Spatiotemporal Patterns of Production Can Be Used to Detect State Change Across an Arid Landscape

Methods to detect and quantify shifts in the state of ecosystems are increasingly important as global change drivers push more systems toward thresholds of change. Temporal relationships between precipitation and aboveground net primary production (ANPP) have been studied extensively in arid and semiarid ecosystems, but rarely has spatial variation in these relationships been investigated at a landscape scale, and rarely has such information been viewed as a resource for mapping the distribution of different ecological states. We examined the broad-scale effects of a shift from grassland to shrubland states on spatiotemporal patterns of remotely sensed ANPP proxies in the northern Chihuahuan Desert. We found that the normalized difference vegetation index (NDVI), when averaged across an eight-year period, did not vary significantly between these states, despite changes in ecosystem attributes likely to influence water availability to plants. In contrast, temporal relationships between precipitation and time-integrated NDVI (NDVI-I) modeled on a per-pixel basis were sensitive to spatial variation in shrub canopy cover, a key attribute differentiating ecological states in the region. The slope of the relationship between annual NDVI-I and 2-year cumulative precipitation was negatively related to, and accounted for 71% of variation in, shrub canopy cover estimated at validation sites using high spatial resolution satellite imagery. These results suggest that remote sensing studies of temporal precipitation–NDVI relationships may be useful for deriving shrub canopy cover estimates in the region, as well as for mapping other ecological state changes characterized by shifts in long-term ANPP, plant functional type dominance, or both.     

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350–1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land‐atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~?7.5 g C m^?2 day^?1 during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350–1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models.     

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。     

Ecological Thresholds in the Savanna Landscape: Developing a Protocol for Monitoring the Change in Composition and Utilisation of Large Trees

Background

Acquiring greater understanding of the factors causing changes in vegetation structure - particularly with the potential to cause regime shifts - is important in adaptively managed conservation areas. Large trees (≥5 m in height) play an important ecosystem function, and are associated with a stable ecological state in the African savanna. There is concern that large tree densities are declining in a number of protected areas, including the Kruger National Park, South Africa. In this paper the results of a field study designed to monitor change in a savanna system are presented and discussed.

Methodology/Principal Findings

Developing the first phase of a monitoring protocol to measure the change in tree species composition, density and size distribution, whilst also identifying factors driving change. A central issue is the discrete spatial distribution of large trees in the landscape, making point sampling approaches relatively ineffective. Accordingly, fourteen 10 m wide transects were aligned perpendicular to large rivers (3.0–6.6 km in length) and eight transects were located at fixed-point photographic locations (1.0–1.6 km in length). Using accumulation curves, we established that the majority of tree species were sampled within 3 km. Furthermore, the key ecological drivers (e.g. fire, herbivory, drought and disease) which influence large tree use and impact were also recorded within 3 km.

Conclusions/Significance

The technique presented provides an effective method for monitoring changes in large tree abundance, size distribution and use by the main ecological drivers across the savanna landscape. However, the monitoring of rare tree species would require individual marking approaches due to their low densities and specific habitat requirements. Repeat sampling intervals would vary depending on the factor of concern and proposed management mitigation. Once a monitoring protocol has been identified and evaluated, the next stage is to integrate that protocol into a decision-making system, which highlights potential leading indicators of change. Frequent monitoring would be required to establish the rate and direction of change. This approach may be useful in generating monitoring protocols for other dynamic systems.     

Global change could amplify fire effects on soil greenhouse gas emissions

Background

Little is known about the combined impacts of global environmental changes and ecological disturbances on ecosystem functioning, even though such combined impacts might play critical roles in shaping ecosystem processes that can in turn feed back to climate change, such as soil emissions of greenhouse gases.

Methodology/Principal Findings

We took advantage of an accidental, low-severity wildfire that burned part of a long-term global change experiment to investigate the interactive effects of a fire disturbance and increases in CO₂ concentration, precipitation and nitrogen supply on soil nitrous oxide (N₂O) emissions in a grassland ecosystem. We examined the responses of soil N₂O emissions, as well as the responses of the two main microbial processes contributing to soil N₂O production – nitrification and denitrification – and of their main drivers. We show that the fire disturbance greatly increased soil N₂O emissions over a three-year period, and that elevated CO₂ and enhanced nitrogen supply amplified fire effects on soil N₂O emissions: emissions increased by a factor of two with fire alone and by a factor of six under the combined influence of fire, elevated CO₂ and nitrogen. We also provide evidence that this response was caused by increased microbial denitrification, resulting from increased soil moisture and soil carbon and nitrogen availability in the burned and fertilized plots.

Conclusions/Significance

Our results indicate that the combined effects of fire and global environmental changes can exceed their effects in isolation, thereby creating unexpected feedbacks to soil greenhouse gas emissions. These findings highlight the need to further explore the impacts of ecological disturbances on ecosystem functioning in the context of global change if we wish to be able to model future soil greenhouse gas emissions with greater confidence.     

Seasonal Response of Grasslands to Climate Change on the Tibetan Plateau

Background

Monitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate.

Methodology/Principal Findings

Grassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity.

Conclusions/Significance

Shortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.     

近30年新疆植被生长异常值时空变化及驱动因子

作为陆地生态系统的主体,植被的时空变化深刻地影响着景观格局和生态功能,深入理解植被动态及其对气候变化的响应,对于提高对生态过程的认识、加强生态管理具有重要意义。在一致性检验的基础上,利用中分辨率成像光谱仪(moderateresolution imaging Spectroradiometer,MODIS)的归一化植被指数(normalized Difference Vegetation Index,NDVI)数据集将新疆地区全球检测与模型研究组(Global Inventory Modeling and Mapping Studies,GIMMS)开发的NDVI数据集的时间序列拓展到2012年,探讨了生长季和各季节植被绿度、气候异常值的动态变化,分析了植被对气候变化的响应。研究结果显示,区域尺度和像元尺度GIMMS与MODIS NDVI之间的一致性较强。1982—2012年,研究区域生长季和各季节植被绿度呈显著增加趋势,但生长季存在明显阶段性:1998年前后分别呈显著增加和显著减少,夏季与秋季与生长季类似,而春季则不存在变化趋势的逆转。NDVI呈正异常值的面积比例与区域尺度NDVI的变化趋势一致;极端异常值、较大异常值多呈明显减少趋势,而一般异常值多呈增加趋势,NDVI的变化倾向于逐渐平稳。区域变暖趋势显著,降水量略有增加,潜在蒸散发显著提高,而湿润指数变化不明显。气温、潜在蒸散发主要在春季、秋季促进植被生长,而夏季降水量、湿润指数对植被生长的调节作用更为突出。     

Dynamic Modelling of Northeast China Transect Responses to Global Change-A Regional Vegetation Model Driven by Remote Sensing Information

A remote sensing driven dynamic simulation model was developed for terrestrial ecosystems. The model was encoded in C language under the environment of SPAMOD, a spatial simulation tool developed under MS Windows. The model was applied to Northeast China Transect to simulate the dynamics of green and non-green biomass of 12 vegetation categories as well as soil water of 3 layers. The green biomass was converted to normalized difference vegetation index (NDVI) of AVHRR remote sensing, and compared with the observed NDVI from 1986 to 1990. The model was also compared with ground measurements of biomass and productivity along the transect. Ambient CO2 concentration, monthly mean air temperature and monthly precipitation were regarded as the three basic driving variables for global change study. The model also included the effects of temperature and precipitation on sunshine fracti6n, relative humidity, radiation, soil water and eventually plant growth. For each CO2 and climatic scenario, the model was run for an equilibrium solution. The results indicated that the natural vegetation of the transect was very sensitive to variation of temperature and CO2 concentration. With CO2 remained unchanged and temperature increased by 4 CE, the induced increase in evapotranspiration could reduce the average biomass and net primary productivity (NPP) over the whole transect by 32.1% and 41.9 % respectively. In contrast, a 20 % increase in precipitation alone could lead to an increase of the average biomass and NPP by 8.1% and 13.4% respectively. Under the present climatic conditions, CO2 doubling could increase the average biomass and NPP by 12.2% and 17.1% respectively. Because of compensation between the positive effects of CO2 and precipitation increase and the negative effect of temperature increase, a comprehensive interaction among CO2 doubling, a 20% increase of precipitation and a 4 ℃ increase of temperature altogether can lead to approximately a 2% reduction in the biomass and NPP of the natural vegetation over the whole transect.     

2000—2019年武夷山亚高山草甸对气候因子的响应及其时滞效应

亚高山草甸对气候变化十分敏感,但目前缺少气候因子对亚热带地区亚高山草甸影响的相关研究,且光学遥感数据对该地区草地信息的提取仍存在一定的挑战。本研究基于MOD13Q1植被指数产品中的归一化植被指数(NDVI)数据集,并结合气象数据,分析2000—2019年间武夷山国家公园黄岗山顶的亚高山草甸的生长变化及其对气候因子的响应和时滞效应。结果表明: 2000—2019年,夏季NDVI呈不显著增加趋势,整个生长季、春季和秋季NDVI均呈极显著增加趋势。NDVI的增加主要受温度增加(0.026 ℃·a^-1)的影响,其中春、秋季温度的增加对草地生长的影响显著高于夏季和整个生长季。生长季NDVI对降水的变化十分敏感,说明即使在降水充沛的亚热带地区,亚高山草甸的生长仍然受到降水的较大影响。不同生长时段温度和降水对草甸NDVI的滞后影响程度不同,温度对亚高山草甸生长的滞后影响为0～1个月,降水对草甸生长的滞后性影响为2～3个月。     

基于遥感与实地调查对潜在可造林区乔木林和灌草地的比较

气候变化引起祁连山东部地区可适植被类型改变,探究植被类型转换的效果对生态环境可持续发展十分重要,但其转换方式及效果仍有待研究,此外传统植被调查的方法有诸多局限性,不能满足大尺度持续的监测,而遥感监测可以弥补这一劣势。基于遥感和样地调查以祁连山生态交错区甘沟小流域为研究地点,对原有灌草地和植树造林的乔木林进行比较,探究二者土壤理化性质、草本植物多样性及植被归一化指数（NDVI）,增强植被指数（EVI）,植被水分指数（NDMI）,水分胁迫指数（MSI）,叶绿素红外指数（CI）,陆地叶绿素指数（MTCI）的差异。结果表明仅有水分相关指标有显著性差异,其中造林造成浅层土壤水分显著降低（P<0.01）,4-5月份MSI和NDMI造林区植被水分高于灌草地（P<0.01）,7-8月份两种植被类型水分指数以及其余指数无显著性差异,另外造林后的土壤有机质出现了轻微下降（P>0.05）。遥感指数和样地调查指标相关性分析中,土壤有机质和Shannon多样性指数与CI成正相关（P<0.05）,植被覆盖度与NDMI成负相关（P<0.05）,由于覆盖度较低的灌草地EVI和NDVI被高估,覆盖度和EVI与NDVI相关性不显著。综合遥感指数和实地调查分析,短时间造林时间内乔木林牺牲了部分土壤水分,提高了植被盖度,且目前造林并未对当地环境产生胁迫,但对生态环境的改善并不明显。基于遥感和样地调查揭示了潜在植被类型转换区原有灌草地和植树造林区的差异,并探讨遥感在小尺度范围内植被监测上的适用性,为植被建设和遥感监测植被状况提供借鉴。     

基于ICEEMDAN方法的黄土高原植被覆盖变化及其对气候变化的响应

地理数据和遥感数据的长期序列中包含噪声和周期性波动信息。本研究基于ICEEMDAN方法对黄土高原1982—2015年归一化植被指数(NDVI)、降雨和温度进行逐像元分解,分解后得到的残差项减少了原始数据中的噪声和周期性波动,并利用残差项研究NDVI的变化趋势以及NDVI与气候因子之间的关系。结果表明: 1982—2015年,黄土高原NDVI以上升为主,残差项NDVI变化趋势的显著性(95.9%)大于原始NDVI变化趋势的显著性(72.3%),并且存在一定的空间差异性。温度和降雨的变化可以在很大程度上解释植被覆盖的变化。其中,温度与黄土高原NDVI之间呈极显著正相关的区域占83.7%,极显著负相关区域占13.9%;降雨与黄土高原NDVI之间呈极显著正相关的区域占54.4%,极显著负相关区域占37.2%。黄土高原植被对气候变化的响应存在明显的空间差异性,不同气候因子对不同植被覆盖类型的影响程度不同。总体上,黄土高原生长季不同植被与温度之间的相关性强于降水,温度是影响黄土高原植被覆盖变化的主要因素。     

近30年河北大海陀自然保护区山地草甸植被(NDVI)变化及其对气候的响应

河北大海陀自然保护区地处我国暖温带落叶阔叶林区,草甸植被多处于山地顶部,对外界干扰敏感。为了研究该地区的草甸植被变化以及其对气候变化的响应,收集了该地区近30年的TM遥感影像资料,1980—2015年的气候数据,包括年平均气温、7月份平均气温、1月份平均气温、年降水量、6—8月平均降水量等多个气候指标,以及大海陀自然保护区及其周边地区的地形数据等,用滑动平均法、M-K检验法、相关分析法及偏相关分析法等方法分析了大海陀自然保护区草甸植被NDVI及其与气候响应。结果表明:(1)近30年来,大海陀自然保护区草甸植被NDVI呈先上升后下降的趋势,在2004年NDVI达到最高,随后逐渐下降。(2)大海陀自然保护区草甸区域的年降水量变化整体表现为波动循环的趋势,总体略有上升,但没有达到显著水平;年均温变化表现为上升趋势,且达到了极显著水平,该地区的气温上升趋势主要由以1月为主的冬季温度升高而引起。(3)草甸植被NDVI与年均温成显著的负相关关系,与年降水量的关系不明显。     

白洋淀湿地生态系统水分条件遥感监测方法

湿地水文条件对湿地生态系统结构和功能起到关键作用。利用遥感获取与湿地水分条件直接相关的生物物理变量,包括归一化植被指数（NDVI）和地表温度,探讨监测湿地挺水植物缺水状况的可能性,并探讨了建立湿地水分遥感监测的新方法。回归分析表明,对于同一挺水植物而言,在湿地旱化的条件下,由于植物的蒸腾作用的差异,在植被生长状况（NDVI）相同的情况下,地势较高处植物的冠层温度亦较高;在生长处高度相同的情况下,植被覆盖度高（NDVI值高）的地方,植物的冠层温度较低。这说明可以通过地表温度和NDVI来监测挺水植物的缺水程度。     

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。     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.     

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.     

基于MODIS NDVI的长江中游区域植被动态及与气候因子的关系

基于1999-2015年的MODIS NDVI时间序列遥感数据，应用趋势分析、变异系数、重标极差分析和偏相关分析等方法，分析了长江中游的植被时空变化特征及其与气象因子的关系。结果表明，长江中游地区NDVI均值总体上呈上升趋势（从0.72增加到0.80）。从空间分布来看，NDVI低值区域（0.1-0.5）占1.40%，高值区域（>0.7）占87.15%；NDVI空间格局呈"西高东低、北高南低"的分布特征，低值区域表现为以三省省会城市为中心向外辐射。Hurst指数显示，研究区大部分区域（60.54%）的NDVI变化趋势具有不确定性，持续性改善区域（34.78%）主要分布在西部山地区，持续性退化区域（3.26%）主要分布在人类活动频繁的较发达城市区域。在年际尺度上，研究区NDVI与各气象因子关系均不显著；月际尺度上，NDVI与降水、相对湿度和日照时数显著相关，降水和日照时数有明显的时滞性。区域内NDVI动态趋势以不确定性发展为主，城市群周边NDVI呈现持续退化的区域应该引起关注。     

基于遥感影像的城市土地利用生态环境效应研究——以城市热环境和植被指数为例

城市化过程中,农村的土壤、水面以及植被等土地覆被类型逐渐减少,取而代之的是由沥青、水泥以及金属等组成的不透水表面,这个过程导致地表水分蒸腾减少、径流加速、显热的存储和传输增加以及水质降低等一系列生态环境效应,其中最明显的两个特征就是土地覆被的植被减少、城市热岛的出现.而城市土地利用类型及其空间结构的生态环境效应同时又是城市生态学中的关键问题,其研究对优化城市功能分区和城市规划管理以及城市可持续发展等都具有重要意义.以上海市为例,采用Landsat7的ETM＋为基本数据源,首先定量反演了每个像元内的陆地表面温度（LST）和植被指数（NDVI）,然后利用GIS中的空间分析功能,将由于城市土地覆被所形成的生态环境效应综合到土地利用的图斑中来,按照这个思路对城市土地利用的生态环境效应进行研究.分析LST、NDVI在不同土地利用类型之间的差异以及二者之间的定量关系,并引入多样性指数（SHDI）,讨论了不同土地利用的空间组合下,LST和NDVI的空间差异及相互关系.研究结果显示：LST和NDVI具有明显的相关性,LST大的区域对应NDVI一般都较小,反之亦然;中心城市LST表现出热岛效应,而NDVI则为低谷效应.通过Tamhance T2 post-hoc多重比较发现,LST以及NDVI在两两土地利用类型之间的差异不同.从土地利用斑块和类型两种尺度水平上建立了LST和NDVI的定量关系,二者具有明显负相关的线性关系,但在不同土地利用类型上二者关系并不同.其中工业仓储、交通用地与公园绿地、农业用地差异最为显著.它们和SHDI之间的关系揭示,LST与土地利用多样性具有正相关关系,而NDVI则与SHDI呈负相关关系,SHDI越大的地区,LST越大,而NDVI越小.由此,可以将LST、NDVI和SHDI作为三个基本指标,来定量评价城市土地利用类型、结构对生态环境的影响,以此作为城市功能分区中生态环境影响评价的参考.也为高性价比的中等分辨率遥感数据与GIS空间分析方法结合在城市规划中的应用提供了一种新的思路.     

Global ecosystems and fire: Multi‐model assessment of fire‐induced tree‐cover and carbon storage reduction

In this study, we use simulations from seven global vegetation models to provide the first multi‐model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001–2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire‐induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state‐of‐the‐art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.     

基于无人机低空遥感的荒漠植被覆盖度与归一化植被指数验证及其对水热梯度的响应

为了验证在荒漠地区MODIS-NDVI产品的精度以及为在气候变化背景下荒漠草地的科学管理提供依据,本文利用无人机低空遥感研究了干旱荒漠地区植被覆盖度(FVC)和归一化植被指数(NDVI)对水、热梯度的响应规律。在内蒙古阿拉善荒漠地区的100个样点采用GreenSeeker手持光谱仪获得NDVI值(NDVI_R),通过MODIS-NDVI数据产品提取每个样点的NDVI(NDVI_M),借助NDVI_R验证NDVI_M的精确度;通过无人机遥感手段获得每个采样点的FVC(FVC_U),利用像元二分模型反演每个样点的FVC(FVC_M),借助FVC_U验证FVC_M的精确度;并结合气象数据探讨基于无人机低空遥感的荒漠地区FVC和NDVI对水热梯度的响应。结果表明: MODIS-NDVI数据产品能够反映阿拉善地区的NDVI,精确度为84.2%,但比真实值高15.7%;FVC_M能够反映阿拉善地区的FVC状况,精确度为83.1%,但比真实值低14.8%;不同采集方式获得的NDVI受气象因子的影响程度不同,NDVI不仅受气温和降雨的影响,也受地温、蒸发量以及两者相互作用的影响,由于受大气影响程度不同, NDVI_M受地温、蒸发量、降水量的影响比NDVI_R大,NDVI_R受气温的影响比NDVI_M大。在阿拉善地区研究FVC随水热梯度的变化不仅要考虑降水量和气温,还应考虑蒸发量、地温以及气象因子之间相互作用的影响,其中,气温与降雨、蒸发量与地温以及气温与蒸发量之间相互作用对FVC_U的影响较大。