及其维持机制的研究可以有效揭示植物物种多样性分布特征及其影响环境因子，为区域物种资源的保护及可持续开发利用提供理论依据。新疆天山南坡是帕米尔-天山山地生物地理省物种较为丰富的生境区域，也是我国具有重要意义的生物资源和生物多样性关键地区之一。目前该区主要集中在局部区域植物区系特征及植物群落物种多样性的研究上，对于大尺度的植物区系特征、性质及沿海拔梯度格局研究及大区域范围内的植物群落物种多样性海拔梯度格局及其影响环境因子则缺乏系统地研究。为了更好地了解该区植物多样性分布格局及其影响环境因子，本研究以新疆天山中段南坡为研究区，以种子植物为研究对象，利用研究区大尺度的物种数据及群落尺度的物种样方调查资料，利用地统计学和数量生态学的理论与方法，从植物区系组成、特征及性质、植物区系海拔梯度格局、植物群落物种多样性分布格局及其影响环境因子等方面进行了系统、深入地研究。主要研究结果如下： 1. 新疆天山中段南坡种子植物种类相对丰富，优势科现象明显，大种属和寡种属占据优势。根据大尺度区域物种数据统计，共有种子植物 87 科、439 属，1454 种，分别占新疆种子植物科、属、种总数的 75.65%、59.89%和 40.57%；科内大科优势现象明显，物种丰富性趋向于集中在菊科（Composifa，188 种）、禾本科（Graminae，184 种）、豆科（Leguminosae，135 种）等 15 个大科内，所含种数占区域总种数的75.58%。这是植物在严酷的荒漠环境中长期进化适应的结果。属的组成中以大种属（≥10 种)和寡种属(2～5 种)为主，其所含种数分别占总种数的 32.68%和 34.68%。生活型组成中，木本植物种类相对比较匮乏，乔木 12 种，灌木 168 种，两者合占该区总种数的 12.39%，草本植物有 1262 种，占该区总种数的 86.85%，区系成分中占绝对优势。 2.该区新疆特有种及珍稀濒危保护植物较多。有新疆特有种 55 种，隶属 20 科43 属，占新疆特有种、所隶属科、属的 20.91%、57.14%和 37.07%；有各类珍稀濒危野生植物 55 种，其中，IUCN 物种红色名录（2010）收录 9 种；《濒危野生动植物种国际贸易公约》CITES（2010）收录 10 种；新疆维吾尔自治区重点保护植物 37 种，其中，I 级保护植物有 25 种，II 级保护植物有 12 种；保留了第四纪冰期之前的残遗植物物种 51 种。该区域植物区系具有既古老又年青的特征。科、属的植物区系地理成分均以温带地理成分为主。温带分布及其变型科有 26科，占非世界分布总科数的 60.46%；属的温带地理成分在区系中占明显优势, 占到总属数的 62.67%。这与新疆所处欧亚大陆腹地的干旱气候环境是相适应的。3.大区域尺度内，科、属及种的物种丰富度均表现出随着海拔升高，丰富度先增加、后减少的单峰分布格局，峰值出现在中低海拔 1900-2000m 处，说明此海拔段是天山中段南坡地区资源组合（水、热）的最佳地段。不同生活型植物沿海拔梯度的变化格局不同。乔木、一年生草本、藤本及寄生植物是随着海拔梯度的升高呈现降低的趋势。灌木、多年生草本及二年生草本植物是呈现单峰变化格局，但灌木和二年生草本的峰值低于多年生草本植物的峰值。灌木的峰值区域在海拔 1400-2000m 处，多年生草本的峰值在海拔 1900-2500m 处，二年生草本的峰值在海拔 1500-2100 m 处。水分与能量是限制物种丰富度分布的主要环境影响因子。 4.世界成分比重沿海拔梯度的升高呈单峰分布结构；温带区系成分所占比重在海拔梯度上的分布呈缓慢上升趋势，这与温带区系植物耐低温，适合生长在高海拔地区的生态适应性是相吻合的；古地中海地理成分 Tdzh比重在海拔梯度上呈现双峰变化格局；热带区系成分 Trd 沿海拔梯度分布虽呈波浪状分布，但总的趋势呈现随海拔的升高而逐渐下降的趋势；东亚地理成分 Tdy 比重沿海拔梯度的分布呈双峰分布格局，高峰区间分别是 2400-2500m 和 3300-3400m；这些分布格局均与当地干旱气候条件及海拔带上的热量和水分条件的变化相适应的。该区温带区系成分占绝对的主导地位，所以该区没有区系平衡点。 5.经 TWINSPAN 数量分类，126 个群落样地被划分成合头草+琵琶柴+霸王-戈壁针茅+盐生草群落、天山猪毛菜+骆驼刺+裸果木群落、准噶尔铁线莲-纤绠蒿+狗尾草+黄花苜蓿群落、白皮锦鸡儿-草原苔草+针茅群落、线叶嵩草+棱子芹群落、线叶嵩草+委陵菜+大红红景天群落、雪岭云杉-刺叶锦鸡儿-苔草+早熟禾群落等 25 个群落类型。山地荒漠带和山地荒漠草原带分布的群落类型多是以荒漠灌木、半灌木为主组成的群落类型；高山高寒草地与高山高寒草甸植被带中的群落类型主要是以喜湿、耐寒、喜肥的以禾本科、莎草科植物为主的优势群体。群落类型分布是与海拔梯度上气候与土壤环境因子的变化相适应的。不同生活型物种多样性指数在不同植被类型分布中表现不同。灌木物种的四种多样性指数值均较草本物种的低，群落总体的物种多样性受草本物种影响较大，其变化趋势与其大致相同。不同生活型物种多样性分布格局与环境因子如水分、热量及土壤营养成分的变化是相适应的。6.在RDA排序分析的基础上，运用GAM模型模拟了不同生活型物种多样性指数沿海拔梯度的分布格局。不同生活型物种的海拔梯度格局是不同的。灌木物种的四种多样性指数中，Patrick丰富度指数Rs、Pielou 均匀度指数Es、Shannon-wiener 多样性指数Hs均表现出单调下降趋势，而Simpson多样性指数Ds则呈现单峰曲线格局，峰值出现在海拔2200~2300m处。草本物种的四种多样性指数中，Patrick丰富度指数Rh呈现单峰曲线结构，其余三种多样性指数Eh、Hh和Dh均呈现单调上升趋势。植物群落总体物种多样性指数中，Patrick丰富度指数Rt呈现单峰分布结构，即随着海拔的升高呈现先升高再降低的趋势，峰值出现在中高海拔带3100~3200m处；Pielou均匀度指数Et、Shannon-Wiener多样性指数Ht呈现随着海拔升高先降低再升高的U型曲线结构；Simpson多样性指数Dt则呈现单调上升趋势。草本层植物生长受小环境基质（土壤有机质、土壤含水量、全氮、有效氮、有效磷）即小尺度的资源可利用性的影响较大，灌木的生长受海拔梯度上水热变化的影响较大。 7. 通过物种多样性指数与土壤环境因子及海拔因子间的RDA排序分析，影响植物群落物种多样性分布格局的主要环境因子是海拔Elev、土壤水SW、有机质SOM、全氮TN、全磷TP、有效氮AN和土壤总盐TS。不同生活型的物种对环境因子的变化响应不同。8. 由于处在不同的气候及地质环境背景下，影响不同区域群落物种多样性的环境因子不同。影响和静巴仑台区和库车区植物群落物种多样性分布格局的主要环境因子是海拔、土壤水、全氮、有效氮、有机质和全盐；影响拜城区的主要环境因子是海拔、土壤水、有机质、全氮、有效氮；影响温宿区的主要环境因子是海拔、土壤水、有机质、全氮、全磷、有效氮、有效磷和全盐。不同生活型植物由于处在不同的气候及地质环境背景下，形成对不同环境因子适应的选择性响应
和田地区农业碳效应及农业碳汇补偿机制研究
No full text温室气体排放引起的以全球变暖为主要特征的气候变化已经极大的影响了世界人民的生产、生活，并且已经渐变为国际社会普遍关注的焦点。温室气体主要来自第二产业和第三产业，但快速发展的农业增加了温室气体的排放量，加速了气候变暖。虽然农业是碳源，但是农业能够固碳，具有强大的碳汇生态功能，碳减排潜力巨大。基于此，本文选择经济落后环境脆弱而且以农业经济为主导的和田地区为研究区，探讨农业碳效应，并尝试建立农业碳汇补偿机制，以期促进扶贫开发，增加农民收入，推动农业可持续发展，同时也为应对全球气候变化做出应有的贡献。本文主要研究内容与结论如下：（1）和田地区农业碳效应整体表现为正效应。在农业碳排放方面，本文从农业碳排放强度对和田地区、全疆、全国做了对比，结果显示中国的农业碳排放强度为 507.00 kg/万元 AGDP，新疆的农业碳排放强度为699.22 kg/万元 AGDP，和田地区农业碳排放强度为 1137.97kg/万元 AGDP，和田地区农业为高碳排农业，农业碳减排任务艰巨；本文运用脱钩理论探索了和田地区农业碳排放与农业经济增长之间的关系，从农业碳排放与农业经济增长的脱钩指数看，1999-2014 年经历了“脱钩—挂钩—脱钩”三种状态过程，通过对和田地区、全疆、全国的对比表明和田地区是一个在脱钩阶段上严重滞后于全国与全疆的地区；从农业碳排放驱动机理来看，农业劳动力、农业生产效率和农业经济是和田地区农业碳排放增加的主要因素，而农业结构因素在很大程度上抑制了和田地区农业碳排放。在农业碳汇方面，本文从碳汇水平对和田地区与全国进行了对比，全国的平均碳汇水平约为 4.14，而和田地区为 6.78，高出全国平均水平 63.60%，表明和田地区农业为高碳汇农业；农业碳汇的影响因素有农业有机肥、农作物产量、种植业生产结构、农业产业结构、土地利用方式和耕作制度等，影响和田地区农业碳汇的主要因素是农业产业结构，特别是特色林果业的发展，长期均衡分析表明特色林果业面积增加 1%，农业碳汇总量增加 0.4556%；本文采用净碳汇量乘以吨碳价格法来估算农业碳汇的经济效益，最终计算出 2014 年和田地区农业碳汇效益为 7.25 亿元，每亩耕地碳汇效益为 261.34 元。综合来看，一方面和田地区由于农业生产方式、技术落后，管理粗放，农业属于高碳排农业；另一方面，由于特色林果业的发展，农业碳汇水平高，农业碳汇生态功能明显，碳汇经济效益高，属于高碳汇农业。和田地区农业碳效应整体表现为正效应，减排増汇潜力巨大。（2）构建了和田地区农业净碳汇补偿机制和低碳模式下农业碳汇补偿机制。本文以和田地区农业碳效应整体表现为正效应为前提构建了包括补偿目标、补偿原则、利益相关者、补偿标准、补偿方式、补偿资源来源等六个方面的农业净碳汇补偿机制；基于和田地区农业属于高碳排农业，本文构建了包括化学品减量化、低碳耕作、秸秆还田、低碳养殖等低碳模式下农业碳汇补偿机制，制定了各低碳模式下的补偿标准，并对低碳模式下的政府补偿、市场补偿做了详细的介绍，特别的还对农业温室气体减排自愿交易案例进行了分析，表明开展农业温室气体自愿减排交易项目具有可行性，以期为和田地区开展低碳模式下的农业温室气体减排项目提供借鉴。（3）提出了推进和田地区农业减源増汇的对策建议。根据和田地区农业碳效应分析发现的问题，提出了针对和田地区人口、经济、科技、农业结构等八方面的农业碳减排的政策建议；同时，提出了包括法律、政策、保障体系等三个方面完善和田地区农业碳汇补偿机制的建议，其实这也是保障和田地区农业碳减排的政策建议顺利实施的建议
荒漠城市生态系统对未来气候变化响应的模拟研究与可持续评估
No full text作为人类活动的热点区域，城市突出反映了人类对自然环境的改造和控制；城市区域内大规模的物质生产、消费活动正在（或已经）改变陆地表面覆被状况、生物
西北干旱区植被净初级生产力的遥感估算及时空格局研究
No full textOver the past half-century, almost all parts of the world have experienced warming process, resulting in a series of ecological and environmental problems. Different forms of climate change have different effects on the carbon cycle of terrestrial ecosystems. As an important part of the carbon cycle, vegetation has a profound response to climate change. The vegetation fixed CO2 and synthesized the organic material through photosynthesis. Through respiration and other disturbances in different time scales, the carbon can be returned to the atmosphere. Thus, the carbon cycle is a dynamic equilibrium process, and the whole process must have the participation of plants. Net primary productivity (NPP) represents the carbon sequestration capacity of vegetation. The NPP is an integral part of understanding the carbon cycle process, an important ecological index to monitor the changes of natural resources and ecological environment. The ecological environment in arid area of Northwest China is fragile and sensitive, and the smaller climate fluctuation may cause the change of ecological environment, so the arid region of Northwest China has been widely concerned by scholars Arid continental climate, landforms of mountains and basins and the special characteristics of the soil and vegetation have made significant different vegetation types and ecosystems between these areas with other regions in our country. Climate change has further aggravated the unbalanced distribution of the water resources in the study area. The contradiction of water resources is more prominent, and the vulnerability of ecosystem is more serious. Therefore, it has a profound and far reaching significance for select vegetation NPP as a representative index to monitor and evaluate the ecological environment in this area. Based on MODIS NDVI data and Meteorological station data from 2000-2014 in arid region of Northwest China, this paper improved CASA model with land cover type, and then estimated and quantitative analyzed the changes of NPP in different vegetation types by using the ARCGIS, MATLAB, ENVI and other software. Under the background of climate change, this paper trying to answer some question of what are the distribution of vegetation, the trend of the vegetation, the difference of the biomass in different land cover types, the difference of the effects of climate change on vegetation NPP and the effects of different land use / land cover on vegetation NPP. Results show: 1. In this paper, the remote sensing statistical models, including multi-stepwise regression model, principal components regression model, partial least-squares regression model and ridge regression model, and the CASA model were constructed. The vegetation NPP was estimated by these models. Through the comparison and analysis of the two kinds of estimation models, it is found that the simulation results of the CASA model are closer to the measured data and the simulation results of the CASA model are better than the remote sensing statistical model when the model parameters are easily obtained. 2. The mean annual vegetation NPP of this area is 191.63gC/m2 , There is an obvious regional difference in NPP distribution in arid area in Northwest China, basically high in the northwest and southeast and low in the center. In the Altai Mountains, Ili River Valley, Tianshan Mountains, west of Kunlun Mountains and some areas in Hexi Corridor, the biomass is high; in the Central of desert, the vegetation NPP is very low, generally less than 30gC/m2 . 3. There is increasing trend in annual NPP with an annual rate at 2.98 gC/m2 (p<0.01).The trend is relatively stable from 2000 to 2009 with the annual rate at 2.30 g C m-2 . After 2009, the annual NPP increased rapidly with the rate at 6.60 g C m-2 a -1 . The trend differs for vegetation types with largest increase in cropland(6.34gC/m2·a), followed by shrub(4.40 gC/m2·a), and least increase in woodland(0.53 gC/m2·a). In the seasonal changes, the vegetation NPP is high in July, and then shows s downward trend. By calculation, the NPP from June to August accounted for 64.9% of the whole growth season in the acid region of Northwest China from 2000 to 2014. 4. On the spatial distribution of NPP in the study area, overall vegetation NPP has showed a tendency to improve. The vegetation NPP in 82.84% areas was appeared an increased tendency, 3.05% areas remained relatively stable, and 14.11% areas appeared slightly decreased since 2000. Vegetation NPP has a significant correlation with precipitation (r=0.538) and not so significant correlation with temperature (r=0.394), indicating vegetation NPP is more highly correlated with precipitation than temperature, and the correlation coefficient differs for different vegetation types. 5. By analyzing the characteristics of land use/land cover and the effects between the land use/land cover with the vegetation NPP, The change of land use / land cover in the arid area of Northwest China was characterized by the decrease of unused land area and the increase of forest land, cultivated land, shrub and grassland from 2000 to 2014. The trend differs for vegetation types with largest increase in cropland (6.34gC/m2·a), followed by shrub (4.40 g C/m2·a), and least increase in woodland (0.53 gC/m2·a). The total amount of vegetation NPP increased from 2.89 × 105G g C / a to 3.26 × 105G g C /a from 2000 to 2014. The increase was 3.69 × 104 G g C / a and the rate of change was 13%
极端干旱区胡杨根系吸水模型的构建
No full textRoots(mainly 0.05). In the vertical direction, the maximum root length density and fine root densely distribution area were more shallow than that of the river.3. The soil water content is the most important factor determining the distribution of fine roots in the lower reaches of Tarim River, the absence of fine roots in the soil surface is due to the coupling effect of low water content and high salt content. Because of the limitation of soil water and salt, the soil organic matter, available nitrogen and PH have little effect on the distribution of fine roots.4. The compensation water uptake process is weak in model simulation. After removing the compensation term, we adjusted the models at both sites and established the root water uptake models of Populus euphratica .That is
干旱区绿洲农田防护林景观格局及其对作物产量的影响
No full textThe windbreak is an agroforestry ecological system integrating economy, ecology andsociety. It plays a key role in reducing the wind speed, improving the microclimate and soilconditions of agricultural and animal husbandry production, maintaining the health offarmland ecosystem, ensuring the stable yield of agriculture and animal husbandry, andrealizing the sustainable development of farmland ecosystem. However, farmlandwindbreaks also have negative effects on crop yield. The evaluation of the protective effectof farmland windbreak is the key to test the rational construction of the windbreak and thescientific planning and design of the future windbreak. It is the link between theconstruction and management of the windbreak. What is the comprehensive benefit of thewindbreak? Does it help to achieve the goal of planning and design? It is the urgent need toanswer the question of windbreak effect. Therefore, this study selects the oasis in theManas River Basin which is a strong representative and typical in the arid area of Xinjiangand uses the remote sensing data and statistical data to carry out the evaluation of theprotective effect of the oasis farmland windbreak in the basin. The landscape pattern offarmland windbreaks in arid oasis and its effect on the main crop yield in the study area arealso studied. The following results were obtained:(1) The analysis of the landscape pattern with the ratio of belt to patch, theconnectivity and the ring degree to the windbreak of Manas County, Shawan County andthe Regimental Farm showed that the relative error of each landscape metric was greaterthan 0.15. The prominent problems include the limited windbreak area, uneven windbreakdistribution, small number of closed grids and poor forming conditions. In order to achievethe sustainability of the farmlands, the missing windbreak needs to be developed and thedensity of windbreak should also be increased.(2) Based on the Landsat8 OLI remote sensing image as the data source and the dataof the cotton space extracted by the object-oriented method, and the light energy utilizationmodel, the CASA model, and the crop biomass-yield model was used to analyze the yield of the main crop. Cotton production was estimated using the data released by the Bureau ofStatistics of the county cotton yield data to verify. The cotton acreage of the Manas RiverBasin accounts for 61.13% of the total area of crop cultivation, and the average yield ofcotton in the basin is 2049.27kg/ha, and the estimation error is less than 4%. It can be seenthat the high yield area of cotton higher than 2400kg/ha is mainly distributed in the centralarea of the oasis in Manas County, Farm 143, Farm 121 and Farm 122. The cotton yield is1800~2400kg/ha. The middle-yielding areas of cotton are mainly distributed in ShawanCounty and Oasis East and West. The low yield area of cotton yield below 1800kg/ha ismainly distributed in Xinhu Farm, Farm 136 West, Farm 135 and other southern edge aswell as near desert areas.(3) Based on the multi-period Landsat series of image data, the spatial distributioninformation of windbreak in different age groups was extracted. The quality coefficient ofwindbreaks was calculated by the normalized vegetation index of the windbreaks.Windbreak evaluation system was established to analyze the effect of different protectionlevels on cotton yield according to the tree height and the maximum protection distance ofdifferent age groups. The results showed that the cotton yield was in a stable state when theprotection level of Manas County and Shawan County was 70%. Compared with theprotection level of 0%, the cotton yield increased by 136 kg/ha and 175 kg/ha. When theprotection level of Regimental Farm is 90%, the cotton yield is in a basically stable state.Compared with the protection level of 0%, the cotton yield increased by 214kg/ha.Compared to Manas County and Shawan County landscape pattern, the Regimental Farmcoverage and continuity is poor, showing that the construction of the windbreak in theRegimental Farm needs to be further strengthened and improved