西南地区不同植被类型归一化植被指数与气候因子的相关分析

基于中国西南地区1982—2006年的归一化植被指数(NDVI)遥感数据集和气象数据,运用GIS技术对年均气温、年降水量和干旱指数进行插值,分析了西南地区不同植被类型(沼泽、灌丛、草丛、草原、草甸、针叶林、阔叶林、高山植被、栽培植被)NDVI的年际变化及其与气候因子的相关性.结果表明:研究期间,西南地区NDVI、年均气温、年降水量总体呈上升趋势,其中,年均气温的上升趋势达极显著水平,干旱指数则呈下降趋势;在9种植被类型中,沼泽和草丛NDVI呈下降趋势,且草丛的下降趋势达显著水平,其他7种植被类型的NDVI均呈上升趋势,且针叶林、草甸和高山植被的NDVI上升趋势达显著水平,灌丛NDVI呈极显著上升趋势.9种植被类型所在地区的年均气温均显著上升;年降水量的变化均不显著;沼泽、草丛和栽培植被所在地区的干旱指数呈上升趋势,草甸和高山植被所在地区的干旱指数显著下降,其他4种植被类型所在地区的干旱指数呈不明显的下降趋势.研究区灌丛和针叶林NDVI与年均气温呈显著正相关,灌丛和草甸NDVI与干旱指数呈显著负相关.在保持其他2个气候因子不变的情况下,针叶林、阔叶林、高山植被NDVI与年均气温的相关性最大,草丛NDVI与年降水...     

乌伊岭国家级自然保护区植被覆盖演变及其对气候突变的响应

探究中国北方高纬度森林覆盖区植被演变受到气候因子变化乃至突变的影响,选用MODIS-NDVI数据与TM/ETM+数据,结合62年的气象观测数据,运用像元二分法模型、累计距平分析、Mann-Kendall非参数检验、滑动T检验与相关性分析,探讨了乌伊岭国家级自然保护区1975—2016年气候变化及其突变对植被覆盖的演化规律,并对不同气候因子与植被覆盖类型的空间变化进行相关性分析。结果表明:(1)乌伊岭保护区气候变化呈现暖干化发展的趋势。年均气温上升(0.557℃/10a),年均最低气温与冬季增温幅度最快,秋季最慢。降水量年际变化较小(-14.052 mm/10a),季节性变化明显。经突变性检验,1980—1995年是气候增温减湿的突变时期。(2)研究区植被生长季的NDVI为0.673,有植被覆盖的区域占87.69%,其中高等植被覆盖区所占比最大。(3)气候突变时期,生长季NDVI显著下降,植被退化严重。低植被覆盖区无显著变化,而高植被覆盖区开始逐渐退化为中等与中低等植被覆盖区。在空间上植被覆盖的退化状况主要由中心山地沿四周低山丘陵区累年逐渐降低。不同植被覆盖区域下降的幅度:混交林草地针叶林耕地湿地。(4)乌伊岭保护区年均最大NDVI与年均气温和年均降水量的相关系数分别为0.261、0.068,其中呈正相关区域占总面积56.67%和42.79%,在分布趋势上两者都表现出明显的空间差异性。而气温因子影响植被覆盖的空间范围与能力更强,空间相关性更高,也是影响植被退化的主导因素。     

2001—2020年川西北高原归一化植被指数演变特征及其对极端气候的响应

川西北高原是典型的生态气候敏感区,其植被状况与气候变化密切相关。本研究基于2001—2020年MODIS-NDVI数据集和气象数据,采用最大值合成、地理探测器模型、线性趋势分析、相关分析等方法,研究川西北高原生长季归一化植被指数(NDVI)的变化趋势及其对气候因子的响应机制。结果表明: 研究期间,川西北高原植被覆盖度整体状况良好,86.8%的区域植被稳定,12.6%的区域NDVI呈弱持续性上升趋势,0.6%的区域NDVI呈下降趋势,全区生态环境呈稳中向好的发展趋势。研究区植被覆盖度空间差异大,总体呈由西南向东北上升的趋势,并有显著的立体变化。海拔1350 m以下,NDVI随海拔升高而上升;海拔1350～3650 m,NDVI无显著变化;海拔3650～5900 m,NDVI随海拔升高而下降,在4750～5900 m快速下降;海拔5900 m以上,几乎无植被。川西北高原的NDVI受多种自然因子交互作用影响,热量因子(月最高气温极大值、月最低气温极小值、植物生长期、年均温、生长期均温)是主导气候因子,除月最高气温极大值外,其余温度因子对NDVI均以正贡献为主。NDVI对气温指数的响应高于降水指数。在气候变暖背景下,极端气温暖指数对川西北高原植被生长尤其是高海拔地区植被生长及改善以促进作用为主。     

黄河上游不同干湿气候区植被对气候变化的响应

 研究气候变化背景下植被变化趋势及其与水热因子的关系, 对于黄河源区的生态恢复和生态建设具有重要意义。采用基于FAO Penman-Monteith的降水蒸散比来描述区域的干湿状况, 划分了黄河上游地区的干湿气候区。在此基础上, 利用AVHRR归一化植被指数(NDVI)和GLOPEM净初级生产力(NPP)数据集和同期的气候资料, 分析了黄河上游植被覆盖、植被生产力和气候变化的趋势, 探讨了不同干湿气候区影响植被变化的主要气候因子。结果表明, 研究区域东南部为半湿润气候区, 其余为半干旱气候区, 干湿气候分界线与450 mm降水等值线较接近; 1981–2006年区域气候趋于干暖化, 尤其是气温的升高趋势明显; 半湿润地区NDVI和NPP显著增加, 半干旱地区略有增加; 半湿润地区的NDVI多与气温显著正相关, 与降水量的相关性较弱, 气温是植被生长的主要气候制约因素; 半干旱地区的NDVI则与降水量的正相关性更强, 对降水量的变化较为敏感。NPP对气候变化的响应模式与NDVI相似。植被对气候变化的响应部分依赖于研究区域所具备的水热条件, 干湿气候划分有助于更好地解释植被对气候变化响应的空间差异。     

生长季川陕不同地带植被覆盖对气候变化的时空响应

川陕地区处于中国800mm等降水量线过渡带的南北两侧,区内分山、川、原3种地形,是退耕还林(草)最早实施区域。基于2001—2014年的MODIS、气温和降水量数据,选取10种植被地带数据,采用Sen+MK检验和时滞偏相关等方法,结合重分类后的4种地貌类型和6类土地利用/覆盖数据,分年内生长季、年际生长季和非生长季的对比、以及植被生长最好的8月与5月、6月、7月、8月、5—6月、6—7月、7—8月、5—8月共8个时间段的相关性3种时间尺度,对川陕地区植被NDVI与气候因子的关系进行了深入探讨。结果表明:1)川陕、陕西和四川年均气温分别以0.02℃/10a、0.01℃/10a和0.03℃/10a(通过0.01显著性水平)的线性速度增加,低于近50年来(1951—2001年)全国的气温增速(0.22℃/10a);2)川陕、陕西、四川尺度上,植被NDVI与同季气温、降水量的相关性一致,与上季的相关性不具一致性。植被NDVI与上季气温、降水量的相关性均高于同季,相较于降水量,与气温呈现出更多的负相关性,其中陕西地区最为显著;3)川陕地区气温变化趋势与全球变暖不同步,植被生长受气温的影响较小或无影响;降水量相较于气温对陕西地区植被生长的影响更大;气温是四川植被生长的主要限制因素。植被覆盖与气温、降水量的相关性在草地、林地和农耕区最为显著。     

黄土高原归一化植被指数与自然环境因子的空间关联性——基于地理探测器

植被对改善黄土高原脆弱的生态环境有着关键作用,系统研究黄土高原归一化植被指数(NDVI)空间分布和环境因子的空间关联性,可为新时代黄土高原植被高质量建设提供科学依据。以黄土高原2000-2017年年均植被NDVI为研究对象,选取气候要素、地形因素、土壤类型和植被类型等自然环境因子,运用GIS和地理探测器技术手段,在剔除土地利用类型发生变化栅格的基础上,研究黄土高原年均NDVI与环境因子的空间关联性,结果表明:2000-2017年黄土高原年均NDVI值在0.016-0.72之间,呈地带性分布,由西北部向东南部逐渐升高,大于0.3的区域占50.23%;2000-2017年黄土高原年均植被NDVI分布具有空间异质性,且在不同植被区、地貌区、土壤区和气候区中,NDVI空间分布的主要环境驱动因子具有差异性。年均降雨量对NDVI空间分布具有强解释力,是黄土高原85.20%的区域植被生长的主要制约因子;约12.01%的区域主要受土壤类型影响,为中等解释力,其余区域的植被生长主要受年均气温,日照时数或海拔影响。建议综合考虑不同环境条件下植被NDVI的空间分布与环境影响因子的空间关联性,明确不同区域中植被NDVI的环境制约因子,以制约因子定植,在防止土壤干燥化、贫瘠化的前提下,提高植被覆盖率和生物多样性,以期促进黄土高原植被建设高质量发展。     

1982-2016年东北黑土区植被NDVI动态及其对气候变化的响应

植被是陆地生态系统的重要组成部分,在调节气候、水土保持等方面具有重要作用,因此,监测植被生长变化并探讨其与气候变化之间的关系,在全球变化研究中具有重要意义。基于MODIS NDVI和GIMMS NDVI数据集,并通过一致性检验,在区域和像元两个空间尺度上,利用一元线性回归模型,研究东北黑土区1982-2016年植被生长动态,分析植被生长对气温和降水量的响应程度。结果表明：区域尺度上,1982-2016年东北黑土区植被生长季NDVI变化分为3个阶段（先增加继而减少最后再增加）,区域植被的生长在气温、降水量的共同作用下,呈现出明显季节差异;像元尺度上,1982-2016年东北黑土区NDVI总体趋势为改善状态,主要改善植被类型为草原、森林和农业植被,鹤岗市、绥化市和长春市改善面积较大;多年平均NDVI值与同期气温和降水量具有一定的相关关系,平原地区植被NDVI与气温主要呈显著正相关关系,植被类型主要为耕地;平原地区边缘和山地地区的植被NDVI与降水量以显著正相关关系为主,主要植被类型为森林和草地。     

湖北省地区植被覆盖变化及其对气候因子的响应

归一化植被指数(NDVI)作为一个重要的遥感参数,能够准确地反映植被覆盖程度和植被生长状况、生物物理化学性质及生态系统参数的变化,其时序数据也已成为基于生物气候特征开展大区域植被和土地覆盖分类的基本手段。基于2001—2012年MODIS-NDVI数据,利用趋势分析法以及线性相关分析等方法对湖北省植被年际变化趋势、月变化趋势进行详细分析;并且研究该区植被覆盖时空变化及其与气温和降水的关系。结果表明近12年来,研究区大部分区域植被覆盖度良好,其中鄂西北及鄂南地区NDVI值较高为0.82,鄂中东部城市NDVI值较低为0.13;2001—2012年间年均NDVI整体呈增加趋势,增速1%/10a;植被覆盖度基本不变区域占研究区总面积的92.8%,大致符合我国中部地区植被覆盖变化趋势;分析NDVI与气候因子的相关关系可知,降水量对湖北植被NDVI年变化起有重要影响;逐月NDVI与月平均气温及月降水量的回归分析表明,降水和气温对生长季不同月份的植被NDVI影响明显不同,同时呈现一定的滞后性。     

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。     

安徽省2000-2009年不同类型植被的变化及其与气温、降水的关系

为了了解安徽省不同类型植被与气候环境因子的关系,利用2000-2009年的逐月MODIS/NDVI数据、安徽省80个气象站逐日气温、降水资料和安徽省土地覆盖数据,研究了安徽省近10年来植被指数的时空变化特征及其与气温、降水的相关性.结果表明:近10年来,安徽省各覆盖类型的植被指数变化趋势不一致,作物种植区和城镇的植被指数增加显著,其他覆盖类型的植被指数变化不显著;林地的平均植被指数最高,作物种植区次之,城镇最低;植被指数的月变化在作物种植区呈现双峰型,而其他覆盖类型呈现单峰型.安徽省月平均NDVI分别与月平均气温、月降水量呈显著线性正相关和非线性正相关,降水量对植被NDVI的作用存在一个阈值,但年际关系均呈弱正相关.植被指数与气温的偏相关系数林地最高,作物种植区最低,自然植被区的偏相关系数较人工植被区的大,植被指数与降水的偏相关系数恰好相反.安徽省淮北平原中部和江淮之间北部大部分地区(非水浇地)的植被是由气温和降水的共同作用驱动;淮北中部少数格点和少数水体格点的植被是单独由降水作用驱动;除一些水面的格点是非气象因子驱动外,其他大部分地区的植被是单独由气温作用驱动.     

Climate and vegetation in China III water balance and distribution of vegetation

Distributions of 29 vegetation types in China as a function of climatic humidity or aridity were analysed using Thornthwaite's system, by employing meteorological records from 671 stations in China. The annual potential evapotranspiration and the humidity/aridity indices were calculated for every station, and distribution maps of water deficiency, water surplus and moisture index (Im) were constructed. The Im map showed that arid areas (Im<0) occupied about 56% of the country. The effect of the difference in soil water storage capacity on Thornthwaite's indices was examined, and Im values were found to differ little, although some differences were observed in actual annual evapotranspiration, water deficiency and water surplus values. Correlations between Im values and distributions of 29 vegetation types, identified from a vegetation map with a scale of 1/4000000, were investigated. The distributions of desert, steppe, woodland, deciduous forest and evergreen forest corresponded to Im values of below −40, −40–−20, −20-0, 0–60 and over 60, respectively. In addition, climatic factors delimiting the northern distribution of evergreen broadleaf forest were investigated, and it was clarified that the northern limit was restricted by combined hydrothermal conditions, and not by the low temperature in winter.     

Influence of vegetation and vegetation management on Culex mosquitoes in surface stormwater habitats

Wetlands Ecology and Management - Stormwater drainage infrastructure creates abundant, nutrient-rich habitats in urban landscapes vulnerable to colonization by undesirable organisms, including...     

Quantitative estimation of vegetation changes by comparing two vegetation maps

The main goal of our work was to estimate how large the errors are associated with repeated vegetation mapping. We compared two vegetation maps (both 1:10 000) of the Pieniny National Park—ca 2300 ha (southern Poland), the first made in 1966 and the second in 2001. We superimposed—using the ARC-INFO software—a dense grid of points (50 × 50 m) upon each map, and we determined the identity of vegetation unit in each point for the year 1966 and for the year 2001. That procedure was repeated 100 times, each time changing the position of the grid by a random vector. To estimate the size of mapping errors, we compared the patches of communities which should not change their location during 35 years: vegetation of rocky outcrops and local wet depressions, and fertile beech forest, considered a climax community for the Pieniny Mountains. Overlapping small vegetation patches (average patch size below 0.5 ha) yielded highly erroneous results, while the reliability of overlapping the communities with large patches is much higher, exceeding 80% for average patch size of 5 ha. Taking into consideration the communities of average patch size of 1 ha, we can estimate that the vegetation has undergone profound changes: some communities expanded, while others shrunk. The area of meadows remained about the same, but majority of meadows in 2001 was located in former arable fields and previous meadow areas become forested. Among beech forests, we recorded an increase of area covered by floristically rich variants at the expense of floristically poor variants. We conclude that some information about vegetation changes may be obtained only by comparing sequential vegetation maps, but the reliability of the results strongly depends on the size of vegetation patches.     

Climate and vegetation in China II. Distribution of main vegetation types and thermal climate

The authors examined relationships between Kira's warmth index (WI) and four other important thermal indices: the sums of daily mean temperatures above 5°C and 10°C, Thornthwaite's potential evapotranspiration (PE) and Holdridge's annual biotemperature. The thermal records of 671 meteorological stations evenly located all over China were used to make these comparisons. Close correlations were found within the four relationships, and accordingly WI was used to analyse the thermal distributions of the main vegetation types. Vegetation types around the 671 stations were read from a vegetation map with a scale of 1/4000000. Vegetation types at 269 stations corresponded to the natural or seminatural vegetation, and 29 vegetation types were distinguished by arranging the 269 data into the same or similar types. The geographical distribution of these 29 types and the corresponding main climatic features were described. The relations between WI and distribution of these vegetation types were discussed in detail. As a result, WI values (°C month) corresponding to the vegetation zones could be summarized as follows: (1) arctic or alpine vegetation zone: 0–15; (2) boreal or subalpine vegetation zone: 15-(50–55); (3) cool-temperate vegetation zone: (50–55)–(80–90); (4) warm-temperate vegetation zone: (80–90)–(170–180). These values almost coincided with Kira's values. Chinese postgraduate student in Japan sent by the Chinese Government.     

Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth

This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution.     

Soils and vegetation of central Australian sandridges III. Sandridge vegetation of the Simpson Desert

This is the third of a series of papers describing the soils and vegetation of the central Australian sandridges and their interrelations. It details topographic—floristic patterns on fourteen transects at seven sites in the northwest, southwest and southeast Simpson Desert. There is a consistent vegetational zonation on the main Simpson sandridges, with regional modifications due to the broad scale NW-SE floristic gradient. Closer dunes have more similar vegetation than distant ones. Swale vegetation is less consistent than sandridge vegetation and depends on soil type. Species differ greatly in their degree of restriction both topographically and geographically. Zone separation differs greatly between dunes in consequence. Zones defined on overall floristics are less clearly separated in the Simpson than in the western deserts. A floristically and structurally distinct crest zone is recognizable on all main dunefield sandridges. The only universally applicable zonation is swale, flank, crest. Vegetation patterns are more closely correlated with field soil texture than with topography.     

Patterned vegetation and rainfall intermittency

We study a mathematical model for the dynamics of patterned dryland vegetation in the presence of rainfall intermittency, adopting a spatially explicit approach. We find that most results found for constant precipitation carry over to the case of intermittent rainfall, with a few important novelties. For intermittent precipitation, the functional forms of the water uptake and consequently of the vegetation growth rate play an important role. Nonlinear, concave-up forms of water uptake as a function of soil moisture lead to a beneficial effect of rainfall intermittency, with a stronger effect when vegetation feedbacks are absent. The results obtained with the explicit-space model employed here are in keeping with those provided by simpler, implicit-space approaches, and provide a more complete view of vegetation dynamics in arid ecosystems.     

Climate change and vegetation response

This study, as many other current investigations in palaeoecology is focused on the long-term dynamics of vegetation and the extent to which they are controlled by climate change. Climate and classes of climate change are defined and reviewed, and examples cited of vegetation response. The concepts of vegetation, plant community and equilibrium are examined, with particular emphasis on theories on short term dynamics developed by ecologists working with temperate and boreal forests. Vegetation response to climate change can be modified by anthropogenic factors, topographic diversity and soils, life-cycle characteristics and hysteresis.I am grateful for comments on an earlier version of this paper by Keith Bennett, Les Cwynar and Glen MacDonald, and I particularly appreciate the useful remarks by Colin Prentice.I am grateful for comments on an earlier version of this paper by Keith Bennett, Les Cwynar and Glen MacDonald, and I particularly appreciate the useful remarks by Colin Prentice.