北半球中高纬度地区近30年植被春季物候温度敏感性

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。     

近40年沈阳城市森林春季物候与全球气候变暖的关系

1960-2005年期间,沈阳气候受全球气候变暖的影响,年平均气温总体呈上升趋势,气温升幅为0.96℃,但以1982年为界,1960-1982年为偏冷阶段,气温降幅最大值为1.95 ℃:1983-2005年为偏暖阶段,气温升幅最大值为1.60 ℃.一年四季气温处于上升阶段,以冬、春季气温升幅最大,分别为2.3 ℃和1.35℃.城市森林主要树种的春季物候期,在气候偏冷阶段,春季物候期出现较晚,而在偏暖阶段,春季物候期提前发生.同时,物候春季开始日期与结束日期有密切的同步相关性,并与物候季节节奏的长短呈负相关.树木萌动期早晚与冬季和早春气温高低呈显著的负相关,冬春季气温越高,芽萌动越提前.展叶早晚主要受展叶前的春季气温高低的影响,与冬季气温相关性不显著.始花前2-8旬,特别是2-14旬气温对始花期影响最显著.寒冷指数(CI)与树木芽萌动期、展叶始期呈显著正相关,而与开花始期相关性不显著.预测了CO2倍增和气温升高条件下,沈阳城市森林主要树种的萌动期、展叶始期和开花始期分别提前40.41、43.08和24.13 d.     

近40年沈阳城市森林春季物候与全球气候变暖的关系术

1960-2005年期间,沈阳气候受全球气候变暖的影响,年平均气温总体呈上升趋势,气温升幅为0．96℃,但以1982年为界,1960-1982年为偏冷阶段,气温降幅最大值为1．95℃;1983-2005年为偏暖阶段,气温升幅最大值为1．60℃。一年四季气温处于上升阶段,以冬、春季气温升幅最大,分别为2．3℃和1．35℃。城市森林主要树种的春季物候期,在气候偏冷阶段,春季物候期出现较晚,而在偏暖阶段,春季物候期提前发生。同时,物候春季开始日期与结束日期有密切的同步相关性,并与物候季节节奏的长短呈负相关。树木萌动期早晚与冬季和早春气温高低呈显著的负相关,冬春季气温越高,芽萌动越提前。展叶早晚主要受展叶前的春季气温高低的影响,与冬季气温相关性不显著。始花前2—8旬,特别是2—4旬气温对始花期影响最显著。寒冷指数（CI）与树木芽萌动期、展叶始期呈显著正相关,而与开花始期相关性不显著。预测了CO2倍增和气温升高条件下,沈阳城市森林主要树种的萌动期、展叶始期和开花始期分别提前40．41、43．08和24．13d。     

黄河流域2001-2020年植被物候及其对气候变化的响应

植被周期性的物候更替被公认为是全球气候变化的综合指示器,深入研究区域植被物候的变化趋势和时空特征,可以提高对该区生态系统稳定性及动态变化程度的认识。基于2001-2020年16天、250m分辨率的中分辨率成像光谱仪归一化植被指数（MODIS NDVI）数据,利用Savitzky-Golay滤波法（S-G）和相对阈值法提取黄河流域植被物候参数,结合谷歌地球引擎（GEE）平台提供的欧洲中期天气预报中心第五代陆地再分析数据集（ERA5-LAND）小时气候再分析数据集和气候危害组红外降水站数据（CHIRPS）日降水数据集数据,运用趋势分析和偏相关分析等方法,探究全球气候变化下黄河流域不同植被分区物候参数空间分布特征、变化趋势,及其对气候因子的响应。结果表明：（1）2001-2020年黄河流域气候整体呈暖湿化的发展趋势,年均温上升幅度为0.15℃/10a（P>0.05）,年降水增加幅度为24mm/10a（P<0.05）。（2）黄河流域暖温带落叶阔叶林区域的生长季始期和中期最早,温带南部典型草原亚地带和温带南部荒漠草原亚地带最晚,温带灌木、禾草半荒漠亚地带的生长季结束期最晚,青藏高原高寒植被区域的生长季长度最短。（3）全流域内生长季始期和中期分别有69.3%和66.4%的面积呈提前趋势（P<0.05）,生长季末期50.9%的面积结束期呈推迟趋势（P<0.05）,66.1%的面积整个生长季长度呈延长趋势（P<0.05）。（4）不同植被地带气候对物候参数影响存在差异,温度因子对带北部典型草原亚地带、高寒草原地带和高寒草甸地带的物候参数影响较大,降水和太阳辐射因子对温带南部典型草原亚地带、温带灌木、禾草半荒漠地带、温带南部荒漠草原亚地带和中亚热带常绿阔叶林地带的物候参数影响较大。     

淮河流域暖季极端高温干旱复合事件的演变特征及其与气候和植被的关系

使用淮河流域1981年至2020年的149个气象站点的气温和相对湿度数据,分析了流域暖季极端高温干旱复合事件(Compound Drought and Heat Events,CDHEs)的时空演变特征,并通过趋势分析和相关分析法探讨了CDHEs与气候和植被的关系。结果表明:①CDHEs的发生日数在年代际尺度上呈现明显的增加趋势,并且范围扩大,频发区逐渐向淮河流域中西部移动;②在年际尺度上,CDHEs随时间序列呈显著的波动上升趋势,空间分布上以西北部为中心向四周递减。连续CDHEs事件呈年际变化,最大2至4天的连续事件存在波动,2019年达到高峰,并且在流域内零散或成片出现;③在月际尺度上,CDHEs的发生日数在6月最多,其次是5月、7月、9月和8月。淮河流域入汛前的旱情和入汛后的旱涝急转都容易导致CDHEs发生,而且随着月际变化向南移动;④CDHEs对水热条件和大气环流具有特别的敏感性。在850hPa反气旋和500hPa显著高压异常的控制下,高温、低湿、高蒸发和降水少的气候背景有利于淮河地区CDHEs的形成,尤其是在淮河中西部地区。因此,CDHEs的发生与气候变化密切相关;⑤CDHEs与植被生长也存在显著关系。CDHEs与GPP呈显著的负相关,而与NDVI呈显著的正相关,显著地区的土地类型以耕地和城乡、工矿、居民用地为主。GPP和NDVI的不同步可能是因为多种因素的非线性相互作用,而不仅仅是单一因素的影响。此外,对于GPP和NDVI来说,土壤含水量至关重要。总之,本文对淮河流域CDHEs的时空分布特征进行了深入研究,并探讨了其与气候和植被的关系。研究结果可以为该地区的气象灾害防御和生态环境保护提供科学依据和参考。     

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。     

甘肃河东地区植被物候及其对气候变化的响应

探究中纬度地区的植被物候及其对气候变化的响应,对理解生态系统对气候变化的响应以及预测区域生态系统的碳循环至关重要。本文基于2000—2018年MODIS EVI数据,利用非对称高斯函数(A-G)与动态阈值法提取森林与草地物候参数,结合气象数据探究河东地区植被物候与气候变化的响应关系。结果表明：森林与草地物候参数存在显著差异,两者生长季始期(start of growing season, SOS)的趋势均提前,生长季末期(end of growing season, EOS)的趋势分别提前和推迟,其中整体SOS呈提前趋势的面积占比61%,EOS呈推迟趋势的面积占比41%,生长季长度(length of growing season, LOS)呈延长趋势的面积占比53%;随着海拔和纬度的上升,植被SOS、EOS和LOS分别呈推迟、提前和缩短的趋势发展,但这种趋势正在减弱;季前气候对SOS和EOS存在不同程度、方向的影响,秋冬季高温推迟SOS,春季高温则提前SOS,春夏季降水增加提前EOS,秋季高温推迟EOS,且对于河东地区而言,最低气温影响更为显著;森林与草地之间对于气候变化的响应程度存...     

2003-2018年米仓山地区植被物候时空变化及对气候的响应

植被物候直接反映了植被对环境变化响应的动态过程,对研究植被与气候的关系具有重要意义。基于遥感植被时序数据,探讨秦巴山区典型山地-米仓山地区植被物候变化及其对气候的响应。利用MODIS NDVI时序数据,采用动态阈值法获取米仓山地区植被物候参数;借助于Theil Sen斜率、Mann Kendall趋势检验方法结合植被类型数据分析研究区物候时空变化;采用偏相关方法分析物候变化与气温和降水之间的关系。结果表明：（1）米仓山地区植被生长季始期（SOS）主要集中在第80-110d,海拔每上升100m,SOS大约推迟0.6d;生长季末期（EOS）主要集中在第250-300d;生长季长度（LOS）主要集中在130-210d。除低海拔区域受人类活动影响物候波动较大外,EOS和LOS随海拔变化存在2000m分界线,其下物候随海拔升高物候明显推迟或缩短,其上物候变化趋于平缓。（2）16a来植被SOS呈提前趋势,提前幅度为0.47d/a,提前的像元占74.03%,其中,达到显著提前的像元占12.21%（P<0.1）;EOS整体呈提前趋势,提前幅度为0.22d/a;LOS略有延长,延长幅度为0.26d/a。（3）区域常绿型森林植被SOS晚于同垂直带的落叶型森林植被;草地、常绿阔叶灌木林SOS提前趋势最明显,变化率分别为-0.80、-0.71d/a;EOS提前趋势最明显的是针阔混交林和落叶阔叶林。（4） SOS主要受3月平均气温和4月降水的影响,3月平均气温升高以及4月降水增加导致SOS提前;EOS主要受10月降水的负向影响。     

陕西吴起植被动态及其与气候变化的关系

使用归一化植被指数(normalized difference vegetation index,NDVI)资料,分析了陕西省吴起县1982-2003年NDVI的演变情况及其与气候变化的关系。结果表明,22年来植被覆盖状况尽管有波动起伏,但整体在持续转好,表现在低覆盖率植被面积在减少,高覆盖率植被面积在增加;年平均NDVI与降水量呈正相关,植被覆盖的改善有利于减小风速;从季节平均值来看,春季降水量与夏季NDVI、夏季降水量与秋季NDVI的相关性均极显著(P<0.01),并且夏秋两季的降水量与年NDVI相关性也显著,说明降水量是影响吴起县植被分布状况的关键性因子;春夏季蒸发量与夏季的NDVI均呈极显著的负相关(P<0.01);春夏季相对湿度与夏季的NDVI呈极显著的正相关(P<0.01),冬季相对湿度与冬季的NDVI呈极显著的负相关(P<0.01)。     

2000—2016年云南地区植被覆盖时空变化及其对水热因子的响应

基于2000-2016年MODIS-NDVI数据,利用趋势分析法以及线性相关分析等方法对云南地区植被月变化趋势、年际变化趋势进行详细分析;探讨植被覆盖变化与主要气候水热因子的关系。结果表明：研究区大部分地区植被覆盖良好,年NDVI的平均值为0.55,其中NDVI较高值（> 0.8）区域主要分布于南部,而西北部和中部城市地区NDVI值较低;自2000年开始,研究区NDVI总体呈显著（P < 0.05）增加趋势,年NDVI的变化斜率为0.0036,植被覆盖呈增加趋势的区域占研究区总面积79.80%;不同季节（春、夏、秋、冬）和生长季的植被状况均呈良性发展趋势;湿润指数和水热综合因子在滇西北与NDVI多呈负相关,在滇中地区以正相关为主;春、夏、秋3个季节NDVI受降水影响较大,而冬季NDVI则受气温影响较大;受降水影响较大的区域主要分布在中部和南部,受气温影响较大区域主要分布在滇西北、滇东北地区;NDVI在不同月份对气候因子的滞后时间存在差异,NDVI与当月气温的相关性强于与当月降水的相关性,植被生长对气温的响应无明显滞后效应,对降水存在3个月的滞后期。     

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.     

Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere

The inter-annual shift of spring vegetation phenology relative to per unit change of preseason temperature, referred to as temperature sensitivity (days °C⁻¹), quantifies the response of spring phenology to temperature change. Temperature sensitivity was found to differ greatly among vegetation from different environmental conditions. Understanding the large-scale spatial pattern of temperature sensitivity and its underlying determinant will greatly improve our ability to predict spring phenology. In this study, we investigated the temperature sensitivity for natural ecosystems over the North Hemisphere (north of 30°N), based on the vegetation phenological date estimated from NDVI time-series data provided by the Advanced Very High Resolution Radiometer (AVHRR) and the corresponding climate dataset. We found a notable longitudinal change pattern with considerable increases of temperature sensitivity from inlands to most coastal areas and a less obvious latitudinal pattern with larger sensitivity in low latitude area. This general spatial variation in temperature sensitivity is most strongly associated with the within-spring warming speed (WWS; r = 0.35, p < 0.01), a variable describing the increase speed of daily mean temperature during spring within a year, compared with other factors including the mean spring temperature, spring precipitation and mean winter temperature. These findings suggest that the same magnitude of warming will less affect spring vegetation phenology in regions with higher WWS, which might partially reflect plants’ adaption to local climate that prevents plants from frost risk caused by the advance of spring phenology. WWS accounts for the spatial variation in temperature sensitivity and should be taken into account in forecasting spring phenology and in assessing carbon cycle under the projected climate warming.     

Simulating the onset of spring vegetation growth across the Northern Hemisphere

Changes in the spring onset of vegetation growth in response to climate change can profoundly impact climate–biosphere interactions. Thus, robust simulation of spring onset is essential to accurately predict ecosystem responses and feedback to ongoing climate change. To date, the ability of vegetation phenology models to reproduce spatiotemporal patterns of spring onset at larger scales has not been thoroughly investigated. In this study, we took advantage of phenology observations via remote sensing to calibrate and evaluated six models, including both one‐phase (considering only forcing temperatures) and two‐phase (involving forcing, chilling, and photoperiod) models across the Northern Hemisphere between 1982 and 2012. Overall, we found that the model that integrated the photoperiod effect performed best at capturing spatiotemporal patterns of spring phenology in boreal and temperate forests. By contrast, all of the models performed poorly in simulating the onset of growth in grasslands. These results suggest that the photoperiod plays a role in controlling the onset of growth in most Northern Hemisphere forests, whereas other environmental factors (e.g., precipitation) should be considered when simulating the onset of growth in grasslands. We also found that the one‐phase model performed as well as the two‐phase models in boreal forests, which implies that the chilling requirement is probably fulfilled across most of the boreal zone. Conversely, two‐phase models performed better in temperate forests than the one‐phase model, suggesting that photoperiod and chilling play important roles in these temperate forests. Our results highlight the significance of including chilling and photoperiod effects in models of the spring onset of forest growth at large scales, and indicate that the consideration of additional drivers may be required for grasslands.     

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau

The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite‐derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long‐term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm^?1. Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C^?1 (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.     

Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite‐derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green‐up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green‐up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green‐up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green‐up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green‐up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature.     

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.     

基于日光诱导叶绿素荧光的北半球森林物候研究

植被物候是反映植被生长规律的重要指标, 对气候的反馈具有重要意义。日光诱导叶绿素荧光(SIF)通过复杂的能量耗散机制与光合作用相关联, 提供了从空间直接探测大范围植被物候的可能性。为了探究气候变化背景下SIF反演不同森林类型物候的适用性, 该文以北半球35个全球通量网(FLUXNET)森林站点为研究对象, 利用2007-2014年SIF值和总初级生产力(GPP)通过双逻辑生长模型和动态阈值法来估算3种典型森林类型的物候, 并采用相关性分析等方法评价SIF在估算不同森林类型物候时的差异性。主要结果为: 1) SIF对生长季开始时间(SOS)的估算精度高于生长季结束时间(EOS); 2) SIF能够更准确地估算混交林(MF)的SOS, 但是不能精确追踪落叶阔叶林(DBF)和常绿针叶林(ENF)的SOS; 3)春季季前短波辐射是驱动SOS的主要气候因素。综上, 建议在将来的研究中将SIF数据与其他遥感指数整合, 应用于不同植物类型的物候监测。     

Onset of spring starting earlier across the Northern Hemisphere

Recent warming of Northern Hemisphere (NH) land is well documented and typically greater in winter/spring than other seasons. Physical environment responses to warming have been reported, but not details of large‐area temperate growing season impacts, or consequences for ecosystems and agriculture. To date, hemispheric‐scale measurements of biospheric changes have been confined to remote sensing. However, these studies did not provide detailed data needed for many investigations. Here, we show that a suite of modeled and derived measures (produced from daily maximum–minimum temperatures) linking plant development (phenology) with its basic climatic drivers provide a reliable and spatially extensive method for monitoring general impacts of global warming on the start of the growing season. Results are consistent with prior smaller area studies, confirming a nearly universal quicker onset of early spring warmth (spring indices (SI) first leaf date, ?1.2 days decade^?1), late spring warmth (SI first bloom date, ?1.0 days decade^?1; last spring day below 5°C, ?1.4 days decade^?1), and last spring freeze date (?1.5 days decade^?1) across most temperate NH land regions over the 1955–2002 period. However, dynamics differ among major continental areas with North American first leaf and last freeze date changes displaying a complex spatial relationship. Europe presents a spatial pattern of change, with western continental areas showing last freeze dates getting earlier faster, some central areas having last freeze and first leaf dates progressing at about the same pace, while in portions of Northern and Eastern Europe first leaf dates are getting earlier faster than last freeze dates. Across East Asia last freeze dates are getting earlier faster than first leaf dates.     

上海市气候变化和人类活动对植被物候的影响

植被物候是气候和自然环境变化的综合指示器,同时也是研究植物生长发育与气候变化的重要参数。随着经济社会的发展夜间灯光兼具指示人类活动信息和光照强度的特点,成为研究城市生态系统和生态建设的热点。基于此,利用地理探测器分析方法和变量投影重要性指标,从时间和空间尺度上探究温度、降水、辐射和夜间灯光对2001—2020年上海市植被物候进行时空变化分析和归因分析,并结合城区和郊区的差异进一步分析夜间灯光和环境因子对物候的影响贡献。结果表明：2001—2020年上海市城区温度高于郊区约0.63℃,春季物候(start growth of season, SOS)提前郊区10d左右,秋季物候(end growth of season, EOS)推迟郊区7d左右,夜间灯光高于郊区2.9倍并且其重心向沿海方向显著偏移。空间尺度上夜间灯光对SOS的影响权重最大(q=0.15),并且辐射∩夜间灯光的组合驱动对城区和郊区的植被物候影响权重均最大(q_max=0.29)。时间尺度上SOS与温度的关系最密切,且随温度的增加而提前(平均R_温度=-0.24),EOS与夜间灯光的...