Driving force and changing trends of vegetation phenology in the Loess Plateau of China from 2000 to 2010

Changes in vegetation phenology are key indicators of the response of ecosystems to climate change. Therefore, knowledge of growing seasons is essential to predict ecosystem changes, especially for regions with a fragile ecosystem such as the Loess Plateau. In this study, based on the normalized difference vegetation index (NDVI) data, we estimated and analyzed the vegetation phenology in the Loess Plateau from 2000 to 2010 for the beginning, length, and end of the growing season, measuring changes in trends and their relationship to climatic factors. The results show that for 54.84% of the vegetation, the trend was an advancement of the beginning of the growing season (BGS), while for 67.64% the trend was a delay in the end of the growing season (EGS). The length of the growing season (LGS) was extended for 66.28% of the vegetation in the plateau. While the temperature is important for the vegetation to begin the growing season in this region, warmer climate may lead to drought and can become a limiting factor for vegetation growth. We found that increased precipitation benefits the advancement of the BGS in this area. Areas with a delayed EGS indicated that the appropriate temperature and rainfall in autumn or winter enhanced photosynthesis and extended the growth process. A positive correlation with precipitation was found for 76.53% of the areas with an extended LGS, indicating that precipitation is one of the key factors in changes in the vegetation phenology in this water-limited region. Precipitation plays an important role in determining the phenological activities of the vegetation in arid and semiarid areas, such as the Loess Plateau. The extended growing season will significantly influence both the vegetation productivity and the carbon fixation capacity in this region.     

青藏高原典型植被生长季遥感模型提取分析

物候变化是衡量全球气候变化最直接、敏感的指示器,针对青藏高原这个独特地域单元上特殊的高寒植被进行关键物候期遥感提取模型及植被物候时空变化的研究具有重要的意义。本文首先以反距离加权空间插值算法与Savitzky-Golay滤波算法相结合的数据重建模型获得高质量2003-2012年青藏高原MODIS归一化植被指数(NDVI)数据。在此数据基础上,分别利用动态阈值法、最大变化斜率法、logistic曲线拟合法3种遥感植被生长季提取模型,对青藏高原地区两种典型植被的生长季(SOS生长季开始期,EOS生长季结束期,LOS生长季长度)进行提取。通过对3种模型提取结果的对比分析,并结合日均温模型对提取结果的验证发现,动态阈值法为青藏高原地区典型植被生长季的最优遥感提取模型。该模型对近10 a的高分辨率典型高寒植被物候参量的反演及时空变化特征分析表明,受青藏高原水热及海拔梯度的影响,青藏高原植被物候变化呈现出从东南向西北的空间分异规律,随春季温度的升高,近10 a来青藏高原高寒草地总体呈现生长季开始期(SOS)提前(0.248 d/a)的趋势。     

Effect of Mathematical Expression of Vegetation Indices on the Estimation of Phenology Trends from Satellite Data

Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date(SOS) and end date(EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.     

Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012

The influence of climate change on vegetation phenology is a heated issue in current climate change study. We used GIMMS-3g NDVI data to detect the spatio-temporal dynamics of the start of the growing season (SGS) over the Tibetan Plateau (TP) from 1982 to 2012 and to analyze its relationship with temperature and precipitation. No significant trend was observed in the SGS at the regional scale during the study period (R ² = 0.03, P = 0.352). However, there were three time periods (1982-1999, 1999-2008 and 2008-2012) with identifiable, distinctly different trends. Regions with a significant advancing trend were mainly scattered throughout the humid and semi-humid areas, whereas the regions with a significant delaying trend were mostly distributed throughout the semi-arid areas. Statistical analysis showed that the response of the SGS to climate change varies spatially. The SGS was significantly correlated with the spring temperature and the start of the thermal growth season (STGS) in the relatively humid area. With increasing aridity, the importance of the spring temperature for the SGS gradually decreased. However, the influences of precipitation and winter temperature on the SGS were complicated across the plateau.     

Effect of topography and accessibility on vegetation dynamic pattern in Mountain-hill Region

Knowledge of both vegetation distribution pattern and phenology changes is very important.Their complicated relationship with elevation and accessibility were explored through a geographically weighted regression(GWR) framework in Fujian province,China.The 16-day time series of 250 m Moderate Resolution Imaging Spectroradiometer(MODIS) Enhanced Vegetation Index(EVI) dataset from 2000 to 2010 was applied.Wavelet transform method was adopted to decompose the original time series and construct the annual maximum EVI and amplitude of the annual phenological cycle(EVI).Candidate explaining factors included topographic conditions,accessibility variables and proportions of primary vegetation types.Results revealed very strong positive influence from parameters of elevation and accessibility to big rivers and negative effect from accessibility to resident on both maximum EVI and phenological magnitude through ordinary linear least square(OLS) regression analysis.GWR analysis revealed that spatially,the parameters of topography and accessibility had a very complex relationship with both maximum EVI and phenology magnitude,as a result of the various combinations of environmental factors,vegetation composition and also intensive anthropogenic impact.Apart from the continuously increasing trend of phenology magnitude with increasing altitude,the influence of topography and accessibility on maximum EVI and phenological magnitude generally decreased,even from strongly positive to negative,with increasing altitude or distance.Specially,the most rapid change of correlation coefficient between them was observed within a low elevation or close distance;less variation was discovered within a certain range of medium altitude or distance and their relationship might change above this range.Non-stationary approaches are needed to better characterize the complex vegetation dynamic pattern in Mountain-hill Region.     

青藏高原月NDVI时空动态变化及其对气候变化的 响应

青藏高原脆弱的高寒植被对外界干扰十分敏感,使其成为研究植被对气候变化响应的理想区域之一。青藏高原气候变化剧烈,在较短的合成时间研究气候变化对植被的影响十分必要。因此,本文利用GIMMS NDVI时间序列数据集,研究了1982-2012年青藏高原生长季月尺度植被生长的时空动态变化,探讨了其与气温、降水量和日照时数等气候因子的响应关系。结果表明：在区域尺度上,除8月外,其他各月份植被均呈增加趋势,显著增加多发生在4-7月和9月;大部分月份的NDVI增加速率随着时段的延长显著减小,表明NDVI增加趋势放缓;在像元尺度上,月NDVI显著变化的区域多呈增加趋势,但显著减少范围的扩张多快于显著增加。4月和7月植被生长主要是受气温和日照时数共同作用,6月和9月受气温的控制,而8月则主要受降水量的影响。长时间序列NDVI数据集的出现为采用嵌套时段研究植被生长变化趋势奠定了前提,而植被活动变化趋势的持续性则有助于形象表征植被活动变化过程、深入理解植被对气候变化的响应和预测植被未来生长变化趋势。由此推测,青藏高原月NDVI未来增加趋势总体上趋于缓和,但在像元尺度显著变化的区域趋于增加。     

南方亚热带季风区将乐县森林植被动态变化及其对气候变化的响应

在全球气候变化背景下,植被动态变化以及植被对气候变化的响应方式已经成为生态学和地理学领域的热点。本文对比分析了南方亚热带季风区将乐县不同类型森林植被对不同时间尺度的干旱响应的差别。基于2000-2017年MODIS-EVI数据及气象站点数据,用最大值合成法、趋势分析法以及相关分析法,分析了森林植被及气象因子的动态变化特征,并对比不同森林植被对气候变化响应的差别。研究表明：① 2000-2017年,研究区植被覆盖度、EVI和降水均显著增加,区域内湿度增加,森林长势渐趋良好;② EVI在生长季初期和末期与同期的降水、温度均显著正相关（P<0.1）,初期森林受降水因子的影响更大,末期受温度因子的影响大;③ 1-3月和周年的气候变化对森林的生长至关重要,长时间尺度的湿度增加对森林生长具有显著的促进作用,SPEI的时间尺度越长与EVI的相关性也越大;④ 针阔混交林与同期温度、降水的相关系数最高,并且与不同时间尺度的SPEI相关性均比较高,属于气候敏感型林型,在生产经营中要谨慎预防气候变化对该林型带来的伤害;⑤ 森林覆盖度变化与降水和SPEI_24的相关性极显著,长时间尺度的降水变化是影响森林植被覆盖率变化的重要因素之一。     

Vegetation cover variation in the Qilian Mountains and its response to climate change in 2000–2011

An understanding 0f variati0ns in vegetati0n c0ver in resp0nse t0 climate change is critical f0r predicting and managing future terrestrial ec0system dynamics. Because scientists anticipate that m0untain ec0systems will be m0re sensitive t0 future climate change c0mpared t0 0thers, 0ur 0bjectives were t0 investigate the impacts 0f climate change 0n variati0n in vegetati0n c0ver in the Qilian M0untains （QLM）, China, between 2000 and 2011. T0 acc0mplish this, we used linear regressi0n techniques 0n 250-m MODIS N0rmalized Difference Vegetati0n Index （NDVI） datasets and mete0r0l0gical rec0rds t0 determine spati0temp0ral variability in vegetati0n c0ver and climatic fact0rs （i.e. temperature and precipitati0n）. Our results sh0wed that temperatures and precipitati0n have increased in this regi0n during 0ur study peri0d. In additi0n, we f0und that gr0wing seas0n mean NDVI was mainly distributed in the vertical z0ne fr0m 2,700 m t0 3,600 m in elevati0n. In the study regi0n, we 0bserved significant p0sitive and negative trends in vegetati0n c0ver in 26.71% and 2.27% 0f the vegetated areas. C0rrelati0n analyses indicated that rising precipitati0n fr0m May t0 August was resp0nsible f0r increased vegetati0n c0ver in areas with p0sitive trends in gr0wing seas0n mean NDVI. H0wever, there was n0 similar significant c0rrelati0n between gr0wing seas0n mean NDVI and precipitati0n in regi0ns where vegetati0n c0ver declined thr0ugh0ut 0ur study peri0d. Using spatial statistics, we f0und that veeetati0n c0ver freauentlvdeclined in areas within the 2,500-3,100 m vertical z0ne, where it has steep sl0pe, and is 0n the sunny side 0f m0untains. Here, the p0sitive influences 0f increasing precipitati0n c0uld n0t 0ffset the drier c0nditi0ns that 0ccurred thr0ugh warming trends. In c0ntrast, in higher elevati0n z0nes （3,900-4,500 m） 0n the shaded side 0f the m0untains, rising temperatures and increasing precipitati0n impr0ved c0nditi0ns f0r vegetati0n gr0wth. Increased precipitati0n als0 facilitated vegetati0n gr0wth in areas experiencing warming trends at l0wer elevati0ns （2,000-2,400 m） and 0n l0wer sl0pes where water was m0re easily c0nserved. We suggest that spatial differences in variati0n in vegetati0n as the result 0f climate change depend 0n l0cal m0isture and thermal c0nditi0ns, which are mainly c0ntr0lled by t0p0graphy （e.g. elevati0n, aspect, and sl0pe）, and 0ther fact0rs, such as l0cal hydr0l0gy.     

Multilevel assessment of spatiotemporal variability of vegetation in subtropical mountain-hill region

The complex spatiotemporal vegetation variability in the subtropical mountain-hill region was investigated through a multi-level modeling framework. Three levels - parcel, landscape, and river basin levels- were selected to discover the complex spatiotemporal vegetation variability induced by climatic, geomorphic and anthropogenic processes at different levels. The wavelet transform method was adopted to construct the annual maximum Enhanced Vegetation Index and the amplitude of the annual phenological cycle based on the 16-day time series of a5om Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index datasets during 2OOl-2OlO. Results revealed that land use strongly influenced the overall vegetation greenness and magnitude of phenological cycles. Topographic variables also contributed considerably to the models, reflecting the positive influence from altitude and slope. Additionally, climate factors played an important role： precipitation had a considerable positive association with the vegetation greenness, whereas the temperature difference had strong positive influence on the magnitude of vegetation phenology. The multilevel approach leads to a better understanding of the complex interaction of the hierarchical ecosystem, human activities and climate change.     

Extracting vegetation phenology metrics in Changbai Mountains using an improved logistic model

Remotely sensing images are now available for monitoring vegetation dynamics over large areas.In this paper,an improved logistic model that combines double logistic model and global function was developed.Using this model with SPOT/NDVI data,three key vegetation phenology metrics,the start of growing season (SOS),the end of growing season (EOS) and the length of growing season (LOS),were extracted and mapped in the Changbai Mountains,and the relationship between the key phenology metrics and elevation were ...     

2000-2013年三江源植被NDVI变化趋势及影响因素分析

基于2000-2013年三江源MODIS NDVI数据,本文系统地分析了三江源植被生长季累计NDVI的时空变化特征,并结合三江源生态保护与建设工程实施的相关统计数据,探讨了人类活动对三江源植被变化的影响,最后通过气候因子与生长季累计NDVI的相关性分析,揭示了影响三江源不同地区植被变化的主要气候限制因素。结果表明,2000-2013年三江源植被NDVI整体上呈增加趋势,NDVI明显增加的区域面积比例达17.84%,主要分布于研究区的西部和北部;明显减少的区域仅占0.78%,多零星分布于研究区中部;NDVI变化稳定或没有显著变化趋势的区域面积比例为59.64%,主要位于研究区东部和南部。三江源生态保护与建设工程的实施虽然促进了植被恢复,但对区域植被整体变化的影响有限,研究时段内区域植被整体好转主要受气候因素控制。西部长江源区的植被生长主要受气温影响,东北部黄河源区主要受降水制约,南部澜沧江源区降水和气温的限制性均不明显。     

Dynamics and responses of vegetation to climatic variations in Ziya-Daqing basins,China

Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) data and meteorological data(temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase(especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1℃, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass.     

Impacts of warming on root biomass allocation in alpine steppe on the north Tibetan Plateau

Biomass is an important component of global carbon cycling and is vulnerable to climate change. Previous studies have mainly focused on the responses of aboveground biomass and phenology to warming, while studies of root architecture and of root biomass allocation between coarse and fine roots have been scarcely reported in grassland ecosystems. We conducted an open-top-chamber warming experiment to investigate the effect of potential warming on root biomass and root allocation in alpine steppe on the north Tibetan Plateau. The results showed that Stipa purpurea had significantly higher total root length, root surface area and tips than Carex moocroftii. However,there were no differences in total root volume, mean diameter and forks for the two species. Warming significantly increased total root biomass(27.60%), root biomass at 0–10 cm depth(27.84%) and coarse root biomass(diameter 0.20 mm, 57.68%) in the growing season(August). However, warming had no significant influence on root biomass in the non-growing season(April). Root biomass showed clear seasonalvariations: total root biomass, root biomass at 0–10 cm depth and coarse root biomass significantly increased in the growing season. The increase in total root biomass was due to the enhancement of root biomass at 0–10 cm depth, to which the increase of coarse root biomass made a great contribution. This research is of significance for understanding biomass allocation, carbon cycling and biological adaptability in alpine grassland ecosystems under future climate change.     

京津冀地区NDVI变化及气候因子驱动分析

植被覆盖动态监测及与气候变化的响应,是陆地生态系统研究的重要内容。本文以2001-2013年间京津冀地区MOD13A 3月合成NDVI数据,结合生长季的降水和气温资料,运用偏相关和复相关分析、趋势分析方法,研究了该区域NDVI的变化特征和空间分布,以及其区域植被覆盖变化的气候驱动力。结果表明,该区域NDVI最大值在13a间缓慢增加,植被覆盖呈现改善趋势;NDVI和生长季降雨量及平均气温的平均偏相关系数分别为0.20和-0.14,表明在年际变化水平上,京津冀地区NDVI总体与降水量呈正相关,与平均气温呈负相关,且降水对NDVI的影响大于温度对NDVI的影响。对植被覆盖驱动分区得出,降水和气温驱动型占区域面积的5.68%;单独降水驱动型和气温驱动型分别占4.51%、0.18%;区域内植被覆盖变化主要受非气候因子驱动型为主,所占比例为89.63%,表明人类活动对植被变化的影响巨大。     

融合植被遥感数据的北京市次日花粉浓度预测

中国国土绿化状况公报指出,2010—2020年中国许多城市的绿化面积增加、绿化质量提高,可随之而来的影响人体健康的致敏性花粉风险也逐渐提高。本文利用遥感手段获得北京市乔木和草地生长区域平均植被叶面积指数（LAI）时间序列作为植被物候信息,并将其作为花粉浓度预测因子之一,结合日气象数据,使用具有外部输入的非线性自回归神经网络模型（NARXnet）,进行北京市次日花粉浓度的预测。结果显示：① 通过逐步回归计算,对于春季数据,日均气温3日平滑,积温,叶面积指数（LAI）和叶面积指数一阶导为次日花粉浓度预测的关键变量;对于秋季数据,日均气温、平均风速、最低日气温、日均气温3日平滑、积温和叶面积指数（LAI）为次日花粉浓度预测的关键变量;② 加入遥感物候信息可显著地提高NARXnet模型的春秋时段的花粉浓度的预测精度。使用本文提出的结合叶面积指数的NARX模型后,预测模型的总体精度为71%。由此,本研究认为在原有气象因子的基础上,辅之以用遥感技术手段获取的大面积植被物候信息,如叶面积指数动态,可作为预测次日花粉浓度的一种有效手段。     

亚热带福建省森林生长季与气温、降水相关性的遥感分析

植物生长季的变化反映了全球气候变化对生态环境的影响。本研究以2000-2006年间MODIS-NDVI影像数据集,使用TIMESAT软件从归一化植被指数（NDVI）时间序列中,分别提取福建省不同森林植被的生长季开始日期（Start of Season,SOS）、生长季结束日期（End of Season,EOS）和生长季长度（Length of season,LOS）等物候参数,并与全省尺度的气温与降水量进行相关分析。结果表明：不同森林类型NDVI与当月月均气温之间具有较显著的相关性（R²为0.72-0.79,p<0.01）,同期温度变化对植被生长的影响相对于降水量更重要;而植被生长对降水量的响应存在大约2个月的时滞效应（R²为0.54-0.75,p<0.01）,说明前期的降水累积对于后续植被生长有较显著影响。福建省森林植被生长季持续时间约213~223 d,开始于每年4月初到4月中旬（第98~103 d）,结束于11月中旬前后（第316~321 d）。其中,南亚热带森林生长季长于中亚热带森林,相同气候条件下的阔叶林生长季时间略长于针叶林。另外,春季（2-4月）气温变化是导致福建省内2个气候带森林生长季开始时间、生长季结束时间及生长季长度变化的关键因素,而伴随春季温度升高,植被生长季开始时间提前（R²为0.83,p<0.01）,同时生长季长度延长（R²为0.80,p<0.01）。7 a间,生长季持续时间呈现微弱延长趋势,总体延长幅度为2.4~3.1 d。     

2002-2012年青藏高原积雪物候变化及其对气候的响应

积雪是地表最活跃的自然要素之一,其动态变化对气候、环境以及人类生活都产生了重要影响。本文利用MODIS积雪产品和IMS雪冰产品,首先通过Terra、Aqua双星合成和临近日合成去除MODIS积雪产品中的部分云像元,再与IMS融合,获取了青藏高原2002-2012年逐日无云积雪覆盖产品,并逐像元计算每个水文年的积雪覆盖日数（SCD）、积雪开始期（SCS）和积雪结束期（SCE）,分析了不同生态分区积雪的时空变化特征,以及积雪开始期和结束期与温度、降水的关系。结果表明：青藏高原积雪分布存在明显的空间差异,南部喜马拉雅山脉和念青唐古拉山地区以及西部帕米尔高原和喀喇昆仑山脉为SCD的2个高值区,年均积雪日数在200 d以上。18.1%的区域SCS表现出明显的提前趋势,主要集中在青藏高原中东部;羌塘高原南部、念青唐古拉山西段以及川西地区有显著推迟趋势,占高原面积的8.5%。23.2%的区域SCE显著推迟,主要集中在果洛那曲高寒区、昆仑山区和念青唐古拉山地区;而仅有6.9%的区域表现出提前趋势,主要分布在高原西南部。总体上,不同生态单元内积雪开始与结束期受温度、降水的影响差异很大,表现出不同的空间格局与演变趋势。     

新疆五彩湾矿区开发对荒漠植被的扰动分析

荒漠露天矿区植被受损评估及环境修复是近年研究的热点方向。为了研究新疆五彩湾地区矿产开发对矿区及周边荒漠植被的扰动影响,采用1990-2017年90景Landsat数据分析煤矿开发前后矿区及周边荒漠植被的时空变化特征,并定量分析矿区植被长势对气候变化、矿区扩张的响应。结果表明：① 2006-2013年矿区植被所受的扰动最大,在周边植被长势转好的情形下出现明显的退化,在1990-2006年和2014-2017年,扰动较小,矿区与周边植被长势变化一致;② 生长季的月度NDVI分析显示,矿区中心样区的植被经历了一个先退化后恢复的过程;③ 矿区开发对周边植被长势的扰动距离分别为“西-东”方向的-17~21 km和“南-北”方向的-13~23 km,其中2013年对植被的干扰距离最大;④ 冬春季降水是五彩湾矿区及周边植被长势转好的主要因素,虽然矿区一直处于扩张的状态,然而随着降水的增加和矿尘防护措施的加强,2014年来矿区植被长势转好,与周边植被变化趋于一致。本文的研究为干旱区露天煤矿及周边荒漠植被变化动态监测及矿区开采的扰动范围提供了准确的数据支持,便于矿区管理者合理制定相关环保法规及矿区管理办法,实施相关环境保护和污染控制等措施。     

Rangeland privatization and its impacts on the Zoige wetlands on the Eastern Tibetan Plateau

The high Zoige Basin （Ruoergai Plateau） on the eastern Tibetan Plateau is a fault depression formed during intensive uplifting of the Tibetan Plateau. The wetland is globally important in biodiversity and is composed of marshes, bogs, fens, wet meadows and shallow water interspersed with low hills and sub-alpine meadows. Most of the Zoige wetlands have long been one of the most important grazing lands in China. Recent rangeland policy has allowed grazing, and usable wetland areas have been being legally allocated to individuals or groups of households on a long-term lease basis. Privatizafion of the wetland has impacted the Zoige wetlands in aspects of hydrologic condition, landscape and biodiversity. The uneven spatial distribution of water resources onprivatelands has led to the practice of extracting ground water, which has decreased the perched water table in Zoige. Fencing off the rangelands and grazing on expanding sand dunes have affected landscapes. Variation in the water table has led to the changes in vegetation diversity, resulting in the changes in wildlife and aquatic diversities and ecosystem processes. Making use all year round of the pasture that was previously grazed only in summer has shrunk the daily activity space of wildlife, and the newly erected fences blocked the movement of wild animals looking for food in the snow to lower and open areas. To maintain the favorable conditions of the Zoige wetland ecosystem, the author suggests that, in addition to biophysical research and implementation of conservation practices, there is an immediate need to initiate an integrated management program, increase public awareness of wetland functions and provide better training for the local conservation staff.     

Alpine tundra species phenology is mostly driven by climate-related variables rather than by photoperiod

The study of plant phenology has frequently been used to link phenological events to various factors, such as temperature or photoperiod.In the high-alpine environment, proper timing of the phenological cycle has always been crucial to overcome harsh conditions and potential extreme events(i.e. spring frosts) but little is known about the response dynamics of the vegetation, which could shape the alpine landscape in a future of changing climate. Alpine tundra vegetation is composed by an array of species belonging to different phytosociological optima and with various survival strategies, and snowbed communities are a relevant expression of such an extreme-climate adapted flora.We set eight permanent plots with each one in a snowbed located on the Cimalegna plateau in Northwestern Italy and then we selected 10 most recurring species among our plots, all typical of the alpine tundra environment and classified in 3different pools: snowbed specialists, grassland species and rocky debris species. For 3 years we registered the phenophases of each species during the whole growing season using an adaptation of the BBCH scale. We later focused on the three most biologically relevant phenophases, i.e., flower buds visible, full flowering, and beginning of seed dispersion. Three important season-related variables were chosen to investigate their relationship with the phenological cycle of the studied species:(i) the Day Of Year(DOY),the progressive number of days starting from the 1 st of January, used as a proxy of photoperiod,(ii) Days From Snow Melt(DFSM), selected to include the relevance of the snow dynamics, and(iii) Growing Degree Days(GDD), computed as a thermal sum. Our analysis highlighted that phenological development correlated better with DFSM and GDD than with DOY.Indeed, models showed that DOY was always a worse predictor since it failed to overcome interannual variations, while DFSM and marginally GDD were better suited to predict the phenological development of most of the species, despite differences intemperature and snowmelt date among the three years. Even if the response pattern to the three variables was mainly consistent for all the species, the timing of their phenological response was different.Indeed, species such as Salix herbacea and Ranunculus glacialis were always earlier in the achievement of the phenophases, while Agrostis rupestris and Euphrasia minima developed later and the remaining species showed an intermediate behavior. However, we did not detect significant differences among the three functional pools of species.