中国东部温带植被生长季节的空间外推估计

利用地面植物物候和遥感归一化差值植被指数（NDVI）数据,以及一种物候-遥感外推方法,实现植被生长季节从少数站点到较多站点的空间外推。结果表明：（1）在1982～1993年期间,中国东部温带地区植被生长季节多年平均起讫日期的空间格局与春季和秋季平均气温的空间格局相关显著;（2）在不同纬度带和整个研究区域,植被生长季节结束日期呈显著推迟的趋势,而开始日期则呈不显著提前的趋势,这与欧洲和北美地区植被生长季节开始日期显著提前而结束日期不显著推迟的变化趋势完全不同;（3）北部纬度带的植被生长季节平均每年延长1．4～3．6d,全区的植被生长季节平均每年延长1．4d,与同期北半球和欧亚大陆植被生长季节延长的趋势数值相近;（4）植被生长季节结束日期的显著推迟与晚春至夏季的区域性降温有关,而植被生长季节开始日期的不显著提前则与晚冬至春季气温趋势的不稳定变化有关;（5）在年际变化方面,植被生长季节开始和结束日期分别与2～4月份平均气温和5～6月份平均气温呈负相关关系。     

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.     

Impacts of snow cover duration on vegetation spring phenology over the Tibetan Plateau

Aims Snow cover occupies large percentage of land surface in Tibetan Plateau. Snow cover duration (SCD) during non-growing seasons plays a critical role in regulating alpine vegetation’s phenology by affecting the energy budgets of land surface and soil moisture conditions. Different period’s snow cover during non-growing season may have distinct effect on the vegetation’s phenology. Start of season (SOS) has been observed advanced under the ongoing climate change in the plateau, but it still remains unclear how the SCD alters the SOS. This study attempts to answer the following questions: (i) What is the pattern of spatial and temporal variations for SCD and grassland SOS? (ii) Which period’s SCD plays a critical role in grassland’s SOS?     

Change in winter snow depth and its impacts on vegetation in China

Snow on land is an important component of the global climate system, but our knowledge about the effects of its changes on vegetation are limited, particularly in temperate regions. In this study, we use daily snow depth data from 279 meteorological stations across China to investigate the distribution of winter snow depth (December–February) from 1980 to 2005 and its impact on vegetation growth, here approximated by satellite‐derived vegetation greenness index observations [Normalized Difference Vegetation Index (NDVI)]. The snow depth trends show strong geographical heterogeneities. An increasing trend (>0.01 cm yr^?1) in maximum and mean winter snow depth is found north of 40°N (e.g. Northeast China, Inner Mongolia, and Northwest China). A declining trend (?1) is observed south of 40°N, particularly over Central and East China. The effect of changes in snow depth on vegetation growth was examined for several ecosystem types. In deserts, mean winter snow depth is significantly and positively correlated with NDVI during both early (May and June) and mid‐growing seasons (July and August), suggesting that winter snow plays a critical role in regulating desert vegetation growth, most likely through persistent effects on soil moisture. In grasslands, there is also a significant positive correlation between winter snow depth and NDVI in the period May–June. However, in forests, shrublands, and alpine meadow and tundra, no such correlation is found. These ecosystem‐specific responses of vegetation growth to winter snow depth may be due to differences in growing environmental conditions such as temperature and rainfall.     

Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China

Using phenological and normalized difference vegetation index (NDVI) data from 1982 to 1993 at seven sample stations in temperate eastern China, we calculated the cumulative frequency of leaf unfolding and leaf coloration dates for deciduous species every 5 days throughout the study period. Then, we determined the growing season beginning and end dates by computing times when 50% of the species had undergone leaf unfolding and leaf coloration for each station year. Next, we used these beginning and end dates of the growing season as time markers to determine corresponding threshold NDVI values on NDVI curves for the pixels overlaying phenological stations. Based on a cluster analysis, we determined extrapolation areas for each phenological station in every year, and then implemented the spatial extrapolation of growing season parameters from the seven sample stations to all possible meteorological stations in the study area. Results show that spatial patterns of growing season beginning and end dates correlate significantly with spatial patterns of mean air temperatures in spring and autumn, respectively. Contrasting with results from similar studies in Europe and North America, our study suggests that there is a significant delay in leaf coloration dates, along with a less pronounced advance of leaf unfolding dates in different latitudinal zones and the whole area from 1982 to 1993. The growing season has been extended by 1.4–3.6 days per year in the northern zones and by 1.4 days per year across the entire study area on average. The apparent delay in growing season end dates is associated with regional cooling from late spring to summer, while the insignificant advancement in beginning dates corresponds to inconsistent temperature trend changes from late winter to spring. On an interannual basis, growing season beginning and end dates correlate negatively with mean air temperatures from February to April and from May to June, respectively.     

2000-2021年青藏高原生长季植被敏感性的时空变异

为揭示青藏高原陆地生态系统对气候变化敏感性的时空变异性,基于植被敏感性指数(Vegetation Sensitivity Index, VSI),使用2000—2021年青藏高原6—8月生长季MODIS EVI和ERA5再分析资料的温度、降水和太阳辐射数据,首先探究了22年里青藏高原陆地生态系统敏感性的空间变异性及其主要气候驱动因素,其次探究了青藏高原VSI在P₁(2000—2006年)、P₂(2007—2013年)和P₃(2014—2021年)时期内VSI的时间变异性,研究表明：(1)2000—2021年青藏高原生长季VSI的空间异质性较强,其中东南部灌木和森林的VSI较高,而西北部高山荒漠、高山草原和高山草甸的VSI较低;(2)22年里温度、降水和太阳辐射分别主导着青藏高原55.89%、19.24%和24.87%地区的VSI变化,其中温度主导着东南部灌木和森林的VSI,降水主导着东北大部分地区高山草甸的VSI,而太阳辐射主导着西南大部分地区高山草原的VSI。时间变异性结果表明：(3)P₁—P     

Uneven winter snow influence on tree growth across temperate China

Winter snow is an important driver of tree growth in regions where growing‐season precipitation is limited. However, observational evidence of this influence at larger spatial scales and across diverse bioclimatic regions is lacking. Here, we investigated the interannual effects of winter (here defined as previous October to current February) snow depth on tree growth across temperate China over the period of 1961–2015, using a regional network of tree ring records, in situ daily snow depth observations, and gridded climate data. We report uneven effects of winter snow depth on subsequent growing‐season tree growth across temperate China. There shows little effect on tree growth in drier regions that we attribute mainly to limited snow accumulation during winter. By contrast, winter snow exerts important positive influence on tree growth in stands with high winter snow accumulation (e.g., in parts of cold arid regions). The magnitude of this effect depends on the proportion of winter snow to pre‐growing‐season (previous October to current April) precipitation. We further observed that tree growth in drier regions tends to be increasingly limited by warmer growing‐season temperature and early growing‐season water availability. No compensatory effect of winter snow on the intensifying drought limitation of tree growth was observed across temperate China. Our findings point toward an increase in drought vulnerability of temperate forests in a warming climate.     

中国植被生长期的时空变化

基于822个气象站点1951—2017年的日均温度数据,采用世界气象组织给定的植被生长期(GSL)定义,利用Slope、Mann-Kendall和Hurst指数分析中国各省(区)不同时期的GSL变化趋势及相应时期150、200、250、300和350 d的GSL等值线移动速度。结果表明: 研究期间中国北方地区GSL变化显著。GSL增长速度表现为北方快于南方、高海拔快于低海拔。中国大部分地区未来GSL变化趋势与当前的变化趋势相同。北方绝大部分省(区)GSL增长速度在0.1~0.2 d·a^-1,西藏的增速最快,为0.44 d·a^-1。1981—2000年是中国各省(区)GSL变化最显著的时段。除新疆GSL延长是生长期终日(GSE)主导外,其他各省(区)GSL延长总体是生长期始日(GSS)占主导。在高纬度和高海拔省(区),GSL变化对年均温度的变化更敏感。年均温越高的省(区)GSL也普遍越长。1951年以来,中国150、200、250、300和350 d的GSL等值线出现了明显移动,东北地区200 d等值线的移动速度最快,其平均北移速度为6.11 km·a^-1。中国GSL等值线总体移动规律为:等值线数值越大,北移速度越慢。其中,350 d等值线在部分区段甚至出现了南移的情况。中国GSL延长将导致农作物种植边界北移,自然植被生长期延长。该变化对中国农作物的品质、产量和生态系统碳固定的影响还有待深入研究。     

林下植被和凋落物对寒温带森林生长季土壤CH4通量的影响

为进一步探究林下植被和凋落物管理对我国寒温带森林生长季土壤CH₄通量的影响,采用静态箱-气相色谱法对大兴安岭北部4种林型（白桦林、山杨林、樟子松林和兴安落叶松林）4种处理（自然状态、去除凋落物、去除林下植被以及去除林下植被和凋落物）的土壤CH₄通量排放特征进行观测研究。结果表明：该地区森林生长季土壤均表现为CH₄的汇,4种林型不同处理后土壤CH₄通量表现为单峰变化趋势,吸收峰值出现在7月或8月。自然状态4种林型土壤CH₄平均吸收通量表现为白桦林（-79.23±14.92）μg m^-2 h^-1>山杨林（-64.27±9.60）μg m^-2 h^-1>樟子松林（-62.54±15.48）μg m^-2 h^-1>兴安落叶松林（-48.73±12.26）μg m^-2 h^-1,兴安落叶松土壤CH₄平均吸收通量显著小于其他三种林型（P<0.05）。相比于自然状态,4种林型在去除凋落物后土壤CH₄吸收通量提高了2.12%-12.15%,但变化幅度均没有达到显著水平（P>0.05）。去除林下植被后4种林型CH₄吸收通量提高了0.84%-20.55%,且只有山杨林吸收增加达到显著水平（P<0.05）。同时去除林下植被和凋落物后,对白桦林和樟子松土壤CH₄通量影响不显著（P>0.05）,但对山杨林和兴安落叶松林影响显著（P<0.05）。总之,去除凋落物或林下植被均会提高土壤对CH₄吸收,去除林下植被对土壤CH₄通量的影响要大于去除凋落物的影响,但不同林型不同处理之间还存在差异。     

Variations in satellite-derived phenology in China's temperate vegetation

The relationship between vegetation phenology and climate is a crucial topic in global change research because it indicates dynamic responses of terrestrial ecosystems to climate changes. In this study, we investigate the possible impact of recent climate changes on growing season duration in the temperate vegetation of China, using the advanced very high resolution radiometer (AVHRR)/normalized difference vegetation index (NDVI) biweekly time-series data collected from January 1982 to December 1999 and concurrent mean temperature and precipitation data. The results show that over the study period, the growing season duration has lengthened by 1.16 days yr⁻¹ in temperate region of China. The green-up of vegetation has advanced in spring by 0.79 days yr⁻¹ and the dormancy delayed in autumn by 0.37 days yr⁻¹. The dates of onset for phenological events are most significantly related with the mean temperature during the preceding 2–3 months. A warming in the early spring (March to early May) by 1°C could cause an earlier onset of green-up of 7.5 days, whereas the same increase of mean temperature during autumn (mid-August through early October) could lead to a delay of 3.8 days in vegetation dormancy. Variations in precipitation also influenced the duration of growing season, but such influence differed among vegetation types and phenological phases.     

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.     

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.     

Annual variation in the distribution of summer snowdrifts in the Kosciuszko alpine area,Australia, and its effect on the composition and structure of alpine vegetation

Abstract Australian alpine ecosystems are expected to diminish in extent as global warming intensifies. Alpine vegetation patterns are influenced by the duration of snow cover including the presence of snowdrifts in summer, but there is little quantitative information on landscape‐scale relationships between vegetation patterns and the frequency of occurrence of persistent summer snowdrifts in the Australian alps. We mapped annual changes in summer snowdrifts in the Kosciuszko alpine region, Australia, from Landsat TM images and modelled the frequency of occurrence of persistent summer snowdrifts from long‐term records (1954–2003) of winter snow depth. We then compared vegetation composition and structure among four classes that differed in the frequency of occurrence of persistent summer snowdrifts. We found a curvilinear relationship between annual winter snow depth and the area occupied by persistent snowdrifts in the following summer (r² = 0.9756). Only 21 ha (0.42% of study area) was predicted to have supported summer snowdrifts in 80% of the past 50 years, while 440 ha supported persistent summer snow in 10% of years. Mean cover and species richness of vascular plants declined significantly, and species composition varied significantly, as the frequency of summer snow persistence increased. Cushion plants and rushes were most abundant where summer snowdrifts occurred most frequently, and shrubs, grasses and sedges were most abundant in areas that did not support snowdrifts in summer. The results demonstrate strong regional relationships between vegetation composition and structure and the frequency of occurrence of persistent summer snowdrifts. Reductions in winter snow depth due to global warming are expected to lead to substantial reductions in the extent of persistent summer snowdrifts. As a consequence, shrubs, grasses and sedges are predicted to expand at the expense of cushion plants and rushes, reducing landscape vegetation diversity. Fortunately, few vascular plant species (e.g. Ranunculus niphophilus) appear to be totally restricted to areas where summer snow occurs most frequently. The results from this study highlight potential indicator species that could be monitored to assess the effects of global warming on Australian alpine environments.     

Satellite-based mapping of the growing season and bioclimatic zones in Fennoscandia

Aim  To test whether satellite-derived NDVI values obtained during the growing season as delimited by the onset of phenological phases can be used to map bioclimatically a large region such as Fennoscandia.
Location  Fennoscandia north of about 58° N and neighbouring parts of NW Russia.
Methods  Phenology data on birch from 15 research stations and the half-monthly GIMMS-NDVI data set with 8 × 8 km² resolution from the period 1982–2002 were used to characterize the growing season. To link surface phenology with NDVI data, new algorithms on a pixel-by-pixel basis that show high correlation with phenophases on birch were developed. Then, time-integrated values (TI NDVI) during the phenologically defined growing season were computed to produce a bioclimatological map of Fennoscandia, which was tested and correlated with growing degree days (GDD) obtained from 20 meteorological stations. The map was also compared vs. traditional bioclimatic maps, and analysed for error factors distorting NDVI values.
Results  The correlation between GDD and TI NDVI data during the phenologically defined growing season was very high. Therefore, the TI NDVI map could be presented as a bioclimatic map reflecting GDD. However, several major areas have interfering factors distorting NDVI values, such as the pixel heterogeneity caused by the altitudinal mosaic in western Norway, the mosaic of lakes in southeastern Finland, and the agriculture-dominated areas in southern Fennoscandia.
Main conclusions  TI NDVI data from the phenologically defined growing season during 1982–2002 in Fennoscandia can be processed as a bioclimatic map reflecting GDD, except for the areas distorting NDVI values by their strong ground-cover heterogeneity.     

Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems

In terrestrial high‐latitude regions, observations indicate recent changes in snow cover, permafrost, and soil freeze–thaw transitions due to climate change. These modifications may result in temporal shifts in the growing season and the associated rates of terrestrial productivity. Changes in productivity will influence the ability of these ecosystems to sequester atmospheric CO₂. We use the terrestrial ecosystem model (TEM), which simulates the soil thermal regime, in addition to terrestrial carbon (C), nitrogen and water dynamics, to explore these issues over the years 1960–2100 in extratropical regions (30–90°N). Our model simulations show decreases in snow cover and permafrost stability from 1960 to 2100. Decreases in snow cover agree well with National Oceanic and Atmospheric Administration satellite observations collected between the years 1972 and 2000, with Pearson rank correlation coefficients between 0.58 and 0.65. Model analyses also indicate a trend towards an earlier thaw date of frozen soils and the onset of the growing season in the spring by approximately 2–4 days from 1988 to 2000. Between 1988 and 2000, satellite records yield a slightly stronger trend in thaw and the onset of the growing season, averaging between 5 and 8 days earlier. In both, the TEM simulations and satellite records, trends in day of freeze in the autumn are weaker, such that overall increases in growing season length are due primarily to earlier thaw. Although regions with the longest snow cover duration displayed the greatest increase in growing season length, these regions maintained smaller increases in productivity and heterotrophic respiration than those regions with shorter duration of snow cover and less of an increase in growing season length. Concurrent with increases in growing season length, we found a reduction in soil C and increases in vegetation C, with greatest losses of soil C occurring in those areas with more vegetation, but simulations also suggest that this trend could reverse in the future. Our results reveal noteworthy changes in snow, permafrost, growing season length, productivity, and net C uptake, indicating that prediction of terrestrial C dynamics from one decade to the next will require that large‐scale models adequately take into account the corresponding changes in soil thermal regimes.     

Climatic factors controlling interannual variability of the onset of vegetation phenology in the northern Sub-Saharan Africa from 1988 to 2013

Satellite-based evaluations of change in vegetation phenology have been explored extensively but land cover-specific climate factors driving these anomalous changes are not fully understood in northern Sub-Saharan Africa. In this study, we identified the climatic factors controlling the start of the season (SOS) extracted from GIMMS NDVI from 1988 to 2013 with onset of rainy season (ORS), annual mean temperature (Temp) and precipitation (PP) through the stepwise regression analysis. The results showed that the SOS shifted towards a late onset in a northward direction with distinct earlier and later trends in grassland and cropland, respectively. The stepwise regression has successfully built a model between SOS and its drivers in 46.0% of the total pixels, where its primary factor differed regionally across land covers. The ORS explained the local anomalous SOS change primarily at 44.7% of the pixels where the model was built. Although the ORS was the primary dominant factor in savannah and cropland, the Temp and PP were leading in grassland and shrubland, respectively, and all factors contributed evenly in evergreen forest. The difference of land cover-specific primary factor implicates complex process in dependency of local vegetation phenology on physiological traits and climate regime across land cover in Sub-Saharan Africa.     

季节性雪被对高山生态系统土壤氮转化的影响

在高山生态系统中,季节性雪被对土壤氮含量及转化有着重大影响.降雪是氮沉降的一种重要形式,直接影响着土壤中的有效氮含量;降雪形成不同厚度和持续期的雪被后,造成环境因子(土壤温度和含水量)和生物因子(土壤微生物、高山植物和高山动物)的异质性,进而对土壤中氮素矿化和微生物固持过程产生复杂的影响.本文重点介绍了持续性雪被消融期冻融交替影响土壤氮素矿化和流失的机制,并针对高山地区未来季节性雪被可能发生的变化,综述了野外原位模拟实验的主要研究成果,最后提出了开展季节性雪被对土壤氮影响研究的一些建议.     

季节性雪被对高山森林凋落物分解的影响

季节性雪被可能对高山森林凋落物分解产生重要影响, 但一直没有深入的研究。该文采用凋落物分解袋法, 于2010-2012年雪被覆盖下几个关键时期(冻结初期、深冻期和融化期)以及生长季节, 研究了川西高山森林代表性树种岷江冷杉(Abies faxoniana)、红桦(Betula albosinensis)、四川红杉(Larix mastersiana)和方枝柏(Sabina saltuaria)凋落叶在不同厚度冬季雪被下的分解动态。经过两年的分解, 不同雪被覆盖下岷江冷杉凋落物分解率为33.98%-39.55%, 红桦为46.49%-48.22%, 四川红杉为42.30%-44.93%, 方枝柏为40.34%-43.84%。相对于无雪被覆盖环境, 厚型雪被覆盖均小幅提高了4种凋落物两年的失重率(1.57%-5.57%)。3个针叶树种(岷江冷杉、四川红杉和方枝柏) Olson凋落物分解系数k均以厚型雪被覆盖最大, 薄型雪被覆盖最小, 而阔叶树种红桦分解系数k则表现为无雪被>薄型雪被>较厚型雪被>厚型雪被>中型雪被。尽管在第二年生长季中雪被对红桦凋落物分解的促进作用不明显, 但雪被覆盖明显促进了两年各个关键时期岷江冷杉、四川红杉和方枝柏凋落物的分解。第一年雪被期凋落物分解对当年分解总量的贡献达42.5%-65.5%, 季节性雪被变化明显改变了凋落物冬季分解格局, 对深冻期凋落物分解过程影响尤为显著。综上所述, 当前气候变化情景下冬季雪被的减少可能减缓该区森林凋落物分解过程, 但相对于易分解的阔叶凋落物, 针叶凋落物的响应特征可能更为强烈。     

Impact of spruce forest on rainfall interception and seasonal snow cover evolution in the Western Tatra Mountains,Slovakia

The paper analyzes the impacts of the spruce forest on precipitation interception and evolution of snow cover in the mountain catchment of the Jalovecky creek, the Western Tatra Mountains, Slovakia. Both processes were monitored at the elevation of 1420 m a.s.l.. Interception was measured from the end of August 2006 until November 2008 by a network of 13 raingauges. Mean interception over the studied period in forest window was 23%. Mean values for the dripping zone under tree branches, near stems of the trees and under the young trees were 28%, 65% and 44%, respectively. With exception of forest window, the interception at the same characteristic positions was highly variable. Calculated daily precipitation thresholds needed to fulfill the storage capacity of the canopy were about 0.8–0.9 mm. Differences in snow accumulation and melt in the open area (elevation 1500 m a.s.l.) and in the forest were measured in winters 2003–2008. Snow depths (SD) and water equivalents (SWE) were typically smaller in the forest, although the differences were getting smaller towards the end of snow season. SD and SWE in the forest were higher than in the open area for a short time before the end of season in winters 2003 and 2005. The correlations between SD and SWE in the open area and in the forest explained about 90% of variability. The energy balance snow model UEB satisfactorily simulated the evolution of snow cover in the forest and in the open area.