植物物候是随环境变化表现出的周期性节律变化的事件，对环境变化非常敏感。多数研究发现，增温改变了单个物候事件，如提前了返青期和开花期，推迟了枯黄期；特别是近期发现相对于其他物候序列而言，结实期保持相对稳定，并且物候序列持续期的反应存在等级关系。不同植物个体物候对环境变化的响应模式不同，因而依据植物个体物候很难准确预测群落物候对环境变化的响应模式，所以应该加强群落物候的地面观测研究。尽管放牧是天然草地的主要利用方式，但目前仍然缺乏放牧如何影响气候变化对物候序列影响的研究；尤其是由于研究方法和技术等限制，也缺乏未来气候变化条件下地上与地下物候同步性、物候变化非线性及其机理的研究。

Plant phenology is a periodic event with environmental change, being much sensitive to environmental change. Most of the studies have observed that warming advanced onsets of greenup and flowering, but delayed completely leaf coloring. However, fruitingset kept relative stable under temperature change compared with other phenological sequences. There were hierarchical responses of phenological sequences in duration to temperature change (i.e. warming and cooling). In particular, more attention should be paid to observation of community phenology under future climate change because the response of individual plant phenology to climate change could not predict the response of the community phenology due to different responses from different plants. Although grazing is a major land use for natural grasslands, how grazing affects the effects of climate change on plant and community phenology is still unclear. Meanwhile, few studies have been performed on the synchrony of aboveground and root phenology, nonlinear change of phenological sequences and its mechanisms due to experimental method and technology limitations under future climate change.

植被物候作为自然界规律性、周期性的现象,对自然环境尤其是气候变化有着重要的指示作用,研究其时空变化特征对陆地植被生态环境监测具有重要意义。本研究采用Savitzky-Golay滤波法重建秦岭山区2001—2018年MODIS增强植被指数时间序列影像,利用动态阈值法提取研究区春季物候信息(返青期),并对返青期多年平均值和年际变化与海拔、坡度进行相关分析。结果表明: 海拔每升高100 m,植被返青期推迟1.82 d;返青期的年际变化趋势主要集中在0~5 d·(10 a)^-1。其中,呈推迟趋势的像元主要分布在低海拔地区,呈提前趋势的像元主要分布在高海拔地区。高海拔地区返青期的年际变化比低海拔地区复杂;秦岭山区植被返青期存在南北差异。北坡植被返青期多年平均值较南坡早2.9 d,南坡植被返青期的推迟程度大于北坡。南北坡植被返青期的年际变化在低海拔地区呈推迟趋势,且南北坡相差不大,而提前趋势在中高海拔地区存在显著差异。

Vegetation phenology, a regular and periodic phenomenon in nature, is an important indicator for natural environment, especially climate change. The study of spatiotemporal variations of vegetation phenology is of great significance for monitoring the changes of terrestrial vegetation. In this study, the Savitzky-Golay (S-G) filtering method was used to reconstruct time-series MODIS enhanced vegetation index (EVI) data in the Qinling Mountains from 2001 to 2018. The dynamic threshold method was used to extract the spring phenological parameter (start of growth season, SOS). The correlation between multi-year mean SOS and interannual variation with altitude and slope was analyzed. The results showed that SOS was delayed by 1.82 d with every 100 m increase in altitude in the Qinling Mountains. The interannual change trends of SOS mainly concentrated in 0-5 d·(10 a)^-1. The pixels with delaying trend were mainly distributed in low-altitude regions, with the delaying degree being gradually decreased with the elevation. The interannual change trend of SOS in high-altitude regions was more complex than that in lower-altitude regions. The multi-year average SOS in the northern slope was approximately 2.9 d earlier than that of the southern slope, whereas the southern slope had a more significant advancing trend. The interannual change trends of SOS in both north and south slopes showed a delaying trend in low-altitude, with little difference between north and south slopes. The advancing trend in middle and high altitude was significantly different.

北半球气候变暖导致植被春季物候开始日期显著提前, 温度对春季物候的促进作用是一个过程事件而非瞬时事件, 且存在空间差异。该研究在以前研究的基础上, 进一步分析温度对植被物候的作用方式, 并探讨春季物候温度敏感性的空间特征及影响因素。利用GIMMS3g卫星植被指数产品, 采用5种方法提取1982-2009年植被春季物候, 并结合格网气象数据计算植被春季物候的温度敏感性, 着重分析自然植被春季物候温度敏感性与环境因素的关系。结果表明, 温度是北半球植被春季物候的主要制约因素, 54%的像元显示温度最大效应发生在物候开始当月和之前一个月。温度主导的春季物候的像元中, 91.3%的像元指示早春温度对物候开始的促进作用。植被春季物候的温度敏感性存在空间异质性, 随着区域环境因素的不同, 年际温度标准差、累积降水量和辐射对植被春季物候温度敏感性都具有各自或协同的调控作用。

植被物候沿城乡梯度的变化反映城市化过程对局地水热条件的调节作用。遥感技术可从区域和全球等大尺度上获取植被物候信息，从而弥补传统物候观测方法的不足。本研究以我国东北省会城市沈阳、长春、哈尔滨为例，基于MODIS NDVI数据，利用SavitzkyGolay滤波和分段高斯函数计算了各城区周边20 km内缓冲带的2种关键物候参数(生长季开始和结束日期)；分析多年平均物候沿城乡梯度的变化，以及地表温度和林地盖度对物候空间变化的影响。结果发现：距城区越近，生长季开始越早，结束越晚，变化也越明显；在城乡梯度上，生长季随春季和前一年冬季地温升高而提前开始6～31 d·℃^-1，随夏秋两季地温升高而推迟结束0.9～7.6 d·℃^-1，而部分缓冲带内林地增多也会导致类似的生长季提前开始和延后结束。

Changes of vegetation phenology along the urban-rural gradients can reflect how urbanization regulates local water and heat conditions. Remote sensing can provide vegetation phenology at large scales (e.g. regional or global), making it a great alternative to traditional observation method. Taking three provincial capital cities (Shenyang, Changchun, Harbin) in Northeast China as examples, this study examined two critical phenology parameters (start of growing season, and end of growing season) in the buffer zones within 20 km from these urban areas, which were calculated from time series MODIS NDVI images using SavitzkyGolay filtering and segmented Gaussian method. Changes of multi-year mean parameters along the urbanrural gradients in relation to land surface temperature and forest coverage were analyzed. The results show that areas closer to urban sites tend to have earlier start of growing season, later end of growing season, and greater variability. Along the urban-rural gradients, 1 ℃ increase of land surface temperature in spring and last winter leads to an advance in start of growing season by 6-31 days, while 1 ℃ increase of land surface temperature in summer and autumn leads to a delay in end of growing season by 0.9-7.6 days. In some buffer zones, increase of forest coverage also contributes similar advances in start of growing season and delays in end of growing season.

鄱阳湖是我国最大的淡水湖, 是与长江保持自由连通的两个湖泊之一, 也是最为重要的候鸟越冬地之一, 其生境质量对全球的生物多样性保护至关重要。枯水期的鄱阳湖由众多子湖构成, 不同子湖具有不同的水文控制与管理模式, 尤其是位于长江上游的三峡大坝2006年正式运行之后, 不同水文控制模式下的子湖展现出不同的退水机制, 对退水期洲滩出露的时间与湿生植被覆盖和生产力产生了不同的影响。近年来, 遥感和生态模型在研究植被变化中应用广泛。本文以MODIS增强植被指数(enhanced vegetation index, EVI)时间序列表示地表属性, 并利用EVI时间序列模型, 建立了2000-2014年植被覆盖和生产力的时空变化趋势。在研究区内建立的网格中, 随机提取了107个斑块, 采集其每16天间隔的MODIS EVI时间序列(2000年2月至2015年4月), 将自适应Savitzky-Golay平滑算法应用于EVI时间序列分析, 提取了4个关键的植被生长指标, 即生长季开始的日期、生长季长度、生长季EVI峰值和生产力。研究结果表明: (1)具有不同水文控制模式下的湿地植被生长特征表现出显著的差异, 尤其位于自由连通子湖的植被与其他模式的子湖相比: 生长季开始的时间更晚, 生长季较短, EVI峰值较低, 并且生长季节的初级生产力较低; (2)由于水文情势的改变, 自由连通子湖2006年前后的双生长周期湿地植被的生长特征差异明显, 秋季生长季提前, 导致了生物量的过度积累, 降低了越冬雁类食源的适口性; 但位于局部水文控制子湖的湿地植被不存在这种差异。(3)自由连通与局部水文控制的子湖对鄱阳湖越冬候鸟的保护均具有十分重要的意义, 需要保证这两种类型子湖的面积, 为越冬候鸟提供更广阔的食源; 当水文情势发生改变时, 局部的水文人为控制可在一定程度上减缓鄱阳湖水情变化对湿地植被生长带来的影响。

Poyang Lake, the largest freshwater lake in China, is one of two lakes that maintain a natural hydrological link with the Yangtze River. The lake system is critical for biodiversity conservation globally, harboring large number of migratory waterbirds. During the dry season, Poyang Lake fragments in to numerous sub-lakes, and different sub-lakes have different hydrological control and management mode. However, the recent hydrological alternation, presumably caused by the operation of Three Gorge Dam (TGD), is threatening the ecological integrity of the lake system, especially as a wintering ground for waterbirds. A robust investigation of the effects of TGD on vegetation cover and productivity at this critical biodiversity hotspot is therefore timely, and could incorporate recent advances in remote sensing and ecological modelling. In this study, using MODIS EVI (enhanced vegetation index) time series, we investigated the spatiotemporal patterns of growth in the lake for the period of 2000-2014, which includes periods before (2000-2006) and after (2007-2014) TGD was commissioned. Firstly, we extracted 107 16-day MODIS EVI time series (February 2000 to April 2015) for 10 randomly placed transects across the lake. We then applied the adaptive Savitzky-Golay smoothing algorithm to the EVI time series, and extracted four key growth metrics, namely, the starting date of growth season, growth season length, seasonal peak EVI, and productivity index. We found significant associations between the hydrological alternation and changes in vegetation seasonality. First, we found that the vegetation growth characteristics of wetlands under different hydrological control modes showed significant differences. In particular, the vegetation located in the freely connected sub-lakes had a later start of growing season, shorter growing season, lower peak EVI value, and lower primary productivity compared to sub-lakes of other modes. Second, due to the hydrological alteration, growth characteristics of sites in freely connected sub-lakes displayed two cycles per year and differed significantly before and after 2006. The advance of the autumn growing season led to excessive accumulation of biomass, which reduced the palatability of the food of migratory geese. However, this difference does not exist in the sites located in the local controlled sub-lake. Third, free connected and local controlled sub-lakes are both important for the protection of migratory birds of Poyang Lake. It is necessary to protect areas harboring both types of sub-lakes to provide a wider food source for wintering migratory birds. Local hydrology control can, to some extent, slow down the impact of much larger scale hydrological alteration on wetland vegetation growth.

One hundred years ago, Andrew D. Hopkins estimated the progressive delay in tree leaf-out with increasing latitude, longitude, and elevation, referred to as "Hopkins' bioclimatic law." What if global warming is altering this well-known law? Here, based on ∼20,000 observations of the leaf-out date of four common temperate tree species located in 128 sites at various elevations in the European Alps, we found that the elevation-induced phenological shift (EPS) has significantly declined from 34 d⋅1,000 m conforming to Hopkins' bioclimatic law in 1960, to 22 d⋅1,000 m in 2016, i.e., -35%. The stronger phenological advance at higher elevations, responsible for the reduction in EPS, is most likely to be connected to stronger warming during late spring as well as to warmer winter temperatures. Indeed, under similar spring temperatures, we found that the EPS was substantially reduced in years when the previous winter was warmer. Our results provide empirical evidence for a declining EPS over the last six decades. Future climate warming may further reduce the EPS with consequences for the structure and function of mountain forest ecosystems, in particular through changes in plant-animal interactions, but the actual impact of such ongoing change is today largely unknown.

深入认识北半球植被物候在全球变暖背景下的动态变化特征,对于评估和预测生态系统结构和功能对气候变化的响应有重要的指示作用.遥感技术是获取北半球植被春季物候的最重要方法,但是由于物候提取算法的差异,目前还存在较大的不确定性.本文利用5种方法,基于卫星获取的归一化植被指数估算了北半球中高纬地区1982—2009年植被春季物候开始日期,分析了该日期的多年动态变化的时空特征,并探讨了气候变化对春季物候变化的影响.结果表明: 研究区植被春季物候开始日期呈现提前趋势,研究期间提前(4.0±0.8) d,其中,欧亚大陆提前速率为(0.22±0.04) d·a^-1,显著高于北美大陆的变化速率(0.03±0.02 d·a^-1);不同植被类型的变化趋势不同,5种方法都显示草地表现为显著提前趋势,而林地的提前趋势不显著.区域平均的植被春季物候开始日期的年际波动主要受春季温度的变化所驱动(r² =0.61,P<0.001), 温度每上升1 ℃,可以导致春季物候提前(3.2±0.5) d,而春季降水影响不显著(P>0.05).

In-depth understanding the variation of vegetation spring phenology is important and nece-ssary for estimation and prediction of ecosystem response to climate change. Satellite-based estimation is one of the important methods for detecting the vegetation spring phenology in Northern Hemisphere. However, there are still many uncertainties among different remote sensing models. In this study, we employed NDVI satellite product from 1982 to 2009 to estimate vegetation green-up onset dates in spring across Northern Hemisphere, and further analyzed the phenology spatio-temporal variation and the relationship with climate. Results showed that spatial mean spring phenology significantly advanced by (4.0±0.8) days during this period in the Northern Hemisphere, while spring phenology advanced much faster in Eurasia (0.22±0.04 d·a^-1) than in North America (0.03±0.02 d·a^-1). Moreover, phenology of different vegetation types changed inconstantly during the period. All five methods consistently indicated that grassland significantly advanced, while forests didn’t advance robustly among methods. In addition, the interannual change of spring phenology was mainly driven by spring temperature. The spring phenology advanced (3.2±0.5) days with 1 ℃ increase in temperature. On the contrary, we did not find significant relationship between vegetation spring phenology and spring accumulative precipitation across the Northern Hemisphere (<i>P</i>&gt;0.05) in this study.

研究草地物候变化对揭示草地生态系统随全球气候变化的响应机制具有重要的科学意义.本研究基于1983—2015年的GIMMS NDVI 3g、气候和数字高程模型(DEM)数据,采用动态阈值法提取北方草地的物候信息[生长季始期(SOS)、生长季末期(EOS)、生长季长度(LOS)],分析北方草地物候的时空变化及LOS对气候的响应.结果表明: 88.9%的像元SOS发生在3月下旬到5月下旬(日序第90～150天),其中,68.1%的像元表现为提前,速率为-1.5～0 d·(32 a)^-1;79.7%的像元EOS发生在10月上旬到10月下旬(日序第270～300天),其中,70.3％的像元表现为推迟,速率为0～1.5 d·(32 a)^-1;LOS持续在100～140 d,其中,LOS变长的像元占73.7%,速率为0～1.5 d·(32 a)^-1.LOS与气温呈显著正相关(R=0.628),与降水呈弱负相关(R=-0.091),并存在明显的空间差异.以海拔2000 m为分界线,低于2000 m时,LOS与海拔呈弱正相关(R=0.235),高于2000 m时,LOS与海拔呈显著负相关(R=-0.861);海拔高于3000 m时,海拔每升高1000 m, LOS缩短约10 d.

Understanding phenological change of grasslands has scientific significance to reveal their responses to global climate change. Based on the data of GIMMS NDVI 3g, climate data from 1983 to 2015 and digital elevation model (DEM), dynamic threshold method was used to extract the phenological information of northern grassland [the start of growth season (SOS), the end of growth season (EOS), and the length of growth season (LOS)]. We analyzed the temporal and spatial variation of phenology of grassland vegetation and the influence of climate on LOS. The results showed that 88.9% of SOS occurred from late March to late May (90-150 d), and 68.1% of pixels were advanced with a rate of -1.5-0 d·(32 a)^-1. 79.7% of EOS occurred from early October to late October (270-300 d), with a delay rate of 0-1.5 d·(32 a)^-1, accounting for 70.3% of the pixel number. LOS lasted for 100-140 days and became longer (73.7%), with a rate of 0-1.5 d·(32 a)^-1. LOS was significantly positively correlated with temperature (<i>R</i>=0.628) and weakly negatively correlated with precipitation (<i>R</i>=-0.091). There was a significant spatial variation. The 2000 m line above sea level was recognized as the demarcation line. LOS had a weak positive correlation with altitude under 2000 m (<i>R</i>=0.235) and a significant negative correlation with altitude above 2000 m (<i>R</i>=-0.861). Above 3000 m altitude, LOS decreased by about 10 d for every 1000 m elevation.

Climate change is lengthening the growing season of the Northern Hemisphere extratropical terrestrial ecosystems, but little is known regarding the timing and dynamics of the peak season of plant activity. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations and atmospheric CO concentration and δ C isotope measurements at Point Barrow (Alaska, USA, 71°N) to study the dynamics of the peak of season (POS) of plant activity. Averaged across extratropical (>23°N) non-evergreen-dominated pixels, NDVI data show that the POS has advanced by 1.2 ± 0.6 days per decade in response to the spring-ward shifts of the start (1.0 ± 0.8 days per decade) and end (1.5 ± 1.0 days per decade) of peak activity, and the earlier onset of the start of growing season (1.4 ± 0.8 days per decade), while POS maximum NDVI value increased by 7.8 ± 1.8% for 1982-2015. Similarly, the peak day of carbon uptake, based on calculations from atmospheric CO concentration and δ C data, is advancing by 2.5 ± 2.6 and 4.3 ± 2.9 days per decade, respectively. POS maximum NDVI value shows strong negative relationships (p < .01) with the earlier onset of the start of growing season and POS days. Given that the maximum solar irradiance and day length occur before the average POS day, the earlier occurrence of peak plant activity results in increased plant productivity. Both the advancing POS day and increasing POS vegetation greenness are consistent with the shifting peak productivity towards spring and the increasing annual maximum values of gross and net ecosystem productivity simulated by coupled Earth system models. Our results further indicate that the decline in autumn NDVI is contributing the most to the overall browning of the northern high latitudes (>50°N) since 2011. The spring-ward shift of peak season plant activity is expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.© 2017 John Wiley & Sons Ltd.

Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate-carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy-covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000-2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r(2) = 0.90) and GPP recovery after a fire disturbance in South Dakota (r(2) = 0.88). Additional analysis of the eddy-covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.

Changes in peak photosynthesis timing (PPT) could substantially change the seasonality of the terrestrial carbon cycle. Spring PPT in dry regions has been documented for some individual plant species on a stand scale, but both the spatio-temporal pattern of shifting PPT on a continental scale and its determinants remain unclear. Here, we use satellite measurements of vegetation greenness to find that the majority of Northern Hemisphere, mid-latitude vegetated area experienced a trend toward earlier PPT during 1982-2012, with significant trends of an average of 0.61 day yr(-1) across 19.4% of areas. These shifts correspond to increased annual accumulation of growing degree days (GDD) due to warming and are most highly concentrated in the eastern United States and Europe. Earlier mean PPT is generally a trait common among areas with summer temperatures higher than 27.6 ± 2.9 °C, summer precipitation lower than 84.2 ± 41.5 mm, and fraction of cold season precipitation greater than 89.2 ± 1.5%. The trends toward earlier PPT discovered here have co-occurred with overall increases in vegetation greenness throughout the growing season, suggesting that summer drought is not a dominant driver of these trends. These results imply that continued warming may facilitate continued shifts toward earlier PPT and cause these trends to become more pervasive, with important implications for terrestrial carbon, water, nutrient, and energy budgets.© 2016 John Wiley & Sons Ltd.

Climatic warming has advanced spring phenology across the Northern Hemisphere, but the spatial variability in temperature sensitivity of spring phenology is substantial. Whether spring phenology will continue to advance uniformly at latitudes has not yet been investigated. We used Bayesian model averaging and four spring phenology models, and demonstrated that the start of vegetation growing season across the Northern Hemisphere will become substantially more synchronous (up to 11.3%) under future climatic warming conditions. Larger start of growing season advances are expected at higher than lower latitudes (3.7–10.9 days earlier) due to both larger rate in spring warming at higher latitudes and larger decreases in the temperature sensitivity of start of growing season at low latitudes. The consequent impacts on the northern ecosystems due to this increased synchrony may be considerable and thus worth investigating.

Autumn phenology plays a critical role in regulating climate-biosphere interactions. However, the climatic drivers of autumn phenology remain unclear. In this study, we applied four methods to estimate the date of the end of the growing season (EOS) across China's temperate biomes based on a 30-year normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). We investigated the relationships of EOS with temperature, precipitation sum, and insolation sum over the preseason periods by computing temporal partial correlation coefficients. The results showed that the EOS date was delayed in temperate China by an average rate at 0.12 ± 0.01 days per year over the time period of 1982-2011. EOS of dry grassland in Inner Mongolia was advanced. Temporal trends of EOS determined across the four methods were similar in sign, but different in magnitude. Consistent with previous studies, we observed positive correlations between temperature and EOS. Interestingly, the sum of precipitation and insolation during the preseason was also associated with EOS, but their effects were biome dependent. For the forest biomes, except for evergreen needle-leaf forests, the EOS dates were positively associated with insolation sum over the preseason, whereas for dry grassland, the precipitation over the preseason was more dominant. Our results confirmed the importance of temperature on phenological processes in autumn, and further suggested that both precipitation and insolation should be considered to improve the performance of autumn phenology models.© 2015 John Wiley & Sons Ltd.

利用系统聚类方法和经验正交函数分解（EOF分析）2种方法,分别提取了北半球中纬度地区1982~2011年秋季（9~11月）归一化差值植被指数（NDVI）变化的主要模态,辨识了植被绿度变化的区域差异;并采用奇异值分解（SVD）的方法,综合时间和空间2个维度上的变异信息,揭示了植被绿度变化的气候背景。结果表明,北半球中纬度秋季植被绿度变化有2种基本模态,一种是持续增加模态（模态I）,该模态广泛分布于北美大陆、亚欧大陆的北半部（大约在55^oN以北）和东西两端,NDVI平均增速为0.014/10a;另一种是趋势转折模态（模态II）,NDVI先增加,后减少,转折点大致出现在1994年,该模态主要出现在亚欧大陆中部,NDVI变化的平均速率分别是0.027/10a和-0.017/10a,其中以40^oE~80^oE最为典型。植被绿度变化与温度变化的时空特征基本一致。模态I区域的温度变化以持续性升高为主要特征,模态II区域的温度变化则以先增加后降低为主要特征,转折年份与NDVI变化的转折年份基本一致。SVD分析的第一模态NDVI与温度的时间系数相关系数为0.82,第二模态为0.92。由此表明,植被绿度变化主导模态可能由温度变化模态所致,在区域-大洲尺度上,温度变化的区域差异导致了秋季植被绿度变化的区域差异。

：To understand response of terrestrial ecosystem to climate changes, it is important to study variations in vegetation greenness (VG) under the changing climate. We firstly extend the Advanced Very High Resolution Radiameter (AVHRR)-based Normalized Difference Vegetation Index (NDVI) from 2006 to 2011 by calibrating the Moderate Resolution Imaging Spectroradiometer-based NDVI. Using hierarchical clustering and empirical orthogonal function (EOF) analysis, this study picked out main models of variations of autumn VG (September to November) which was indicate by NDVI from 1982 to 2011. Then, by using Singular Value Decomposition (SVD), we integrated temporal variations and spatial variations of NDVI and temperature to reveal climate background of variations in VG. We found that the MODIS-NDVI captures the main variations of VG as the AVHRR-NDVI; therefore, it is reliable to extend the AVHRR-NDVI with the MODIS-NDVI. Both of cluster analysis and EOF analysis show the variations in autumn VG had two main models. One (model I) was featured by an increasing trend of VG from 1982 to 2011. This model spreads across the North America land, northern part and (west, east) two ends of Eurasia. The mean rate of increase in NDVI was ~0.014 per decade. The other model (model II) was featured by turn of NDVI variations. This model mostly spread in the center area of Eurasia. The turn point of NDVI variations was about 1994. From 1982 to 1994, the NDVI increased at the rate of 0.027 per decade; while, from 1995 to 2011, the NDVI decreased at the rate of 0.017 per decade. EOF analysis as well as illustrates that above two models could explain 21.1% and 8.1% of total variations of NDVI, respectively. The SVD analysis illustrated that variations in NDVI matched well with variations in temperature. In the Model I area, the temperature changes were featured by an increasing trend. The time coefficients of NDVI and temperature had a strong correlation (R=0.82). In the model II area, the temperature changes were featured by a turn point. Before the turn point, temperature increased; after the turn point, temperature decreased. The time coefficients of NDVI and temperature also had a strong correlation (R=0.92). These results suggest that the persisting greening in the Model I area occurred in the climate warming background and conversion from greening to browning in the Model II area co-occurred with the climate changes from warming to cooling. These findings demonstrate that the main models of variations in VG might result from temperature variations. In the continental scale, the spatial heterogeneity of temperature variations resulted in spatial heterogeneity of VG variations.

As the continuation and development of NOAA/AVHRR NDVI, the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) of MODIS have been comprehensively used in many fields. In order to investigate the difference between NDVI and EVI derived from MODIS, comparative study of these two vegetation indices was conducted by statistics and geo- statistic methods (semi- variance function). By the comparison of the two kinds of vegetation index distribution maps in different period, it is demonstrated that EVI improve the sensitivity for well- vegetated areas where NDVI is saturated when plants grow well, which will be helpful in monitoring plants growth status. At same resolution, i.e. 250m, 500m and 1000m, by means of the geo- statistics, the results show that range, variance and variation coefficient of EVI is higher than that of NDVI, the value of NDVI is even, and its spatial relativity is higher than that of EVI, which all show that EVI is more sensitive to the spatial heterogeneity of plants in research area.

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin &gt; Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.

Accurate predictions of spring plant phenology with climate change are critical for projections of growing seasons, plant communities and a number of ecosystem services, including carbon storage. Progress towards prediction, however, has been slow because the major cues known to drive phenology - temperature (including winter chilling and spring forcing) and photoperiod - generally covary in nature and may interact, making accurate predictions of plant responses to climate change complex and nonlinear. Alternatively, recent work suggests many species may be dominated by one cue, which would make predictions much simpler. Here, we manipulated all three cues across 28 woody species from two North American forests. All species responded to all cues examined. Chilling exerted a strong effect, especially on budburst (-15.8 d), with responses to forcing and photoperiod greatest for leafout (-19.1 and -11.2 d, respectively). Interactions between chilling and forcing suggest that each cue may compensate somewhat for the other. Cues varied across species, leading to staggered leafout within each community and supporting the idea that phenology is a critical aspect of species' temporal niches. Our results suggest that predicting the spring phenology of communities will be difficult, as all species we studied could have complex, nonlinear responses to future warming.© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Seasonality in photosynthetic activity is a critical component of seasonal carbon, water, and energy cycles in the Earth system. This characteristic is a consequence of plant's adaptive evolutionary processes to a given set of environmental conditions. Changing climate in northern lands (>30°N) alters the state of climatic constraints on plant growth, and therefore, changes in the seasonality and carbon accumulation are anticipated. However, how photosynthetic seasonality evolved to its current state, and what role climatic constraints and their variability played in this process and ultimately in carbon cycle is still poorly understood due to its complexity. Here, we take the "laws of minimum" as a basis and introduce a new framework where the timing (day of year) of peak photosynthetic activity (DOY ) acts as a proxy for plant's adaptive state to climatic constraints on its growth. Our analyses confirm that spatial variations in DOY reflect spatial gradients in climatic constraints as well as seasonal maximum and total productivity. We find a widespread warming-induced advance in DOY (-1.66 ± 0.30 days/decade, p < 0.001) across northern lands, indicating a spatiotemporal dynamism of climatic constraints to plant growth. We show that the observed changes in DOY are associated with an increase in total gross primary productivity through enhanced carbon assimilation early in the growing season, which leads to an earlier phase shift in land-atmosphere carbon fluxes and an increase in their amplitude. Such changes are expected to continue in the future based on our analysis of earth system model projections. Our study provides a simplified, yet realistic framework based on first principles for the complex mechanisms by which various climatic factors constrain plant growth in northern ecosystems.© 2019 John Wiley & Sons Ltd.

Tundra dominates two-thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community-specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.© 2020 John Wiley & Sons Ltd.

荒漠草原分布于干旱区和半干旱区,对气候变化的响应极为敏感,但目前学术界对于荒漠草原物候与生产力变化的研究仍较为薄弱。有鉴于此,论文采用2000—2017年MODIS NDVI数据和气象数据,利用通用数量化方法提取内蒙古荒漠草原植被的生长季始期(start of season, SOS)和生长季末期(end of season, EOS);基于Carnegie-Ames-Stanford Approach (CASA)模型估算了植被净初级生产力(NPP),并分析了植被物候和净初级生产力之间的关系。研究结果表明：① 2000—2017年内蒙古荒漠草原SOS呈显著提前趋势(0.88 d/a,PP>0.05),生长季长度(length of season, LOS)呈显著延长趋势(0.76 d/a)。81.53%像元的SOS与2—4月平均气温呈负相关(8.21%显著相关,PPPP2</sup>·a),有自东向西逐渐降低的区域差异;在研究时段内,春、夏季和生长季的NPP均呈不显著增加趋势,秋季NPP有不显著减少趋势;生长季降水量增加有利于生长季NPP的积累。③ 春季NPP与SOS呈不显著负相关,秋季NPP与EOS呈显著正相关。LOS的延长促进了NPP的累积,其中生长季NPP与EOS的推迟关系更为密切。研究结果揭示气候变化对内蒙古荒漠草原植被物候和生产力有显著影响,对区域生态系统管理和生态建设具有重要参考意义。

<p id="C4">Desert steppe is distributed in the semiarid and arid areas and is extremely sensitive to climate change. However, limited field observations and lack of community surveys have resulted in insufficient research on the vegetation phenology and productivity of the desert steppe. Based on the normalized difference vegetation index (NDVI) data from the MODIS dataset during 2000-2017, we used a relative threshold method to extract the phenological parameters in the desert steppe of Inner Mongolia, including the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (LOS). We then estimated the spatiotemporal changes in net primary productivity (NPP) of the desert steppe vegetation by the Carnegie-Ames-Stanford Approach (CASA) model. Finally, we analyzed the relationship between desert steppe productivity, phenophases, and climate variables. Our results show that: 1) during the study period, SOS advanced significantly at a rate of 0.88 d/a (<i>P</i><0.05), while EOS advanced at a rate of 0.13 d/a (non-significant). The average LOS lengthened significantly by 0.76 d/a (<i>P</i><0.05). The SOS was correlated negatively with mean temperature from February to April in 81.53% pixels (8.21% was significant) and negatively correlated with April precipitation in 60.80% pixels (6.12% was significant). The EOS showed a negative relationship with mean temperature in September in 65.16% pixels (5.03% was significant) but positively correlated with precipitation from July to September in 78.61% pixels (10.12% was significant). 2) The average annual NPP from 2000 to 2017 was 104.71gC/(m ²·a) in the study area, showing regional differences with an obviously decreasing trend from east to west. Net primary productivity in spring, summer, and the growing season increased insignificantly, while NPP in autumn showed an insignificant decreasing trend. The increase of precipitation in the growing season is beneficial to the accumulation of ecosystem NPP. 3) Advance of SOS was conducive to the accumulation of spring NPP, and the delay of EOS promoted the accumulation of autumn NPP. There was a significant correlation between the LOS and NPP during the growing season (<i>P</i><0.05). This study revealed the impacts of climate change on vegetation phenology and productivity of the desert steppe in Inner Mongolia, which is significant for ecosystem management and ecological construction of the region. </p>

We combine satellite and ground observations during 1950-2011 to study the long-term links between multiple climate (air temperature and cryospheric dynamics) and vegetation (greenness and atmospheric CO(2) concentrations) indicators of the growing season of northern ecosystems (>45°N) and their connection with the carbon cycle. During the last three decades, the thermal potential growing season has lengthened by about 10.5 days (P < 0.01, 1982-2011), which is unprecedented in the context of the past 60 years. The overall lengthening has been stronger and more significant in Eurasia (12.6 days, P < 0.01) than North America (6.2 days, P > 0.05). The photosynthetic growing season has closely tracked the pace of warming and extension of the potential growing season in spring, but not in autumn when factors such as light and moisture limitation may constrain photosynthesis. The autumnal extension of the photosynthetic growing season since 1982 appears to be about half that of the thermal potential growing season, yielding a smaller lengthening of the photosynthetic growing season (6.7 days at the circumpolar scale, P < 0.01). Nevertheless, when integrated over the growing season, photosynthetic activity has closely followed the interannual variations and warming trend in cumulative growing season temperatures. This lengthening and intensification of the photosynthetic growing season, manifested principally over Eurasia rather than North America, is associated with a long-term increase (22.2% since 1972, P < 0.01) in the amplitude of the CO(2) annual cycle at northern latitudes. The springtime extension of the photosynthetic and potential growing seasons has apparently stimulated earlier and stronger net CO(2) uptake by northern ecosystems, while the autumnal extension is associated with an earlier net release of CO(2) to the atmosphere. These contrasting responses may be critical in determining the impact of continued warming on northern terrestrial ecosystems and the carbon cycle.© 2013 John Wiley & Sons Ltd.

当前人类活动的加剧显著地影响着全球大气循环的格局。大气循环的多个模型均预测未来全球气候变化的显著特征是极端降水事件和极端干旱事件发生的频率会显著增加。水分是干旱、半干旱区草原植物生长发育的限制性资源, 而草原生态系统是陆地生态系统中对降水格局变化非常敏感的系统。但是, 关于极端降水事件和极端干旱事件对草原生态系统结构和功能的影响还是以分散的个案研究为主, 甚至关于极端气候事件的定义迄今也不尽相同。为此, 该文在分析极端气候事件定义及其研究方法的基础上, 总结了极端降水事件和极端干旱事件对草原生态系统土壤水分和养分状况、植物生长发育和生理特性、群落结构、生产力和碳循环过程的影响, 并提出了未来极端气候事件研究中应重点关注的5个重要方向, 以及控制试验研究的2个关键科学问题, 对开展全球变化背景下草原生态系统对极端气候事件响应机制的研究具有指导意义。

Global atmospheric circulations are greatly affected by anthropogenic activities. Several atmospheric circulation models predict that the frequencies of extreme rainfall events and extreme droughts will increase in the future. Water is one of the most limiting resources for growth and development of plants in arid and semi-arid ecosystems. Furthermore, grassland ecosystems have been proven to be very sensitive to changing precipitation regimes. However, our understanding on the effects of extreme climatic events on the structure and functioning of grassland ecosystems is inadequate. By far, the definitions of extreme climatic events are still inconsistent. Therefore, based on analyses of the definitions of extreme climatic events and research methods in literature, we synthesize the effects of extreme rainfall events and extreme droughts on soil water and nutrient availability, individual plant development and physiological characteristics, community structure, ecosystem productivity and carbon cycling. In addition, we put forward five scientific questions on research concerning the impacts of extreme climatic events and identify two key issues on manipulative precipitation experiments to help with understanding the mechanisms on how grassland ecosystems respond to extreme climatic events in the context of global change.

Global climate change has led to significant vegetation changes in the past half century. Inner Mongolia, most of which was located in arid and semi-arid areas, is undergoing a process of prominent warming and drying. It is necessary to investigate the response of vegetation to the climatic variations (temperature and precipitation) for a better understanding of the accumulated consequence of climate change. Vegetation coverage, which is an important indicator for evaluating terrestrial environment, is used to monitor vegetation change. MODIS-NDVI data and climate data were used to analyze the vegetation dynamics and its relationship with climate change on different spatial (forest, grassland and desert biome) and temporal (yearly and monthly) scales in Inner Mongolia during 2001-2010. It was found that vegetation coverage increased from west to east across Inner Mongolia with a change rate of 0.2/10&deg;N. During 2001-2010, the mean vegetation coverage was 0.57, 0.4 and 0.16 in forest, grassland and desert biome, respectively, exhibiting evident spatial heterogeneities. There is a slight increase of vegetation coverage over the study period. Across Inner Mongolia, the vegetation coverages with extremely significant and significant increase accounted for 11.25% and 29.13% of the total study area, respectively, while those with extremely significant and significant decrease were 7.65% and 26.61%, respectively. The correlation analysis between vegetation coverage and climate shows that annual vegetation coverage was better correlated with precipitation, while the change of monthly vegetation coverage is consistent with both the changes of temperature and precipitation, indicating that the vegetation growth within a year is more sensitive to the joint function of hydrothermal combination rather than either climate factor. The vegetation coverage of forest biome was mainly affected by temperature on both yearly and monthly scales, while that of desert biome was mainly influenced by precipitation on the two temporal scales.

Recent temperature increases have elicited strong phenological shifts in temperate tree species, with subsequent effects on photosynthesis. Here, we assess the impact of advanced leaf flushing in a winter warming experiment on the current year's senescence and next year's leaf flushing dates in two common tree species: Quercus robur L. and Fagus sylvatica L. Results suggest that earlier leaf flushing translated into earlier senescence, thereby partially offsetting the lengthening of the growing season. Moreover, saplings that were warmed in winter-spring 2009-2010 still exhibited earlier leaf flushing in 2011, even though the saplings had been exposed to similar ambient conditions for almost 1 y. Interestingly, for both species similar trends were found in mature trees using a long-term series of phenological records gathered from various locations in Europe. We hypothesize that this long-term legacy effect is related to an advancement of the endormancy phase (chilling phase) in response to the earlier autumnal senescence. Given the importance of phenology in plant and ecosystem functioning, and the prediction of more frequent extremely warm winters, our observations and postulated underlying mechanisms should be tested in other species.