Scale Interactions and Regional Climate: Examples from the Susquehanna River Basin

One of the most difficult problems faced by climatologists is how to translate global climate model (GCM) output into regional- and local-scale information that health and environmental effects researchers can use. It will be decades before GCMs will be able to resolve scales small enough for most effects research, so climatologists have developed climate downscaling methods to bridge the gap between the global and local scales. There are two main streams of climate downscaling research. First, high-resolution, limited-area climate models can be embedded in the coarse-scale GCMs, producing much finer resolution climate data. Second, empirical downscaling techniques develop transfer functions linking the large-scale atmospheric circulation generated by the GCMs to surface data. Examples of both types of downscaling, aimed at improving projections of future climate in the Susquehanna River Basin (the Mid-Atlantic Region of the United States), are presented. A third case is also described in which an even higher-resolution nested atmospheric model is being developed and linked to a hydrologic model system, with the ultimate goal of simulating the environmental response to climate forcing at all time and space scales.     

Investigating the impact of climate change on crop phenological events in Europe with a phenology model

Predicting regional and global carbon and water dynamics requires a realistic representation of vegetation phenology. Vegetation models including cropland models exist (e.g. LPJmL, Daycent, SIBcrop, ORCHIDEE-STICS, PIXGRO) but they have various limitations in predicting cropland phenological events and their responses to climate change. Here, we investigate how leaf onset and offset days of major European croplands responded to changes in climate from 1971 to 2000 using a newly developed phenological model, which solely relies on climate data. Net ecosystem exchange (NEE) data measured with eddy covariance technique at seven sites in Europe were used to adjust model parameters for wheat, barley, and rapeseed. Observational data from the International Phenology Gardens were used to corroborate modeled phenological responses to changes in climate. Enhanced vegetation index (EVI) and a crop calendar were explored as alternative predictors of leaf onset and harvest days, respectively, over a large spatial scale. In each spatial model simulation, we assumed that all European croplands were covered by only one crop type. Given this assumption, the model estimated that the leaf onset days for wheat, barley, and rapeseed in Germany advanced by 1.6, 3.4, and 3.4 days per decade, respectively, during 1961–2000. The majority of European croplands (71.4%) had an advanced mean leaf onset day for wheat, barley, and rapeseed (7.0% significant), whereas 28.6% of European croplands had a delayed leaf onset day (0.9% significant) during 1971–2000. The trend of advanced onset days estimated by the model is similar to observations from the International Phenology Gardens in Europe. The developed phenological model can be integrated into a large-scale ecosystem model to simulate the dynamics of phenological events at different temporal and spatial scales. Crop calendars and enhanced vegetation index have substantial uncertainties in predicting phenological events of croplands. Caution should be exercised when using these data.     

The plant phenological online database (PPODB): an online database for long-term phenological data

We present an online database that provides unrestricted and free access to over 16 million plant phenological observations from over 8,000 stations in Central Europe between the years 1880 and 2009. Unique features are (1) a flexible and unrestricted access to a full-fledged database, allowing for a wide range of individual queries and data retrieval, (2) historical data for Germany before 1951 ranging back to 1880, and (3) more than 480 curated long-term time series covering more than 100 years for individual phenological phases and plants combined over Natural Regions in Germany. Time series for single stations or Natural Regions can be accessed through a user-friendly graphical geo-referenced interface. The joint databases made available with the plant phenological database PPODB render accessible an important data source for further analyses of long-term changes in phenology. The database can be accessed via www.ppodb.de.     

Seasonal Foliage Changes in the Eastern Amazon Basin Detected from Landsat Thematic Mapper Satellite Images1

Seasonal changes in tropical forests are difficult to measure from the ground, especially in areas of high species diversity and low phenological synchrony. Satellite images, which integrate individual tree canopies and cover a large spatial extent, facilitate tests for stand-level canopy phenology. Variability in near-infrated radiance (TM bands 4 and 5) of several distinct vegetation types was used to detect seasonal changes in a series of three Landsat Thematic Mapper (TM) images from the wet season to the dry season in Marabá, Brazil (eastern Amazon basin). Despite different atmospheric and instrumental conditions among the images, spectral changes were distinguishable. A phenological process (leaf aging, leaf drop, water stress) was determined from the spectral changes for each vegetation type. Changes in the spectral properties suggest that during the dry season, upland terra firme forest increased the rate of leaf exchange and some riparian vegetation was deciduous. Terra firme forest that had been altered by penetration of fires from nearby pastures increased in leaf biomass over a 14-month period. This study shows that a time series of images can provide information on temporal changes in primary vegetation and guide field studies to investigate seasonal changes that may not be detectable from the ground.     

Multiscale analysis of temporal variability of soil CO2 production as influenced by weather and vegetation

Ecosystem processes are influenced by weather and climatic perturbations at multiple temporal scales with a large range of amplitudes and phases. Technological advances of automated biometeorological measurements provide the opportunity to apply spectral methods on continuous time series to identify differences in amplitudes and phases and relationships with weather variation. Here we used wavelet coherence analysis to study the temporal covariance between soil CO₂ production and soil temperature, soil moisture, and photosynthetically active radiation (PAR). Continuous (hourly average) data were acquired over 2 years among three vegetation types in a semiarid mixed temperate forest. We showed that soil temperature and soil moisture influence soil CO₂ production differently at multiple periods (e.g. hours, days, weeks, months, years), especially after rain pulse events. Our results provide information about the periodicity of soil CO₂ production among vegetation types, and provide insights about processes controlling CO₂ production through the study of phase relationships between two time series (e.g. soil CO₂ production and PAR). We tested the performance of empirical models of soil CO₂ production using the continuous wavelet transform. These models, built around soil temperature and moisture, failed at multiple periods across the measured dates, suggesting that empirical models should include other factors that regulate soil CO₂ production at different temporal scales. Our results add a new dimension for the analysis of continuous time series of biometeorological measurements and model testing, which will prove useful for analysis of increasing sensor data obtained by environmental networks.     

<Emphasis Type="Italic">Alternaria</Emphasis> spores in the air across Europe: abundance,seasonality and relationships with climate,meteorology and local environment

We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central-northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations.     

Longitudinal structure of fish assemblages in a minimally disrupted stream

The longitudinal distribution patterns of fish species are affected by both natural and anthropogenic variables. The role of these factors on the formation of species assemblages is well documented in North America and Western Europe, but detailed information is lacking from Central and Eastern Europe, and the Carpathian region especially. Therefore, we examined the structure of fish assemblages in response to six key environmental parameters in a natural stream system (Udava stream basin, Slovakia). We used the indirect ordination method of gradient analysis (Detrended Correspondence Analysis, DCA) to analyse the species groups and their connections to the sampled sites and to recognize the strongest gradient of assemblage composition. Subsequently, we used the direct ordination method (Canonical Correspondence Analysis, CCA) to identify the strongest gradients in relation to selected variables. Two major gradients were identified that follow the upstream-downstream pattern of fish communities and three variables (distance from source, depth and site slope) are correlated with the first CCA axis (P < 0.05) and two variables (depth and vegetation cover) are correlated with the second CCA axis (P < 0.05). We assume that these factors influence the temperature and the amount of dissolved oxygen that can cause oxygen and temperature stress to intolerant species (e.g., salmonids). Based on these results, we assume that the economically important species, brown trout and grayling, are not native to the stream basin and this status is only the consequence of natural factors. Furthermore, the results suggest that the Udava stream offers favourable conditions for fish species distribution — a view supported by the high variability of particular variables within the proposed model.     

East versus West: contrasts in phenological patterns?

Aim To examine whether change in the timing of a large number of phenological events and their response to temperature differs between trophic levels during the period 1988–2008. Location In the vicinity of Kazan, Tatarstan Republic, Russia (55°45′ N, 49°08′ E). Methods Observations of the dates of first events of 22 plant phases, 8 insect phases, 3 herpetofauna phases and 26 migrant bird phases were examined using regression to assess changes over time and response to temperature. Differences between trophic levels were assessed using ANOVA. Results In comparison to studies from western Europe, relatively few phenological series (15) revealed a significant advance over time, but a much larger number (37), including all the herpetofauna and nearly all the plants, showed a response to temperature. Trends in birds were, on average, twice as great as those for plants, but plants had a significantly greater temperature response. Over the study period local temperatures had not risen significantly but some phenological change was still evident. Main conclusions Phenological change has been less marked in the eastern edge of Europe than in western and central Europe. This is compatible with a lack of significant local warming during the study period. A large number of species show strong responses to temperature so will be expected to advance if/when local temperatures do increase. In contrast to results from elsewhere in Europe, early events were not the most temperature responsive, suggesting local adaptation preventing precocious behaviour and the consequent dangers of sub‐zero temperatures.     

基于带宽优选地理加权回归模型的深圳市植被碳储量反演

植被碳储量估测是自然资源监测的重要内容,遥感技术结合地面样地进行反演可以获得区域范围内植被碳储量的空间连续分布,弥补了传统人工抽样调查估测的不足。然而,现有的参数和非参数遥感估测模型大多忽略了样地数据的变异与空间自相关关系。研究以Landsat 8 OLI影像为数据源提取遥感变量,结合植被碳储量实测调查数据,利用最小信息准则(AICc)、最大空间自相关距离(MSAD)和交叉验证(CV)分别确定最优带宽,组合Gaussian、Bi-square和Exponential核函数构建地理加权回归(GWR)模型估算深圳市植被碳储量,并与多元线性回归(MLR)进行比较,选择最优模型绘制深圳市植被碳储量空间分布图。研究结果表明,GWR模型整体精度优于MLR模型,GWR模型的决定系数(R~2)均高于MLR模型,且均方根误差(RMSE)和平均绝对误差(MAE)显著降低。带宽和核函数的选择对GWR模型估测结果产生了显著影响。以CV确定带宽、Exponential为核函数组合构建的GWR模型效果最佳,其R~2为0.697,RMSE为10.437 Mg C/hm~2,相比其它模型精度上升了13.87%—32....     

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。     

排序和广义线性模型与广义可加模型在植物种与环境关系研究中的应用

排序和广义线性模型(Generalized Linear Model,GLM)与广义可加模型(Goneralized Additive Model,GAM)是研究植物种与环境间关系的重要方法。基于线性模型的排序方法应限定于环境梯度较短的植被数据。而基于单峰模型的排序方法更适用于梯度较长的情况。PCA、CA／RA系列和CCA系列是常用的排序方法。同时进行环境数据和植被数据分析的CCA系列,能清楚地得出植物种与环境间的关系。CCA改进后的DCCA和PCCA,是现今较理想的排序方法。GLM和GAM实质上是用环境变量的高阶多项式来拟合植物种与环境变量的关系。GLM和GAM扩展了植物种与环境变量之间的关系模型,能深入地探讨植物种与环境间的关系。GLM主要是模型决定的,而GAM主要取决于原始数据。一般来说,排序能得出研究区域的主要环境梯度,提供了物种聚集和植物群落的概略描述。GLM与GAM对于深入研究单个植物种与环境间的关系具有优势。在实际研究中,两种方法结合使用能互补不足。     

Shifting and extension of phenological periods with increasing temperature along elevational transects in southern Bavaria

The impact of global warming on phenology has been widely studied, and almost consistently advancing spring events have been reported. Especially in alpine regions, an extraordinary rapid warming has been observed in the last decades. However, little is known about phenological phases over the whole vegetation period at high elevations. We observed 12 phenological phases of seven tree species and measured air temperature at 42 sites along four transects of about 1000 m elevational range in the years 2010 and 2011 near Garmisch‐Partenkirchen, Germany. Site‐ and species‐specific onset dates for the phenological phases were determined and related to elevation, temperature lapse rates and site‐specific temperature sums. Increasing temperatures induced advanced spring and delayed autumn phases, in which both yielded similar magnitudes. Delayed leaf senescence could therefore have been underestimated until now in extending the vegetation period. Not only the vegetation period, but also phenological periods extended with increasing temperature. Moreover, sensitivity to elevation and temperature strongly depends on the specific phenological phase. Differences between species and groups of species (deciduous, evergreen, high elevation) were found in onset dates, phenological response rates and also in the effect of chilling and forcing temperatures. Increased chilling days highly reduced forcing temperature requirements for deciduous trees, but less for evergreen trees. The problem of shifted species associations and phenological mismatches due to species‐specific responses to increasing temperature is a recent topic in ecological research. Therefore, we consider our findings from this novel, dense observation network in an alpine area of particular importance to deepen knowledge on phenological responses to climate change.     

Simulation of Critical Loads for Nitrogen for Terrestrial Plant Communities in The Netherlands

This paper describes a new method to derive nitrogen critical loads for vegetation, and its application to The Netherlands. An ‘inverted’ form of the soil chemical model SMART2 was used to estimate atmospheric nitrogen deposition at the critical conditions for 139 terrestrial vegetation types (associations) occurring in northwestern Europe, using an iterative search procedure. The critical conditions are the lower end of the pH range, and the upper end of the nitrogen availability range for each vegetation type. The critical load is assumed to be the nitrogen deposition that results in the critical conditions. The critical load values were subjected to a sensitivity and uncertainty analysis. Sensitivity analysis showed that the estimated critical N load mainly depends on the vegetation type and to a lesser extent on the soil type and the critical N availability. Of these variables N availability, which was estimated from Ellenberg’s indicator scale, contributes most to the uncertainty. The critical load averaged over all vegetation types and soil types is estimated to be 23 ± 7 kg N ha⁻¹y⁻¹. This is a rather reliable value because its uncertainty is small and it is in agreement with empirical estimates of critical loads. Critical loads per vegetation type are less reliable because they are not correlated to empirical values, although the ranges of simulated and empirical values usually overlap. At the site level, uncertainty becomes very large and it is not possible to determine critical loads with any practical significance. The uncertainties can only be reduced if more data become available on the abiotic response per species under field conditions, at least to nitrogen availability and soil pH.     

Detecting soil salinity with MODIS time series VI data

Mapping of salinization using the satellite derived vegetation indices (VIs) remains difficult at broad regional scales due to the low classification accuracy. Satellite derived VIs from the Moderate Resolution Imaging Spectroradiometer (MODIS) have more potential because the MODIS balances the requirements of spatial detail, spectral and temporal density and tends to reflect vegetation responses through time. However, the relationship between MODIS data and salinity may be underestimated in previous studies because the MODIS time series data were not investigated thoroughly, especially regarding vegetation phenology. This study assessed the applicability of MODIS time series VI data for monitoring soil salinization with a series of MODIS pixels selected in the Yellow River Delta, China. The hidden information in vegetation phenology was investigated by improving the quality of VIs time series data with the Savitzky–Golay filter, extracting the phenological markers and differentiating VIs time series data based on vegetation types. The results showed that the quality of the enhanced vegetation index (EVI) time series data were improved by the Savitzky–Golay filter, which could provide more accurate thresholds of phenological stages than the empirical definition. The seasonal integral of EVI (EVI-SI) extracted from the smoothed EVI time series profile was verified as the best indicator of the degree of soil salinity. Additionally, the correlation of EVI-SI and soil salinity was highly dependent on land cover heterogeneity, and the ranges of correlation coefficients were as high as 0.59–0.92. EVI-SI was linearly correlated with EC_e in cropland with a high model fit (R² = 0.85). The relationship of EVI-SI and EC_e fit best with a binomial line and EVI-SI was able to explain 70% of the variance of EC_e. Despite the poor fit of the linear regression model in mixed sites limited by spatial resolution (R² = 0.32), MODIS time series VI data, as well as the extracted seasonal parameters, still show great potential to assess large-scale soil salinization.     

Phenological description of natural vegetation in southern Africa using remotely‐sensed vegetation data

Abstract. Various attempts have been made to describe and map the vegetation of southern Africa with recent efforts having an increasingly ecologi cal context. Vegetation classification is usually based on vegetation physiognomy and floristic composition, but phenology is useful source of information which is rarely used, although it can contribute functional information on ecosystems. The objectives of this study were to identify a suite of variables derived from time‐series NDVI data that best describe the phenological phenomena of vegetation in southern Africa and, secondly, to assess a classification of pixels of the study area based on NDVI variables using a preexisting map of the biomes that was delimited on the basis of life forms and climate. A number of variables were derived from the satellite data for describing phenological phenomena, which were analysed by multivariate techniques to determine which variables best explained the variation in the satellite data. This set of variables was used to produce a phenological classification of the vegetation of southern Africa, the results of which are discussed in relation to their concordance with the existing biome boundaries.     

1982-2012年中亚地区植被时空变化特征及其与气候变化的相关分析

干旱区植被生态系统对气候变化极为敏感,并且干旱区的植被变化研究对全球碳循环具有重要意义。然而近几十年来,中亚干旱区植被对气候变化的响应机制尚不甚明朗。利用归一化植被指数NDVI数据集和MERRA（Modern-Era Retrospective Analysis for Research and Applications）气象数据,采用经验正交函数（EOF,Empirical Orthogonal Function）和最小二乘法等方法系统分析了31a（1982-2012年）来中亚地区NDVI在不同时间尺度的时空变化特征。进一步分析和研究NDVI与气温和降水的相关性,结果表明：1982-2012年,中亚地区年NDVI总体呈现缓慢增长趋势,而1994年以后年NDVI呈现明显下降趋势,尤其在哈萨克斯坦北部草原地区下降趋势尤为突出。这可能是由于过去30年间,中亚地区降水累计量的持续减少造成的。NDVI的季节变化表明春季NDVI增长最为明显,冬季则显著下降。与平原区相比,中亚山区的NDVI值增长幅度最大,并且山区年NDVI与季节NDVI呈现显著增加趋势（P < 0.05）。中亚地区年NDVI与年降水量正相关,而年NDVI与气温变化存在弱负相关。年NDVI和气温的正相关中心在中亚南部地区,负相关中心则出现在哈萨克斯坦的西部和北部地区;NDVI和降水的相关性中心刚好与气温相反。此外,在近30年间的每年6月至9月,中亚地区NDVI与气温存在近一个月的时间延迟现象。本研究为中亚干旱区生态系统变化和中亚地区碳循环的估算提供科学依据。     

Geographical location, climate and land use influences on the phenology and numbers of the aphid, Myzus persicae, in Europe

Aim The purpose of this study was to improve understanding of the relationship between the spatial patterns of an important insect pest, the aphid Myzus persicae, and aspects of its environment. The main objectives were to determine the predominant geographical, climatic and land use factors that are linked with the aphid's distribution, to quantify their role in determining that distribution, including their interacting effects and to explore the ability of artificial neural networks (ANNs) to provide predictive models. Location The study focused on four spatial scales to account for the aphid data base characteristics and available land use data sets: Europe; a broad zone over Europe covering Belgium, Denmark, France, Ireland, Italy, The Netherlands, Scotland, Sweden and Wales (Regio data base coverage); North‐West Europe (i.e. Belgium, France and the United Kingdom); and England with Wales. Methods Multiple linear regression (MLR) was used to identify the variables in the Geographic location, Climate and Land use groups, that explained significant proportions of the variance in M. persicae total annual numbers and Julian date of first capture. A variance partitioning procedure was used to measure the fraction of the variation that can be explained by each environmental factor and of shared variation between the different factors. Finally, ANNs were employed as an alternative modelling approach for the two largest study areas, i.e. Europe and the Regio data base coverage, to determine whether the relationship between aphid and environmental variables was better described by more complex functions as well as their ability to generalize to new data. Results Land use variables are shown to play a significant role in explaining aphid numbers. The area of agricultural crops, in particular oilseed rape, is positively correlated with M. persicae annual numbers. Among the climatic variables, rainfall is negatively correlated with aphid numbers and temperature is positively correlated. The geographical components also explain a significant part of aphid annual numbers. However, the variance partitioning procedure indicates that while each group has an effect, none is dominant. Aphid first capture is mainly explained by climate where rainfall tends to delay migration and warmer conditions tend to advance it. Climate accounts for the greatest part of the variance when considered separately from the other factors. The geographical and land use components also have a significant effect on first capture at each scale, but their direct contribution is negligible. The ability of the ANN models to generalize to new total numbers and phenological data compared with MLR models was less for Europe (9 and 6% increase in the variance accounted for, respectively) than for the Regio data coverage where an increase of 44% in the variance accounted for was observed. Main conclusions This research supports the hypothesis that climate, land use and geographical location play a role in determining patterns of aphid annual numbers and phenology. The ability of ANN models to predict aphid distribution is improved by the inclusion of temporal land use data. However, identification of the processes involved in such relationships is difficult due to numerous interactions between the environmental factors.     

A systematic review of vegetation phenology in Africa

The study of vegetation phenology is important because it is a sensitive indicator of climate changes and it regulates carbon, energy and water fluxes between the land and atmosphere. Africa, which has 17% of the global forest cover, contributes significantly to the global carbon budget and has been identified as potentially highly vulnerable to climate change impacts. In spite of this, very little is known about vegetation phenology across Africa and the factors regulating vegetation growth and dynamics. Hence, this review aimed to provide a synthesis of studies of related Africa's vegetation phenology and classify them based on the methods and techniques used in order to identify major research gaps. Significant increases in the number of phenological studies in the last decade were observed, with over 70% of studies adopting a satellite-based remote sensing approach to monitor vegetation phenology. Whereas ground based studies that provide detailed characterisation of vegetation phenological development, occurred rarely in the continent. Similarly, less than 14% of satellite-based remote sensing studies evaluated vegetation phenology at the continental scale using coarse spatial resolution datasets. Even more evident was the lack of research focusing on the impacts of climate change on vegetation phenology. Consequently, given the importance and the uniqueness of both methods of phenological assessment, there is need for more ground-based studies to enable greater understanding of phenology at the species level. Likewise, finer spatial resolution satellite sensor data for regional phenological assessment is required, with a greater focus on the relationship between climate change and vegetation phenological changes. This would contribute greatly to debates over climate change impacts and, most importantly, climate change mitigation strategies.     

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.     

The phenological calendar of Estonia and its correlation with mean air temperature

A phenological calendar with 24 phenological phases was compiled for three meteorological stations in Estonia for the period 1948–1996. We analysed the length of the vegetation period, the order of the phenological phases, and the variability and possible changes for two incremental climate change scenarios (±2°C), and compared the results with examples of extreme years. The statistically significant linear trends show that the spring and summer-time phenological phases occurred earlier and the autumn phases moved later during the study period. The study of extreme (minimum and maximum) years shows that 70% of the earliest dates of the 24 phases studied have occurred during the last 15 years with an absolute maximum in 1990 with 8 extreme phases. The phenological spring has shortened (slope –0.23), the summer period has lengthened (slope 0.04), and the autumn has lengthened too. The length of the growing season, determined by the vegetation of rye, has shortened (slope –0.09), which could be the result of changing agricultural technology. The correlation between the starting dates of the phenological phases with the air temperature of the previous 2–3 months is relatively high (0.6–0.8). Studying the +2°C and –2°C scenarios and values for the extreme years shows that, in the case of short variations of air temperature, the phenological development remains within the limits of natural variation. Received: 29 November 1999 / Revised: 15 May 2000 / Accepted: 16 May 2000