The spatial distribution of vegetation types in the Serengeti ecosystem: the influence of rainfall and topographic relief on vegetation patch characteristics

Aim The aim of this study is to introduce a structural vegetation map of the Serengeti ecosystem and, based on the map, to test the relative influences of landscape factors on the spatial heterogeneity of vegetation in the ecosystem. Location This study was conducted in the Serengeti–Maasai Mara ecosystem in northern Tanzania and southern Kenya, between 34° and 36° E longitude, and 1° and 2° S latitude. Methods The vegetation map was produced from satellite imagery using data from over 800 ground‐truthing points. Spatial characteristics of the vegetation were analysed in the resulting map using the fragstats software package. Average patch area and nearest neighbour distance (NND) were determined for grassland, shrubland and woodland vegetation types. The heterogeneity of vegetation types was estimated with Simpson’s diversity index (D). Structural equation modelling (SEM) was used to explore the relationships between the spatial characteristics of vegetation and three predictor variables: annual rainfall, coefficient of variation (CV) in annual rainfall, and topographic moisture index (TMI). Results A vegetation map is presented along with a detailed summary of the distribution of land‐cover classes and spatial heterogeneity in the ecosystem. Significant relationships were found between vegetation diversity (D) and TMI, and also between D and average rainfall. The average area of grassland patches showed significant relationships with average rainfall, with rainfall CV and with TMI. Grassland NND was positively associated with average rainfall. Woodland patch area showed a unimodal response to average rainfall and a negative linear association with TMI. Woodland NND showed a U‐shaped association with annual rainfall and a weaker positive linear association with TMI. An acceptable model that explained variation in shrubland patch characteristics could not be identified. Main conclusions The vegetation map and analysis thereof resulted in three significant causal explanatory models that demonstrate that both rainfall and topography are important contributors to the distribution of woodlands and grasslands in the Serengeti. These findings further indicate that changes in patch characteristics have a complex interaction with rainfall and with topography. Our results are concordant with recent studies suggesting that percent woody cover in African savannas receiving less than c. 650 mm year^?1 is bounded by average annual rainfall.     

KIRA指标的拓展及其在中国植被与气候关系研究中的应用

根据Kira以月平均气温5℃为界的热量指数和干湿度指数概念,提出了以月平均气温10℃为界的生物热量指数,包括生物温暖指数(BWI)和生物寒冷指数(BCI),并修正其干湿度指数为生物干湿度指数(BK).利用中国689个标准气象台站的资料,分析我国主要植被类型分布与热量因子和干湿度因子的关系,得出两者之间较好的相关性,生物温暖指数、寒冷指数和干湿度指数的散点图较好地表现了中国各植被类型与气候指标的关系和格局.以10℃为界的生物温暖指数不仅对我国森林植被的地理分布和温度气候带的划分具有较好的指示作用,而且对西南部高山、亚高山地区的植被与气候关系指示性较强;生物寒冷指数则对亚热带和热带的指示性很好,能够较好区分亚热带南部及热带地区;由热量指数和降水量综合得出的生物干湿度指数,对中国西北部干旱、半干旱区以至全国的植被分布与水分、热量因子的关系分析有较好的应用价值.     

Vegetation pattern of mountains in West Greenland – a baseline for long-term surveillance of global warming impacts

Background: Steep environmental gradients, coupled with predicted high temperature rises in the Arctic make arctic mountain vegetation highly suitable for surveillance of changes related to global warming. However, guidelines and baselines for such a purpose are widely lacking since arctic mountain vegetation has been little explored.

Aims: We explore options for long-term surveillance on the basis of a detailed analysis of extant plant community patterns and their underlying environmental conditions in the mountainous inland of West Greenland.

Methods: Distribution, abundance and site conditions of vegetation types were analysed, using 664 vegetation samples and detailed vegetation maps in four altitudinal belts.

Results: Most plant communities had a restricted elevation distribution and were confined to special habitats predominantly defined by mesotopography and soil moisture.

Conclusions: Based on the strong linkage to habitat conditions, horizontal and vertical changes of species distribution and vegetation pattern are excellent indicators for inferring underlying environmental changes on three different scales. The recommendations given concerning climate sensitive species and plant communities, ecotones for setting up observation sites as well as stratification of analysis by habitats can be the basis for establishing long-term surveillance programmes on arctic mountain vegetation.     

Spatial-temporal character of vegetation cover and its influence factors in the Shule River Basin China,during 1985–2011

Abstract

Vegetation coverage is an important indicator of the terrestrial ecosystems, and it provides crucial significance for evaluation and analysis of vegetation change. The Shule River Basin is a typical ecological fragile region in the inland of Northwest China. We used vegetation coverage index as given in Technical Specifications for Assessment of Ecological Environment. Geographic information system (GIS) spatial analysis was used to analyze the temporal and spatial features of vegetation cover in the Shule River Basin and its influencing factors from 1986 to 2011. The results showed that vegetable cover is very low in most areas of Shule River Basin with only the upstream parts of the oasis and watershed haven high vegetation cover. The average vegetation coverage index increased from 6.78 to 8.31 during 1986–2011. An area of 59,998?km² in the Shule River Basin has unchanged vegetation coverage index and this account for 51.7% of watershed areas for the period of the study. Also, an area of 31,721?km² recorded an increased vegetable cover, accounting for 27.3% while an area of 24,372?km² decreased vegetation cover which accounts for 21.0%. There was different correlation between vegetation cover and annual precipitation in the Shule River Basin.     

2000-2019年重庆市植被覆盖时空变化特征及其驱动因素

基于MODIS-NDVI数据、气象数据、地形数据和人类活动数据,采用趋势分析等方法,应用地理探测器模型,全面分析2000-2019年重庆市植被覆盖时空变化特征,并探究各地理因子及其交互作用对重庆市植被覆盖的影响程度与作用机制。研究发现:(1)2000-2019年,重庆市植被覆盖整体呈波动上升趋势,增长率为4.4%/10a,NDVI偏差值呈先减小后增加趋势。(2)2000-2019年,重庆市植被覆盖高值区主要分布于渝东北和渝东南,低值区则主要分布于三峡库区消落带及渝西、主城地区;植被覆盖空间格局在东西方向上由"一字型"向"斜线型"演化,南北方向上由"浅U型"向"深U型"演化。(3)2000-2019年,各地理因子对重庆市植被覆盖空间分异性解释力大小依次为:年均温(0.3459)>高程(0.3281)>年均降水量(0.2305)>人类活动强度指数(0.1747)>坡度(0.1008)>总辐射(0.0552)>坡向(0.0034);年均温、坡向、人类活动强度指数解释力总体呈增加趋势,年均降水量、总辐射、高程、坡度解释力总体呈减小趋势。(4)2000-2019年,各地理因子对重庆市植被覆盖变化存在交互作用,且呈双因子增强和非线性增强两种类型,而不存在相互独立作用或对植被覆盖变化解释力减弱的交互因子。     

I piani di vegetazione in Italia

Abstract

Vertical zonation of vegetation in Italy. – A revision of the scientific terms used by Italian botanists for the vertical zonation of vegetation reveals some inconsistencies and allows to propose an alignement with the nomenclature used in English and proposed already during the International Botanical Congress of 1910: Belt (ital.: fascia) for the topographical zonation and zone (ital.: zona) for the geographical zonation. Italy belongs to two zones: the mediterranean and the medioeuropean one. A scheme of vegetation belts in both of the zones is proposed. The indications subalpine and montane are substituted by boreal and subatlantic.     

MODISTools – downloading and processing MODIS remotely sensed data in R

Remotely sensed data – available at medium to high resolution across global spatial and temporal scales – are a valuable resource for ecologists. In particular, products from NASA's MODerate‐resolution Imaging Spectroradiometer (MODIS), providing twice‐daily global coverage, have been widely used for ecological applications. We present MODISTools, an R package designed to improve the accessing, downloading, and processing of remotely sensed MODIS data. MODISTools automates the process of data downloading and processing from any number of locations, time periods, and MODIS products. This automation reduces the risk of human error, and the researcher effort required compared to manual per‐location downloads. The package will be particularly useful for ecological studies that include multiple sites, such as meta‐analyses, observation networks, and globally distributed experiments. We give examples of the simple, reproducible workflow that MODISTools provides and of the checks that are carried out in the process. The end product is in a format that is amenable to statistical modeling. We analyzed the relationship between species richness across multiple higher taxa observed at 526 sites in temperate forests and vegetation indices, measures of aboveground net primary productivity. We downloaded MODIS derived vegetation index time series for each location where the species richness had been sampled, and summarized the data into three measures: maximum time‐series value, temporal mean, and temporal variability. On average, species richness covaried positively with our vegetation index measures. Different higher taxa show different positive relationships with vegetation indices. Models had high R² values, suggesting higher taxon identity and a gradient of vegetation index together explain most of the variation in species richness in our data. MODISTools can be used on Windows, Mac, and Linux platforms, and is available from CRAN and GitHub ( https://github.com/seantuck12/MODISTools ).     

Spatial variability of above‐ground net primary production in Uruguayan grasslands: a remote sensing approach

Question: How does above‐ground net primary production (ANPP) differ (estimated from remotely sensed data) among vegetation units in sub‐humid temperate grasslands? Location: Centre‐north Uruguay. Methods: A vegetation map of the study area was generated from LANDSAT imagery and the landscape configuration described. The functional heterogeneity of mapping units was analysed in terms of the fraction of photosynthetically active radiation absorbed by green vegetation (fPAR), calculated from the normalized difference vegetation index (NDVI) images provided by the moderate resolution imaging spectroradiometer (MODIS) sensor. Finally, the ANPP of each grassland class was estimated using NDVI and climatic data. Results: Supervised classification presented a good overall accuracy and moderate to good average accuracy for grassland classes. Meso‐xerophytic grasslands occupied 45% of the area, Meso‐hydrophytic grasslands 43% and Lithophytic steppes 6%. The landscape was shaped by a matrix of large, unfragmented patches of Meso‐xerophytic and Meso‐hydrophytic grasslands. The region presented the lowest anthropic fragmentation degree reported for the Rio de la Plata grasslands. All grassland units showed bimodal annual fPAR seasonality, with spring and autumn peaks. Meso‐hydrophytic grasslands showed a radiation interception 10% higher than the other units. On an annual basis, Meso‐hydrophytic grasslands produced 3800 kg dry matter (DM) ha^?1 yr^?1 and Meso‐xerophytic grasslands and Lithophytic steppes around 3400 kg·DM·ha^?1·yr^?1. Meso‐xerophytic grasslands had the largest spatial variation during most of the year. The ANPP temporal variation was higher than the fPAR variability. Conclusions: Our results provide valuable information for grazing management (identifying spatial and temporal variations of ANPP) and grassland conservation (identifying the spatial distribution of vegetation units).     

基于灰熵关联的平均住院日影响因素研究

目的:分析医疗指标与平均住院日的关联程度,为医院有效缩短平均住院日提供参考依据。方法:建立基于灰熵优化的加权灰色关联度模型,对影响平均住院日的医疗指标进行重要程度的分析。结果:根据关联程度分析,可知影响平均住院日的医疗指标重要程度依次为开放床位数、床位周转次数、治疗有效率、床位使用率、年门诊量、住院手术人次和出院人数。结论:基于灰熵优化的加权灰色关联分析方法可以有效分析医疗指标对平均住院日的影响程度,提高医疗服务质量。     

河西绿洲边缘积沙带形成的典型相关因子

绿洲边缘积沙带的形成因素及其生态效应是一个新的科学问题。为了研究河西绿洲边缘积沙带的形成原因,运用方差分析、相关分析以及典型相关分析等方法,对河西绿洲边缘积沙带的21个样点的观测资料进行了分析。结果表明:河西绿洲边缘积沙带的分布趋势大致为东高西低、东宽西窄,大部分地段目前处于稳定阶段;积沙带上的优势种植物以天然柽柳最多,不同优势种植物的积沙带的迎风坡植被盖度及植被纯盖度差异较显著。典型相关分析结果表明:积沙带的高度和宽度是降水量、到沙源的距离、背风坡植被盖度和年平均风速等气候环境因子共同作用的结果。积沙带的生态效应:一是自身作为一种障碍物的防护作用,二是阻截、减少流沙流沙进入农田的作用。     

基于环境卫星数据的黄河湿地植被生物量反演研究

回归模型拟合植被指数与生物量的定量关系是植被生物量反演的重要研究方法之一.研究在此基础上,基于环境卫星遥感数据和同步野外实地采样数据,以郑州黄河湿地自然保护区为试验区,比较MLRM(多元线性回归模型)与SCRM(一元曲线回归模型)反演植被生物量的能力,并估算研究区植被生物量,生成研究区生物量分布图.结果表明,文中所建立的MLRM在研究区具有较好的反演精度和预测能力.其模型显著性检验为极显著,相关系数为0.9791,模型拟合精度达到29.8 g/m2,其模型预测结果系统误差为49.9g/m2,均方根误差为67.2 g/m2,预测决定系数为0.8742,比传统的一元回归模型具有更高的精度和可靠性.估算研究区域2010年8月湿生植被生物量约为6.849199 t/hm2,相对误差为4.73％.     

低覆盖度行带式固沙林对土壤及植被的修复效应

在我国干旱、半干旱地区由于水分条件的制约,经过漫长的自然演替过程,逐步发育形成了广泛分布的低覆盖度植被,这些低覆盖度植被类型中存在大量的天然乔木疏林或稀疏灌丛,地表处于半流动状态,而配置成行带式后,能够完全固定流沙,并且不同配置模式下行带式固沙林土壤与植被自然恢复程度不同.因此,通过对不同带宽的低覆盖度行带式固沙林对土壤及植被修复的影响研究,揭示了不同带宽行带式固沙林带间土壤因子与植被因子的变化过程,从而阐明行带式固沙林对带间植被自然恢复和土壤发育的促进作用.结果表明,行带式杨树固沙林能够明显的促进带间土壤与植被修复;带间距离的宽窄影响植被恢复及土壤发育效果;宽带间距固沙林带间植被多样性指数高,地上生物量大,根系生物量,总长度及表面积均高,土壤水分养分条件好,微生物数量大植物残体分解快,有利于植被的生长;模糊综合评估结果表明,不同带间距行带式固沙林土壤植被恢复程度不同,宽带间距20m的恢复效果＞带间距15m＞带间距10m.行带式固沙林通过带间宽度的变化可以调节植被与土壤之间的相互作用,窄带间距固沙林土壤与植被的相互作用则由于造林密度大而受到抑制.宽带间距可以明显加快土壤及植被修复的速度,进而缩短土壤及植被修复的时间.     

2000-2019年京津冀地区植被覆盖状况变化及驱动因素

近20年来中国和印度通过土地利用活动改变地表覆盖使植被变得更绿,京津冀地区是植被变得更绿的典型地区。收集京津冀地区2000-2019年MODIS增强型植被指数（EVI）、植被覆盖百分比数据,以及年平均温度和降水量等数据,分析该区近20年来自然植被和农田植被EVI变化过程和趋势,揭示其变化的驱动因素,结果显示2000-2019年京津冀地区自然植被和农田植被EVI显著增加,自然植被EVI增加速率是农田植被的1.8倍。99.51%的自然植被和96.95%的农田植被生长状况改善。2000-2019年京津冀地区自然植被EVI与年平均温度和年降水量相关性不显著。农田植被EVI与年平均温度显著相关,与年降水量相关性不显著。农田灌溉和年平均温度变化是农田植被EVI显著增加的主要驱动因素。近20年京津冀地区通过实施以造林为主的生态建设工程,自然植被生长覆盖状况呈现极显著变好。同时森林植被比非森林植被覆盖百分比增加趋势更明显。以造林为主的生态建设工程是京津冀地区自然植被生长覆盖状况显著变好的主要驱动因素。     

基于NDVI的米仓山植被覆盖变化趋势分析

基于1998年4月至2009年12月的SPOT-VEGETATION逐旬NDVI数据,采用MVC(最大值合成法)获得月NDVI值,用均值法计算各季及年均NDVI值;对5种植被类型的年均NDVIy和生长季NDVIg进行一元线性回归,辅助以趋势线分析定量描述研究区植被覆盖动态变化,并采用R/S分析(重标极差法)动态预测米仓山植被覆盖未来变化趋势。结果表明:研究区12年间NDVI整体呈上升趋势,相对于前期(1999~2001年)、中期(2003~2005年)和后期(2007~2009年)的NDVI增加显著;年最大NDVI≥0.70的区域占总面积的98.95%,年均NDVI≥0.70的区域占93.69%,且植被覆盖增加的面积远大于减少的面积;划分的5种植被类型中,阔叶林类NDVI值最高,人工植被类NDVI值最低;R/S法计算结果显示,Hurst指数(H)为0.876 8,表现为很强的持续性,预示未来一定时限内米仓山植被覆盖将有稳定的增加趋势。     

Report of the Alpine Section

Background: Under climate-change scenarios, rock outcrops, by providing microclimatically diverse habitats, different from those of surrounding zonal vegetation matrix, may serve as climatic refugia and thereby facilitate the persistence of specialist species.

Aim: We tested whether rock outcrops of southern temperate latitudes could act as local refugia for a cold-adapted flora in the face of global warming.

Methods: We related species composition of 50 outcrops and that of their surrounding vegetation to climatic data at local and regional scales to establish whether species distributions reflected differences that could indicate the existence of climatic refugia.

Results: While at a regional scale, species composition of the outcrops across the study area was related to mean annual precipitation and mean annual maximum temperature, locally, southern faces of outcrops had different species and lower maximum temperatures than insolated north faces and surrounding vegetation plots.

Conclusions: South faces of outcrops by providing cool microhabitats, and currently harbouring species not found in the surrounding zonal vegetation matrix, could serve as local refugia for heat-intolerant plants and other microthermic organism. The degree of ‘stability’ of these refugia will depend on the degree of future change in climate. Therefore, it is important to plan protected area networks that maximise local environmental heterogeneity, including the protection of rock outcrops both as refugia for cold-adapted species and as potential stepping stones that would allow dispersal of these species between supportive environments through unfavourable ones.     

Abiotic resource depletion potentials (ADPs) for elements revisited—updating ultimate reserve estimates and introducing time series for production data

Purpose

In 1995, the original method for assessing the impact category abiotic resource depletion using abiotic depletion potentials (ADPs) was published. The ADP of a resource was defined as the ratio of the annual production and the square of the ultimate (crustal content based) reserve for the resource divided by the same ratio for a reference resource (antimony (Sb)). In 2002, ADPs were updated based on the most recent USGS annual production data. In addition, the impact category was sub-divided into two categories, using two sets of ADPs: the ADP for fossil fuels and the ADP for elements; in this article, we focus on the ADP for elements. Since then, ADP values have not been updated anymore despite the availability of updates of annual production data and also updates of crustal content data that constitute the basis of the ultimate reserves. Moreover, it was known that the coverage of elements by ADPs was incomplete. These three aspects together can affect relative ranking of abiotic resources based on the ADP. Furthermore, dealing with annually changing production data might have to be revisited by proposing new calculation procedures. Finally, category totals to calculate normalized indicator results have to be updated as well, because incomplete coverage of elements can lead to biased results.

Methods

We used updated reserve estimates and time series of production data from authoritative sources to calculate ADPs for different years. We also explored the use of several variations: moving averages and cumulative production data. We analyzed the patterns in ADP over time and the contribution by different elements in the category total. Furthermore, two case studies are carried out applying two different normalization reference areas (the EU 27 as normalization reference area and the world) for 2010.

Results and discussion

We present the results of the data updates and improved coverage. On top of this, new calculation procedures are proposed for ADPs, dealing with the annually changing production data. The case studies show that the improvements of data and calculation procedures will change the normalized indicator results of many case studies considerably, making ADP less sensitive for fluctuating production data in the future.

Conclusions

The update of ultimate reserve and production data and the revision of calculation procedures of ADPs and category totals have resulted in an improved, up-to-date, and more complete set of ADPs and a category total that better reflects the total resource depletion magnitude than before. An ADP based on the cumulative production overall years is most in line with the intent of the original ADP method. We further recommend to only use category totals based on production data for the same year as is used for the other (emission-based) impact categories.

     

Trends in phenological phases in Europe between 1951 and 1996

Increases in air temperature due to the anthropogenic greenhouse effect can be detected easily in the phenological data of Europe within the last four decades because spring phenological events are particularly sensitive to temperature. Our new analysis of observational data from the International Phenological Gardens in Europe for the 1959–1996 period revealed that spring events, such as leaf unfolding, have advanced on average by 6.3 days (–0.21 day/year), whereas autumn events, such as leaf colouring, have been delayed on average by 4.5 days (+0.15 day/year). Thus, the average annual growing season has lengthened on average by 10.8 days since the early 1960s. For autumn events, differences between mean trends of species could not be detected, but for spring events there were differences between species, with the higher trends for leaf unfolding and flowering of shrubs indicating that changes in events occurring in the early spring are more distinct. These observed trends in plant phenological events in the International Phenological Gardens and results of other phenological studies in Europe, summarised in this study, are consistent with AVHRR satellite measurements of the normalized difference vegetation index from 1981 to 1991 and with an analysis of long-term measurements of the annual cycle of CO₂ concentration in Hawaii and Alaska, also indicating a global lengthening of the growing season. Received: 21 October 1999 / Accepted: 2 March 2000     

中国东北城乡植被物候时空变化及其对地表温度的响应

以中国东北地区的沈阳、长春、哈尔滨3个大城市及其周边的乡村为研究单元,在像元尺度上采用小波变换法对长时间序列中分辨率成像光谱仪(Moderate-resolution Imaging Spectroradiometer, MODIS)增强植被指数(Enhanced Vegetation Index, EVI)数据滤除噪声数据后重建平滑的EVI曲线,基于EVI曲线,采用动态阈值法提取出研究区2009—2016年植被关键物候期参数指标,即植被生长季开始时间(Start of Growing Season, SOS)和结束时间(End of Growing Season, EOS),分析各研究单元植被物候时空变化特征及其对地表温度的响应特征。结果表明:各研究单元SOS和EOS值的空间分布图存在明显的城乡差异。每一个像元所属的实际位置距离城区中心越近,其SOS值越小,EOS值越大,表明植被生长季开始日期早结束日期晚,整个植被生长期时间变长。各研究单元植被物候参数指标的年际变化趋势具有一定的相似性,即SOS随时间均呈现出提前趋势,且城区和乡村的SOS年际变化趋势保持一致,变化速率各不相同。研究区2012年的SOS值是研究时段内的最大值,从植被物候期反映来看,该年是一个最冷年,这与当年受寒潮影响,出现暴雪,低温等极端天气的气候现象相吻合。各研究单元年均地表温度(Land Surface Temperature,LST)与对应的植被关键物候期参数均有显著的相关性,SOS与LST呈显著负相关,EOS与LST呈高度正相关。即植被物候同期的平均温度越高,植被生长季的起始时间越早,结束时间越晚。     

黄土高原不同植被覆被类型NDVI对气候变化的响应

植被与气候是目前研究生态与环境的重要内容。为探究黄土高原地区植被与气候因子之间的响应机制,利用线性趋势分析、Pearson相关分析、多元线性回归模型以及通径分析的方法,对黄土高原2000—2015年全区和不同植被覆被类型区内NDVI与气候因子的变化趋势以及相互作用关系进行分析。植被覆被分类数据和植被指数数据分别来源于ESA CCI-LC(The European Space Agency Climate Change Initiative Land Cover)以及MODND1T/NDVI(Normalized Difference Vegetation Index)。结果表明:(1) 2000—2015年黄土高原全区植被年NDVI_(max)显著增加的区域占总面积的74.25%,不同植被覆被类型年NDVI_(max)分别为常绿阔叶林常绿针叶林落叶阔叶林落叶针叶林镶嵌草地农田镶嵌林地草地灌木,并且都呈显著增加趋势,其中常绿阔叶林和农田增加幅度最大,为0.012/a。(2)黄土高原全区NDVI与气温、日照、降水和相对湿度等气候因子之间没有显著相关性,但在不同植被覆被类型区,气候因子对NDVI存在显著作用,且不同植被覆被类型差异明显。(3)在全区和不同植被覆被类型区NDVI仅对降水的响应比较一致,气温无论在整个区域尺度还是不同植被覆被类型区对植被的影响均不显著。(4)常绿阔叶林、落叶阔叶林、常绿针叶林及镶嵌林地等以乔木为主的植被覆被类型受年均相对湿度和年总日照时数的显著负效应驱动,草地、镶嵌草地等以草本为主的植被覆被类型则受到年总降水量的显著正效应影响。这说明对植被类型进行区分,更有利于揭示气候对植被的作用机制。     

新疆玉龙喀什河与策勒河流域胡杨年轮对气象因子的响应研究

在树木年轮学与气候学理论基础上,以新疆和田地区玉龙喀什河与策勒河下游河岸胡杨为研究对象,基于流域对应的气象、沙尘天气日数、策勒河径流量等因子,分析了玉龙喀什河与策勒河流域胡杨年轮对气象因子的响应特征,以明确干旱荒漠区胡杨生长过程中的气候限制因子,为促进胡杨生态修复及沙尘防治提供理论依据。结果显示:(1)1976-2018年期间,两流域的气象条件基本一致,其中年均气温呈明显上升趋势,年均降水量呈波动上升趋势,大气相对湿度呈下降趋势,年均沙尘暴、扬沙、浮尘日数均呈显著下降趋势;玉龙喀什河流域的胡杨年轮指数呈先显著上升后整体平缓变化的趋势,而策勒河流域的胡杨年轮指数从1985年开始呈较显著的上升趋势。(2)策勒河流域胡杨年轮指数对年均气象要素的响应显著高于玉龙喀什河流域,且策勒河流域树木年轮指数与年均气温呈显著正相关关系(P0.01),但两流域胡杨年轮指数对年均降水量和大气相对湿度的响应均不显著。(3)玉龙喀什河流域胡杨年轮指数与2月份的大气相对湿度呈显著负相关关系(P0.05);策勒河流域胡杨年轮指数与3、4、9、10月份的气温呈显著正相关关系,与6月份的大气相对湿度呈显著负相关关系(P0.05),与2、4月份的径流量呈显著负相关关系。(4)玉龙喀什河流域胡杨年轮指数与秋冬季节的沙尘暴日数、扬沙日数均呈显著负相关关系;除1、2月份外,策勒河流域胡杨年轮指数与月沙尘(沙尘暴、扬沙、浮尘)天气日数基本均呈显著负相关关系。研究认为,玉龙喀什河与策勒河流域的降水稀少且蒸发量大,胡杨生长所需水源主要依赖于地下水和地表径流的补给,策勒河流域胡杨年轮指数受气温、径流量以及修建水库的影响比较明显。