Divergent phenological response to hydroclimate variability in forested mountain watersheds

Mountain watersheds are primary sources of freshwater, carbon sequestration, and other ecosystem services. There is significant interest in the effects of climate change and variability on these processes over short to long time scales. Much of the impact of hydroclimate variability in forest ecosystems is manifested in vegetation dynamics in space and time. In steep terrain, leaf phenology responds to topoclimate in complex ways, and can produce specific and measurable shifts in landscape forest patterns. The onset of spring is usually delayed at a specific rate with increasing elevation (often called Hopkins' Law; Hopkins, 1918), reflecting the dominant controls of temperature on greenup timing. Contrary with greenup, leaf senescence shows inconsistent trends along elevation gradients. Here, we present mechanisms and an explanation for this variability and its significance for ecosystem patterns and services in response to climate. We use moderate‐resolution imaging spectro‐radiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data to derive landscape‐induced phenological patterns over topoclimate gradients in a humid temperate broadleaf forest in southern Appalachians. These phenological patterns are validated with different sets of field observations. Our data demonstrate that divergent behavior of leaf senescence with elevation is closely related to late growing season hydroclimate variability in temperature and water balance patterns. Specifically, a drier late growing season is associated with earlier leaf senescence at low elevation than at middle elevation. The effect of drought stress on vegetation senescence timing also leads to tighter coupling between growing season length and ecosystem water use estimated from observed precipitation and runoff generation. This study indicates increased late growing season drought may be leading to divergent ecosystem response between high and low elevation forests. Landscape‐induced phenological patterns are easily observed over wide areas and may be used as a unique diagnostic for sources of ecosystem vulnerability and sensitivity to hydroclimate change.     

藏北高原植被物候时空动态变化的遥感监测研究

利用遥感数据提取的植被物候格局及时空变化特征能很好地反映区域尺度上植被对全球变化的响应。目前关于青藏高原地区植被物候的少量报道基本上是基于物候站点的观测记录展开分析的。该文基于非对称高斯拟合算法重建了藏北高原2001-2010年的MODIS EVI (增强型植被指数)时间序列影像, 然后利用动态阈值法提取整个藏北高原2001-2010年植被覆盖的重要物候信息, 包括植被返青期、枯黄期与生长季长度, 分析了植被物候10年间平均状况的空间分异特征以及年际变化情况, 并结合站点观测记录分析了气温和降水对植被物候变化的影响, 结果表明: (1)藏北高原植被返青期在空间上表现出从东南到西北逐渐推迟的水平地带性与东南高山峡谷区的垂直地带性相结合的特征, 近60%区域的植被返青期提前, 特别是高山地区; (2)植被枯黄期的年际变化不太明显, 大部分地区都表现为自然的年际波动; (3)生长季长度的时空变化特征由植被返青期和枯黄期二者决定, 但主要受返青期提前影响, 大部分地区生长季长度延长; (4)研究区内不同气候区划植被物候的年际变化以那曲高山谷地亚寒带半湿润区和青南高原亚寒带半干旱区的植被返青期提前和生长季延长程度最为明显; (5)基于气象台站数据分析气候变化对物候的影响发现, 返青期提前及生长季延长主要受气温升高的影响, 与降水的关系尚不明确。     

日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_(GPP))为第63天,生长季结束时间(EOS_(GPP))为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_(GPP)31天,植被指数EOS滞后EOS_(GPP)10—17天。虽然基于3种遥感指数估算的春季和秋季物候都滞后于通量GPP的物候期,但是卫星SIF的物候信息能够更好地捕捉常绿针叶林的生长阶段。同时,春季温度是影响森林生长季开始时间的最重要因素;秋季水分和辐射是影响生长季结束时间的关键因素。由此可见,SIF估算的亚热带常绿针叶林的春季和秋季物候的滞后时间要短于传统植被指数,能更好地追踪常绿林光合作用的季节性,为深入研究陆地生态系统碳循环及其对气候变化的响应提供重要的基础。     

祁连山不同植被类型的物候变化及其对气候的响应

基于1982—2006年GIMMS NDVI和2000—2014年MODIS NDVI遥感数据,利用double logistic拟合方法提取了1982—2014年祁连山区不同植被的生长季始期、生长季末期和生长季长度3个重要的物候参数,分析了不同植被物候期的时间变化趋势、空间分异特征及对气候因子的响应。结果表明:(1)祁连山区不同植被的生长季始期和生长季末期随年际变化表现出波动提前或推迟,其中沼泽植被的变化波动最大;草甸植被、灌丛植被、阔叶林植被和栽培植被生长季长度出现延长趋势;(2)祁连山区植被生长季始期集中在5月初,其中阔叶林植被生长季开始最早,荒漠植被生长季开始最晚,植被生长季末期集中在9月,栽培植被生长季结束较早,荒漠植被、沼泽植被生长季结束较晚,植被生长季长度集中在110—140 d,其中阔叶林植被、针叶林植被生长季长度较长,而荒漠植被、高山植被生长季长度较短;(3)祁连山植被物候期变化趋势的空间分布表明植被生长季始期、生长季末期主要表现为提前不明显和推迟不明显,生长季长度主要表现为缩短不明显和延长不明显;(4)物候要素与气候要素相关性表明前期温度的积累有利于植被的开始生长,但当年3月的降水量对植被生长季始期同样有重要作用,不同植被生长季末期与8月、9月温度相关性较大,而与10月、11月降水的相关性较大。     

Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data

Recent studies using both field measurements and satellite-derived-vegetation indices have demonstrated that global warming is influencing vegetation growth and phenology. To accurately predict the future response of vegetation to climate variation, a thorough understanding of vegetation phenological cycles and their relationship to temperature and precipitation is required. In this paper, vegetation phenological transition dates identified using data from the moderate-resolution imaging spectroradiometer (MODIS) in 2001 are linked with MODIS land surface temperature (LST) data from the northern hemisphere between 35°N and 70°N. The results show well-defined patterns dependent on latitude, in which vegetation greenup gradually migrates northward starting in March, and dormancy spreads southward from late September. Among natural vegetation land-cover types, the growing-season length for forests is strongly correlated with variation in mean annual LST. For urban areas, the onset of greenup is 4–9 days earlier on average, and the onset of dormancy is about 2–16 days later, relative to adjacent natural vegetation. This difference (especially for urban vs. forests) is apparently related to urban heat island effects that result in both the average spring temperature and the mean annual temperature in urban areas being about 1–3°C higher relative to rural areas. The results also indicate that urban heat island effects on vegetation phenology are stronger in North America than in Europe and Asia. Finally, the onset of forest greenup at continental scales can be effectively described using a thermal time-chilling model, which can be used to infer the delay or advance of greenup onset in relation to climatic warming at global scale.     

Seasonal Foliage Changes in the Eastern Amazon Basin Detected from Landsat Thematic Mapper Satellite Images1

Seasonal changes in tropical forests are difficult to measure from the ground, especially in areas of high species diversity and low phenological synchrony. Satellite images, which integrate individual tree canopies and cover a large spatial extent, facilitate tests for stand-level canopy phenology. Variability in near-infrated radiance (TM bands 4 and 5) of several distinct vegetation types was used to detect seasonal changes in a series of three Landsat Thematic Mapper (TM) images from the wet season to the dry season in Marabá, Brazil (eastern Amazon basin). Despite different atmospheric and instrumental conditions among the images, spectral changes were distinguishable. A phenological process (leaf aging, leaf drop, water stress) was determined from the spectral changes for each vegetation type. Changes in the spectral properties suggest that during the dry season, upland terra firme forest increased the rate of leaf exchange and some riparian vegetation was deciduous. Terra firme forest that had been altered by penetration of fires from nearby pastures increased in leaf biomass over a 14-month period. This study shows that a time series of images can provide information on temporal changes in primary vegetation and guide field studies to investigate seasonal changes that may not be detectable from the ground.     

Greater phenological sensitivity to temperature on higher Scottish mountains: new insights from remote sensing

Mountain plants are considered among the species most vulnerable to climate change, especially at high latitudes where there is little potential for poleward or uphill dispersal. Satellite monitoring can reveal spatiotemporal variation in vegetation activity, offering a largely unexploited potential for studying responses of montane ecosystems to temperature and predicting phenological shifts driven by climate change. Here, a novel remote‐sensing phenology approach is developed that advances existing techniques by considering variation in vegetation activity across the whole year, rather than just focusing on event dates (e.g. start and end of season). Time series of two vegetation indices (VI), normalized difference VI (NDVI) and enhanced VI (EVI) were obtained from the moderate resolution imaging spectroradiometer MODIS satellite for 2786 Scottish mountain summits (600–1344 m elevation) in the years 2000–2011. NDVI and EVI time series were temporally interpolated to derive values on the first day of each month, for comparison with gridded monthly temperatures from the preceding period. These were regressed against temperature in the previous months, elevation and their interaction, showing significant variation in temperature sensitivity between months. Warm years were associated with high NDVI and EVI in spring and summer, whereas there was little effect of temperature in autumn and a negative effect in winter. Elevation was shown to mediate phenological change via a magnification of temperature responses on the highest mountains. Together, these predict that climate change will drive substantial changes in mountain summit phenology, especially by advancing spring growth at high elevations. The phenological plasticity underlying these temperature responses may allow long‐lived alpine plants to acclimate to warmer temperatures. Conversely, longer growing seasons may facilitate colonization and competitive exclusion by species currently restricted to lower elevations. In either case, these results show previously unreported seasonal and elevational variation in the temperature sensitivity of mountain vegetation activity.     

Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation

Plant phenology has gained new importance in the context of global change research, stimulating the development of novel technologies for phenological observations. Regular digital cameras have been effectively used as three-channel imaging sensors, providing measures of leaf color change or phenological shifts in plants. We monitored a species rich Brazilian cerrado savanna to assess the reliability of digital images to detect leaf-changing patterns. Analysis was conducted by extracting color information from selected parts of the image named regions of interest (ROIs). We aimed to answer the following questions: (i) Do digital cameras capture leaf changes in cerrado savanna vegetation? (ii) Can we detect differences in phenological changes among species crowns and the cerrado community? (iii) Is the greening pattern detected for each species by digital camera validated by our on-the-ground leafing phenology (direct observation of tree leaf changes)? We analyzed daily sequences of five images per hour, taken from 6:00 to 18:00 h, recorded during the cerrado main leaf flushing season. We defined 24 ROIs in the original digital image, including total or partial regions and crowns of six plant species. Our results indicated that: (i) for the studied period, single plant species ROIs were more sensitive to changes in relative green values than the community ROIs, (ii) three leaf strategies could be depicted from the species' ROI patterns of green color change, and (iii) the greening patterns and leaf functional groups were validated by our on-the-ground phenology. We concluded that digital cameras are reliable tools to monitor high diverse tropical seasonal vegetation and it is sensitive to inter-species differences of leafing patterns.     

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。     

Codominant water control on global interannual variability and trends in land surface phenology and greenness

Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus, we assessed the performance of a new developed phenology module within the LPJmL (Lund–Potsdam–Jena managed Lands) DGVM with a comprehensive ensemble of three satellite data sets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on interannual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season interannual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming‐induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, interannual variability and trends are dominantly controlled by water availability and land‐use and land‐cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated with a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a codominant control for start of growing season and peak greenness trends at the global scale.     

Is the grass always greener? Land surface phenology reveals differences in peak and season‐long vegetation productivity responses to climate and management

Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual‐resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season‐long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season‐long productivity. Annual precipitation and temperature had strong explanatory power for productivity‐related phenology measures but predicted date‐based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing‐season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land‐use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.     

Landscape controls on the timing of spring,autumn, and growing season length in mid‐Atlantic forests

The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field‐based and remote‐sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium‐resolution remote sensing data, organized by day of year, to explore the influence of climate‐related landscape factors on the timing of spring and autumn leaf‐area trajectories in mid‐Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape‐scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.     

基于物候特征的盐渍化信息数据挖掘研究

盐渍化是影响植被和作物长势的重要因素,精确反演盐渍化的时空分布信息至关重要。基于MOD13A1-NDVI数据反演生长季开始日期(SOS)、生长季结束日期(EOS)、生长季长度(LEN)等物候参数和计算出能高精度反演盐渍化空间分布的多种植被指数、盐分指数、地形指数、干旱指数等参数后作为BP-ANN人工神经网络的输入因子来反演盐渍化信息,同时按照植被类型和地貌类型进行分区来反演盐渍化信息,以探讨盐渍化受植被和地貌类型的影响。主要结论如下:(1)盐渍化的形成受多种因素的影响,与物候参数大多呈非线性关系,不能单纯的以某拟合公式来进行表达,需要借助人工神经网络超强的非线性拟合能力来反演盐渍化信息。(2)通过深入挖掘植被物候信息,在融入物候参数后的反演精度显著提高。可决系数R2从0.68(非物候参数)增加到0.79(包括物候参数),但是需要加入地形、影像数据和土壤水分等方面的信息来更加精确的反演盐渍化信息。生物累积量指标LSI(Large seasonal integral)和SSI(Small seasonal integral)能够很好的表征盐渍化的信息。(3)划分植被类型后的盐渍化提取精度进一步提高,可决系数R~2达到了0.88。(4)以地貌特征作为类型分区后,反演结果的R~2达到了0.85,精度较高,比以植被类型作为分区的精度略小。高程较低区域的盐渍化现象普遍较重,盐渍化程度受到地形和地貌因素的影响显著。(5)农用地区域多为非盐渍化和轻度盐渍化地,稀疏植被区多为重盐渍化地。研究区的非盐渍化和轻盐渍化地、中盐渍化地和重度盐渍化地比例分别为53.42%,13.71%,32.87%。以上的研究结果提出了一种融合物候信息和非物候参数来反演盐渍化信息的方法,进行深入的协同植被物候监测盐渍化信息方面的数据挖掘,在融入了物候参数后,盐渍化的预测精度显著提高。     

北京市植物物候对热岛效应的响应

都市的快速发展致使城市热岛效应日渐加剧。城市绿化对缓解热岛效应有一定的作用,但同时其物候也受到了影响。本文基于遥感影像数据,通过对照北京市热岛区与非热岛区、不同热岛强度等级的植物物候差别,研究热岛效应对植物物候的影响。采用Landsat 8影像对北京市地表温度进行反演,结合空间分析进行热岛效应分区分级识别;通过MOD13A1的归一化植被指数(NDVI)数据,采用Dallimer平均值法和动态阈值法提取植被生长季始期(SOG)、生长季末期(EOG)、生长季长度(LOG)等重要植被物候参数,研究植被物候在热岛区与非热岛区、不同热岛强度等级之间的差异。结果表明:北京市夏季与冬季相比,热岛效应更为显著;利用Dallimer平均值法提取的北京市热岛区SOG比非热岛区提前4 d,EOG延迟9 d,LOG延长13 d;利用动态阈值法提取的SOG提早10 d,EOG推迟4d,LOG延长14 d,动态阈值法提取的物候信息与观测的物候信息更为接近;随着热岛强度等级提高,SOG提前,EOG推迟,LOG延长。本研究丰富了我国华北地区植被物候对热岛效应的响应机制,同时对研究全球变暖对生态系统的影响具有一定价值。     

Differences in leaf phenology between juvenile and adult individuals of two tree species in a seasonally dry tropical woodland

In temperate forests, juvenile trees anticipate leaf phenology compared to adults, thus avoiding shading and herbivory. This is also expected to occur in seasonal tropical forests due to intense herbivory and shading during the rainy season; however, the anticipation of leaf phenology by juveniles in seasonal tropical forests has yet to be demonstrated. Stem‐succulent species are expected to be prone to juvenile phenological anticipation because these species are able to use water stored in their stems for leaf flushing in the dry season. We investigated this hypothesis by comparing leaf phenology (bud break, leaf expansion) of juveniles and adults of two species with contrasting wood densities in the transition between dry and rainy seasons in a tropical dry woodland. We also investigated the level of light limitation that juveniles experience in the rainy season. Both species exhibited bud break during the dry season, but only expanded their leaves with the occurrence of the first rains. In general, the stem‐succulent species had a more precocious bud break; however, anticipation by juveniles occurred only in the species with more dense wood. Canopy openness was lower than in temperate deciduous forests, but the fact that the full expansion of leaves occurred only with rainfall indicates that bud break in anticipation of canopy closure contributes only to keeping leaf photosynthetic balance from going negative, and not to higher carbon gain. The importance of anticipated budding for escaping herbivory remains an alternative explanation in need of investigation.     

Phenology and climate relationships in aspen (Populus tremuloides Michx.) forest and woodland communities of southwestern Colorado

Trembling aspen (Populus tremuloides Michx.) occurs over wide geographical, latitudinal, elevational, and environmental gradients, making it a favorable candidate for a study of phenology and climate relationships. Aspen forests and woodlands provide numerous ecosystem services, such as high primary productivity and biodiversity, retention and storage of environmental variables (precipitation, temperature, snow–water equivalent) that affect the spring and fall phenology of the aspen woodland communities of southwestern Colorado. We assessed the land surface phenology of aspen woodlands using two phenology indices, start of season time (SOST) and end of season time (EOST), from the U.S. Geological Survey (USGS) database of conterminous U.S. phenological indicators over an 11-year time period (2001–2011). These indicators were developed with 250 m resolution remotely sensed data from the Moderate Resolution Imaging Spectroradiometer processed to highlight vegetation response. We compiled data on SOST, EOST, elevation, precipitation, air temperature, and snow water equivalent (SWE) for selected sites having more than 80% cover by aspen woodland communities. In the 11-year time frame of our study, EOST had significant positive correlation with minimum fall temperature and significant negative correlation with fall precipitation. SOST had a significant positive correlation with spring SWE and spring maximum temperature.     

黄土高原植被物候变化及其对季节性气候变化的响应

受气候变化影响,全球范围内植被物候发生了显著变化,而目前针对不同植被分区类型下（荒漠草原区、典型草原区、森林草原区、落叶栎林区、落叶栎林亚区）植被物候变化及其对季节性气候变化响应的研究尚少。因此基于MODIS遥感归一化差值植被指数（MODIS NDVI：MOD13Q1）数据、中国植被区划数据及135个气象站点插值数据,利用Sen''s斜率估计、Hurst指数和高阶偏相关分析等方法,研究黄土高原2001-2018年植被物侯变化及其对季节性气候变化的响应。结果表明：（1）黄土高原植被生长季始期（SOS,Start of Growing Season）主要集中在第96-144天,子植被分区由西北向东南方向,逐渐呈现提前趋势,71.0%的像元植被SOS整体提前0-2 d/10a （α=0.05）,且在未来一段时间66%的像元植被SOS继续呈现提前趋势;植被生长季末期（EOS,End of Growing Season）主要集中在第288-304天,各子植被分区植被EOS变化基本保持一致,87.6％的像元植被EOS整体延迟0-3 d/10a （α=0.05）,且在未来一段时间有80%的像元植被EOS继续呈现推迟趋势。（2）黄土高原植被SOS主要受各季节温度的影响;当年春季降水导致植被SOS提前,主要分布在黄土高原中部;上年夏季和上年秋季降水增加会导致植被SOS推迟;当年春季、上年秋季和年初冬季的温度升高均会导致植被SOS提前;各子植被分区植被SOS对不同季节降水的响应存在差异,而对不同季节温度的响应具有一致性。（3）黄土高原植被EOS主要受各季节降水和秋季温度的影响;不同季节降水增加均会导致大部分植被EOS推迟;当年秋季温度导致整体区域植被EOS推迟,且各子植被区植被EOS对当年秋季温度响应具有一致性。该研究可为大尺度植被物候影响因素提供新的认识,也为植被适应未来气候变化提供借鉴。     

基于植被/温度特征的黄土高原地表水分季节变化

地表水分是监测土地退化的一个重要指标,是气候、水文、生态、农业等领域的主要参数。选择陕北黄土高原地区作为研究区域,首先采用基于植被覆盖特征的植被状态指数（Vegetation Condition Index,简称VCI）和基于地表温度特征（Land Surface Temperature,简称Ts）的温度状态指数（Temperature Condition Index,简称TCI）分别评价了区域地表水分状况的季节变化。在此基础上分析了植被指数与地表温度特征线性关系的季节变化规律,计算了基于两者经验关系的地表干燥度指数（Temperature Vegetation Dryness Index,TVDI）。该指数对Ts／NDVI特征空间的生态特征的解释,对土壤和作物的水分含量具有综合的指示意义。文中利用该指数综合评价了研究区域地表水分状况的时空分布差异,进一步对VCI、TCI与TVDI相关关系的季节变化进行比较分析,并结合气候因子进行了相关验证,从而对不同指数的应用范围做出判定。研究结果表明,单独采用TCI或VCI表征地表水分会受到明显的季节影响,而TVDI能在不同季节综合体现植被覆盖和地表温度特征对地表水分的影响,从而能较好的反映区域地表水分状况的时空变化特征。各区域的TVDI值季节分布上皆为4—7月份高于10-翌年1月份,但各区TVDI值的季节变化则存在显著不同,而各流域内部TVDI值的空间变异性也存在季节差异,其中在10月份较为显著。     

基于多种遥感植被指数、叶绿素荧光与CO2通量数据的温带针阔混交林物候特征对比分析

植被物候学作为研究植被与环境条件相互作用的科学,在全球气候变化的大背景下已成为国际热点研究领域,其中森林植被在调节全球碳平衡、维护全球气候稳定的过程中有着至关重要的作用。随着遥感技术的发展,多种遥感指数被应用到森林植被物候研究中,其中以MODIS NDVI和EVI应用最为广泛,而叶绿素荧光(SIF)作为植被光合作用的"探针"也被广泛应用于森林植被物候研究中。为了探究3种指数在森林植被物候研究中的差异与特性,本文以长白山温带红松阔叶林通量观测站为研究区域,采用模型拟合结合动态阈值法提取2007—2013森林物候特征参数,并使用通量数据(总初级生产力GPP)进行验证。结果表明:NDVI与EVI、SIF相比,表现为生长季开始时间与结束时间的明显提前和滞后,与GPP数据偏差较大,且夏季生长季峰期曲线形态过宽且平坦,无法较好反映生长季变化特征;EVI相较于NDVI有所改善,整体变化趋势与SIF、GPP基本吻合,但依然存在秋季衰减时间稍迟于SIF与GPP的问题;SIF虽然存在夏季骤降现象,但依然与GPP数据一致性最好,可以较好反映出森林植被季节变化特征。SIF数据与植被光合作用的紧密关联使其在植被物候研究中具有优于植被指数的准确性,并随着遥感平台的增加和反演方法的改善,将会在多尺度、多类型的植被物候监测中发挥更加重要的作用。     

新疆植被物候时空变化特征

基于MODIS-NDVI数据,提取新疆2001—2016年典型植被物候期,分析新疆不同生态分区的山地-绿洲系统植被物候期的时空演变趋势和空间分异特征,并结合同期气象数据,探讨植被物候与气候变化的响应关系。结论为:(1)新疆植被物候具有明显的纬向分布和垂直地带性分布特征,海拔在物候的地域分异中扮演着重要作用。新疆植被生长季开始时间(Start of season,SOS)集中于3月中旬至5月上旬,生长季结束时间(End of season,EOS)集中于10月中旬至12月下旬。(2)与全球大背景下典型植被物候特征变化趋势相反,新疆植被SOS呈推迟趋势,推迟幅度为1.9d/10a;EOS呈提前趋势,提前幅度为3.66d/10a;生长季长度(Length of season,LEN)呈缩短趋势,缩短幅度为5.6d/10a。除东疆地区外,全疆及不同分区均呈现出绿洲及平原SOS较早,山地区域较迟;全疆及不同分区均呈现出山地EOS结束较早,绿洲结束较迟;除东疆地区外,全疆及不同分区的LEN均为绿洲及平原区域山地,同样显示出垂直地带性分布的特征。(3)通过冗余分析(Redundancy analysis,RDA)解释了物候特征与气象因子关系的绝大部分信息,生长季开始时间受春季气温、前一年冬季降水量和日照时数的显著影响。夏季和秋季降水量是新疆植被生长季结束时间的重要影响因素,在总体上受气温和日照时数的影响较小。