Strong contribution of autumn phenology to changes in satellite‐derived growing season length estimates across Europe (1982–2011)

Land Surface Phenology (LSP) is the most direct representation of intra‐annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land‐surface fluxes, and is central to accurately parameterizing terrestrial biosphere–atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan‐European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape‐based aggregation scheme. We used indicators of Start‐Of‐Season, End‐Of‐Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982–2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18–24 days decade^?1 over 18–30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing‐season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI‐derived end‐of‐season contributed more to the GSL trend than changes in spring green‐up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.     

A comparative study of satellite and ground-based phenology

Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.     

Temperature,precipitation, and insolation effects on autumn vegetation phenology in temperate China

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.     

Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008

Changes in vegetative growing seasons are dominant indicators of the dynamic response of ecosystems to climate change. Therefore, knowledge of growing seasons over the past decades is essential to predict ecosystem changes. In this study, the long‐term changes in the growing seasons of temperate vegetation over the Northern Hemisphere were examined by analyzing satellite‐measured normalized difference vegetation index and reanalysis temperature during 1982–2008. Results showed that the length of the growing season (LOS) increased over the analysis period; however, the role of changes at the start of the growing season (SOS) and at the end of the growing season (EOS) differed depending on the time period. On a hemispheric scale, SOS advanced by 5.2 days in the early period (1982–1999) but advanced by only 0.2 days in the later period (2000–2008). EOS was delayed by 4.3 days in the early period, and it was further delayed by another 2.3 days in the later period. The difference between SOS and EOS in the later period was due to less warming during the preseason (January–April) before SOS compared with the magnitude of warming in the preseason (June–September) before EOS. At a regional scale, delayed EOS in later periods was shown. In North America, EOS was delayed by 8.1 days in the early period and delayed by another 1.3 days in the later period. In Europe, the delayed EOS by 8.2 days was more significant than the advanced SOS by 3.2 days in the later period. However, in East Asia, the overall increase in LOS during the early period was weakened in the later period. Admitting regional heterogeneity, changes in hemispheric features suggest that the longer‐lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf‐out.     

Discrepancies in vegetation phenology trends and shift patterns in different climatic zones in middle and eastern Eurasia between 1982 and 2015

Changes in vegetation phenology directly reflect the response of vegetation growth to climate change. In this study, using the Normalized Difference Vegetation Index dataset from 1982 to 2015, we extracted start date of vegetation growing season (SOS), end date of vegetation growing season (EOS), and length of vegetation growing season (LOS) in the middle and eastern Eurasia region and evaluated linear trends in SOS, EOS, and LOS for the entire study area, as well as for four climatic zones. The results show that the LOS has significantly increased by 0.27 days/year, mostly due to a significantly advanced SOS (?0.20 days/year) and a slightly delayed EOS (0.07 days/year) over the entire study area from 1982 to 2015. The vegetation phenology trends in the four climatic zones are not continuous throughout the 34‐year period. Furthermore, discrepancies in the shifting patterns of vegetation phenology trend existed among different climatic zones. Turning points (TP) of SOS trends in the Cold zone, Temperate zone, and Tibetan Plateau zone occurred in the mid‐ or late 1990s. The advanced trends of SOS in the Cold zone, Temperate zone, and Tibetan Plateau zone exhibited accelerated, stalled, and reversed patterns after the corresponding TP, respectively. The TP did not occurred in Cold‐Temperate zone, where the SOS showed a consistent and continuous advance. TPs of EOS trends in the Cold zone, Cold‐Temperate zone, Temperate zone, and Tibetan Plateau zone occurred in the late 1980s or mid‐1990s. The EOS in the Cold zone, Cold‐Temperate zone, Temperate zone, and Tibetan Plateau zone showed weak advanced or delayed trends after the corresponding TP, which were comparable with the delayed trends before the corresponding TP. The shift patterns of LOS trends were primarily influenced by the shift patterns of SOS trends and were also heterogeneous within climatic zones.     

物候变化对北美温带落叶阔叶林生态系统生产力的影响

数据源、时间范围、空间尺度等的差异导致许多物候变化对陆地生态系统碳收支影响的研究缺少可比性。该文基于4级碳通量填充数据, 采用相对阈值方法提取了两个北美典型温带阔叶林站Harvard Forest (HF)和University of Michigan Biological Station (UMBS)共20年的物候参数(返青期、枯黄期和生长季长度), 并研究了物候变化对生态系统生产力的影响。结果表明: 1)生长季长度的延长对年累积总初级生产力(GPP)有显著贡献, 但由于呼吸作用(RE)的干扰, 生长季长度变化对年净生态系统生产力(NEP)的影响并不显著; 2)返青期的提前对上半年生态系统总初级生产力的贡献最为显著, 二者的相关系数分别为0.76 (HF)和0.93 (UMBS); 3)枯黄期的延迟对生产力的影响并不显著; 4)随着春季返青期的提前或秋季枯黄期的延迟, 上、下半年GPP和RE的累积量虽均有增加趋势, 但由于各自增加的幅度不确定, 导致年NEP与二者的响应关系复杂。     

Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006

Aim We intend to characterize and understand the spatial and temporal patterns of vegetation phenology shifts in North America during the period 1982–2006. Location North America. Methods A piecewise logistic model is used to extract phenological metrics from a time‐series data set of the normalized difference vegetation index (NDVI). An extensive comparison between satellite‐derived phenological metrics and ground‐based phenology observations for 14,179 records of 73 plant species at 802 sites across North America is made to evaluate the information about phenology shifts obtained in this study. Results The spatial pattern of vegetation phenology shows a strong dependence on latitude but a substantial variation along the longitudinal gradient. A delayed dormancy onset date (0.551 days year^?1, P= 0.013) and an extended growing season length (0.683 days year^?1, P= 0.011) are found over the mid and high latitudes in North America during 1982–2006, while no significant trends in greenup onset are observed. The delayed dormancy onset date and extended growing season length are mainly found in the shrubland biome. An extensive validation indicates a strong robustness of the satellite‐derived phenology information. Main conclusions It is the delayed dormancy onset date, rather than an advanced greenup onset date, that has contributed to the prolonged length of the growing season over the mid and high latitudes in North America during recent decades. Shrublands contribute the most to the delayed dormancy onset date and the extended growing season length. This shift of vegetation phenology implies that vegetation activity in North America has been altered by climatic change, which may further affect ecosystem structure and function in the continent.     

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。     

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。     

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006

Shifts in the timing of spring phenology are a central feature of global change research. Long‐term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start‐of‐spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground‐based phenology, and two temperature‐driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day‐of‐year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground‐ or model‐based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.     

1990-2020年地表物候时空变化对高寒湿地景观演变过程的响应

地表物候是生态系统环境变化的敏感指示器。为探讨物候时空变化和湿地景观生态格局与过程之间的关系,论文以若尔盖高寒湿地为例,基于1990—2020年GIMMS3g NDVI和MODIS NDVI数据集、7期Landsat TM/OLI卫星遥感数据,采用阈值法提取地表物候参数,基于面向对象的分类方法解译出土地利用数据,利用土地覆盖转换指数模型(PNTI)刻画高寒湿地动态变化过程,分析地表物候时空变化与高寒湿地景观格局演变过程的关系。结果表明：(1)1990—2020年研究区呈现前期湿地面积减少后期趋于稳定的特征,根据土地利用类型演变路径和强度分为动态平衡区、退化演变区和恢复演变区,面积占比分别56.84%、 28.14%和15.02%。(2)植被返青期(SOS)、生长盛期(POS)呈南早北晚,枯黄期(EOS)呈中间早周边晚,生长期长度(LOS)呈中间短周边长、西北短东南长的空间分布特征。SOS分布在第96—149天,EOS分布在第249—284天,LOS持续125—173d, POS分布在第179—209天。SOS、POS先推迟后提前、EOS先提前后推迟,LOS呈现先缩短后延长的规律,199...     

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。     

Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology

The timing of the end of the vegetation growing season (EOS) plays a key role in terrestrial ecosystem carbon and nutrient cycles. Autumn phenology is, however, still poorly understood, and previous studies generally focused on few species or were very limited in scale. In this study, we applied four methods to extract EOS dates from NDVI records between 1982 and 2011 for the Northern Hemisphere, and determined the temporal correlations between EOS and environmental factors (i.e., temperature, precipitation and insolation), as well as the correlation between spring and autumn phenology, using partial correlation analyses. Overall, we observed a trend toward later EOS in ~70% of the pixels in Northern Hemisphere, with a mean rate of 0.18 ± 0.38 days yr^?1. Warming preseason temperature was positively associated with the rate of EOS in most of our study area, except for arid/semi‐arid regions, where the precipitation sum played a dominant positive role. Interestingly, increased preseason insolation sum might also lead to a later date of EOS. In addition to the climatic effects on EOS, we found an influence of spring vegetation green‐up dates on EOS, albeit biome dependent. Our study, therefore, suggests that both environmental factors and spring phenology should be included in the modeling of EOS to improve the predictions of autumn phenology as well as our understanding of the global carbon and nutrient balances.     

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982–2010

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen’s climate regions for the periods of 1982–1999 and 2000–2010, respectively. The results show that OGI and GSL varied considerably during 1982–2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982–1999 and 2000–2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982–1999) to prolonged trends (2000–2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than 1 % in most of climate regions although it could be as large as 10 %.     

Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere

Climate change has substantial influences on autumn leaf senescence, that is, the end of the growing season (EOS). Relative to the impacts of temperature and precipitation on EOS, the influence of drought is not well understood, especially considering that there are apparent cumulative and lagged effects of drought on plant growth. Here, we investigated the cumulative and lagged effects of drought (in terms of the Standardized Precipitation–Evapotranspiration Index, SPEI) on EOS derived from the normalized difference vegetation index (NDVI3g) data over the Northern Hemisphere extra‐tropical ecosystems (>30°N) during 1982–2015. The cumulative effect was determined by the number of antecedent months at which SPEI showed the maximum correlation with EOS (i.e., R_max‐cml) while the lag effect was determined by a month during which the maximum correlation between 1‐month SPEI and EOS occurred (i.e., R_max‐lag). We found cumulative effect of drought on EOS for 27.2% and lagged effect for 46.2% of the vegetated land area. For the dominant time scales where the R_max‐cml and R_max‐lag occurred, we observed 1–4 accumulated months for the cumulative effect and 2–6 lagged months for the lagged effect. At the biome level, drought had stronger impacts on EOS in grasslands, savannas, and shrubs than in forests, which may be related to the different root functional traits among vegetation types. Considering hydrological conditions, the mean values of both R_max‐cml and R_max‐lag decreased along the gradients of annual SPEI and its slope, suggesting stronger cumulative and lagged effects in drier regions as well as in areas with decreasing water availability. Furthermore, the average accumulated and lagged months tended to decline along the annual SPEI gradient but increase with increasing annual SPEI. Our results revealed that drought has strong cumulative and lagged effects on autumn phenology, and considering these effects could provide valuable information on the vegetation response to a changing climate.     

1982-2013年内蒙古地区植被物候对干旱变化的响应

气候变化引起的植被物候变化正在大幅度改变生态系统,研究植被物候对干旱的响应对保护内蒙古的生态系统具有重要意义。根据1：100万植被区划,把内蒙古划分为8个植被分区,利用多时间尺度气象标准化降水蒸散指数（SPEI）和NDVI3g时序数据所反演的物候指标,分析内蒙古植被物候的时空变化及其对干旱的响应规律。结果显示：1）在1982年至2013年间,内蒙古植被受到不同时间尺度下干旱的高度控制,尤其是时间尺度干旱的影响（SPEI-3）;2）对于整个研究区,生长季开始（SOS）呈提前趋势,生长季结束（EOS）呈延后趋势,生长季长度（LOS）呈延长趋势,像元比例分别为63.79%、59.77%和62.83%;3）内蒙古除荒漠植被类型地区外,同年春季和夏季初期干旱对SOS均具有延迟作用,同年秋季干旱对EOS均具有延迟作用 ;4） 不同植被类型对干旱强度指数的响应程度存在差异,响应程度集中在-10d/0.1-10d/0.1（例如,1d/0.1表示干旱强度指数每增大0.1,会导致物候指数延迟1 d,而-1d/0.1表示干旱强度指数每增大0.1,会导致物候指数提前1 d）。     

Comparison of phenology trends by land cover class: a case study in the Great Basin, USA

Direct impacts of human land use and indirect impacts of anthropogenic climate change may alter land cover and associated ecosystem function, affecting ecological goods and services. Considerable work has been done to identify long‐term global trends in vegetation greenness, which is associated with primary productivity, using remote sensing. Trend analysis of satellite observations is subject to error, and ecosystem change can be confused with interannual variability. However, the relative trends of land cover classes may hold clues about differential ecosystem response to environmental forcing. Our aim was to identify phenological variability and 10‐year trends for the major land cover classes in the Great Basin. This case study involved two steps: a regional, phenology‐based land cover classification and an identification of phenological variability and 10‐year trends stratified by land cover class. The analysis used a 10‐year time series of Advanced Very High Resolution Radiometer satellite data to assess regional scale land cover variability and identify change. The phenology‐based regional classification was more detailed and accurate than national or global products. Phenological variability over the 10‐year period was high, with substantial shifts in timing of start of season of up to 9 weeks. The mean long‐term trends of montane land cover classes were significantly different from valley land cover classes due to a poor response of montane shrubland and pinyon‐juniper woodland to the early 1990s drought. The differential response during the 1990s suggests that valley ecosystems may be more resilient and montane ecosystems more susceptible to prolonged drought. This type of regional‐scale land cover analysis is necessary to characterize current patterns of land cover phenology, distinguish between anthropogenically driven land cover change and interannual variability, and identify ecosystems potentially susceptible to regional and global change.     

Response of vegetation phenology to urbanization in the conterminous United States

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.     

柽柳灌丛关键物候参数多种植被指数遥感提取的适用性——基于CO2通量观测和Sentinel-2数据

本研究以额济纳绿洲四道桥超级站为研究区,结合2018—2019年涡度通量、气象数据和2017—2020年Sentinel-2遥感影像,分析通量塔总初级生产力(GPP)与环境因子的关系,评估12种遥感植被指数对柽柳灌丛长势模拟和关键物候参数提取的适用性。采用7参数双逻辑斯蒂函数(DL-7)+全局模型函数(GMF)拟合GPP和各植被指数生长曲线,并逐年提取生长季始期(SOS)、生长季峰期(POS)和生长季末期(EOS)3种关键物候参数。结果表明: 有效积温(GDD)和土壤含水量是影响柽柳灌丛物候动态的主要环境因子。与2018年相比,2019年由于气温较低,SOS前的积温累积速率较慢,柽柳灌丛需要更长时间的热量积累来进入生长季,从而导致2019年SOS比2018年晚。在SOS与POS之间,2018和2019年水热条件相似,但2019年POS比2018年晚8 d,可能是2019年SOS较晚所致。POS以后,2019年较高的GDD和较低的土壤含水量使柽柳灌丛遭受水分胁迫,导致其生长季后期时间缩短。标准化的Sentinel-2植被指数与10:00—14:00 GPP均值的线性回归结果表明,宽波段植被指数中的增强型植被指数和窄波段植被指数中的叶绿素红边指数、倒红边叶绿素指数、红边归一化植被指数(NDVI705)能够较好地反映与柽柳灌丛GPP具有较高的一致性。柽柳灌丛SOS和EOS的遥感提取结果表明,Sentinel-2窄波段植被指数比宽波段植被指数的准确性更高,尤其是修正叶绿素吸收反射率指数提取SOS最准确,MERIS陆地叶绿素指数提取EOS最准确;Sentinel-2宽波段植被指数提取POS的准确性更高,尤其是两波段增强型植被指数和植被近红外反射率指数最准确。综合所有物候参数来看,NDVI705综合表现最佳。     

Spring phenology rather than climate dominates the trends in peak of growing season in the Northern Hemisphere

Shifts in plant phenology regulate ecosystem structure and function, which feeds back to the climate system. However, drivers for the peak of growing season (POS) in seasonal dynamics of terrestrial ecosystems remain unclear. Here, spatial–temporal patterns of POS dynamics were analyzed by solar-induced chlorophyll fluorescence (SIF) and vegetation index in the Northern Hemisphere over the past two decades from 2001 to 2020. Overall, a slow advanced POS was observed in the Northern Hemisphere, while a delayed POS distributed mainly in northeastern North America. Trends of POS were driven by the start of growing season (SOS) rather than pre-POS climate both at hemisphere and biome scale. The effect of SOS on the trends in POS was the strongest in shrublands while the weakest in evergreen broad-leaved forest. These findings highlight the crucial role of biological rhythms rather than climatic factors in exploring seasonal carbon dynamics and global carbon balance.