Spring phenology in boreal Eurasia over a nearly century time scale

It has been widely reported that tree leaves have tended to appear earlier in many regions of the northern hemisphere in the last few decades, reflecting climate warming. Satellite observations revealed an 8-day advance in leaf appearance date between 1982 and 1991 in northern latitudes. In situ observations show that leaf appearance dates in Europe have advanced by an average of 6.3 days from 1959 to 1996. Modelling of leaf appearance on the basis of temperature also shows a marked advance in temperate and boreal regions from 1955 to 2002. However, before 1955, reported studies of phenological variations are restricted to local scale. Modelling, ground observations and satellite observations are here combined to analyse phenological variations in Eurasian taiga over nearly a century. The trend observed by remote sensing consists mainly in a shift at the end of the 1980s, reflecting a shift in winter and spring temperature. In western boreal Eurasia, a trend to earlier leaf appearance is evident since the mid-1930s, although it is discontinuous. In contrast, the strong advance in leaf appearance detected over Central Siberia using satellite data in 1982–1991 is strengthened by late springs in 1983–1984; moreover, in this region the green-up timing has displayed successive trends with opposite signs since 1920. Thus, such strong trend is not unusual if considered locally. However, the recent advance is unique in simultaneously affecting most of the Eurasian taiga, the leaf appearance dates after 1990 being the earliest in nearly a century in most of the area.     

Greater deciduous shrub abundance extends tundra peak season and increases modeled net CO2 uptake

Satellite studies of the terrestrial Arctic report increased summer greening and longer overall growing and peak seasons since the 1980s, which increases productivity and the period of carbon uptake. These trends are attributed to increasing air temperatures and reduced snow cover duration in spring and fall. Concurrently, deciduous shrubs are becoming increasingly abundant in tundra landscapes, which may also impact canopy phenology and productivity. Our aim was to determine the influence of greater deciduous shrub abundance on tundra canopy phenology and subsequent impacts on net ecosystem carbon exchange (NEE) during the growing and peak seasons in the arctic foothills region of Alaska. We compared deciduous shrub‐dominated and evergreen/graminoid‐dominated community‐level canopy phenology throughout the growing season using the normalized difference vegetation index (NDVI). We used a tundra plant‐community‐specific leaf area index (LAI) model to estimate LAI throughout the green season and a tundra‐specific NEE model to estimate the impact of greater deciduous shrub abundance and associated shifts in both leaf area and canopy phenology on tundra carbon flux. We found that deciduous shrub canopies reached the onset of peak greenness 13 days earlier and the onset of senescence 3 days earlier compared to evergreen/graminoid canopies, resulting in a 10‐day extension of the peak season. The combined effect of the longer peak season and greater leaf area of deciduous shrub canopies almost tripled the modeled net carbon uptake of deciduous shrub communities compared to evergreen/graminoid communities, while the longer peak season alone resulted in 84% greater carbon uptake in deciduous shrub communities. These results suggest that greater deciduous shrub abundance increases carbon uptake not only due to greater leaf area, but also due to an extension of the period of peak greenness, which extends the period of maximum carbon uptake.     

A new seasonal‐deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios

A spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf‐out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head‐to‐head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km²), we found that the revised model substantially outperformed the standard CLM seasonal‐deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long‐term trends (1950–2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf‐out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf‐out in colder regions, but later leaf‐out in warmer regions, and no trend globally. The earlier spring leaf‐out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr^?1) and evapotranspiration (up to 24 mm yr^?1) when results were integrated across the study region. These results suggest that the standard seasonal‐deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land–atmosphere interactions and feedbacks may result.     

Change in the Green-Up Dates for Quercus mongolica in Northeast China and Its Climate-Driven Mechanism from 1962 to 2012

The currently available studies on the green-up date were mainly based on ground observations and/or satellite data, and few model simulations integrated with wide coverage satellite data have been reported at large scale over a long time period (i.e., > 30 years). In this study, we combined phenology mechanism model, long-term climate data and synoptic scale remote sensing data to investigate the change in the green-up dates for Quercus mongolica over 33 weather stations in Northeast China and its climate-driven mechanism during 1962-2012. The results indicated that the unified phenology model can be well parameterized with the satellite derived green-up dates. The optimal daily mean temperature for chilling effect was between -27°C and 1°C for Q. mongolica in Northeast China, while the optimal daily mean temperature for forcing effect was above -3°C. The green-up dates for Q. mongolica across Northeast China showed a delayed latitudinal gradient of 2.699 days degree^-1, with the earliest date on the Julian day 93 (i.e., 3^th April) in the south and the latest date on the Julian day 129 (i.e., 9^th May) in the north. The green-up date for Q. mongolica in Northeast China has advanced 6.6 days (1.3 days decade^-1) from 1962 to 2012. With the prevailing warming in autumn, winter and spring in Northeast China during the past 51 years, the chilling effect for Q. mongolica has been weakened, while the forcing effect has been enhanced. The advancing trend in the green-up dates for Q. mongolica implied that the enhanced forcing effect to accelerate green-up was stronger than the weakened chilling effect to hold back green-up while the changes of both effects were caused by the warming climate.     

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf‐out times across groupings of species in a dynamic vegetation model

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf‐out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf‐out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970–2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf‐out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf‐out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.     

Field evidence for earlier leaf-out dates in alpine grassland on the eastern Tibetan Plateau from 1990 to 2006

Worldwide, many plant species are experiencing an earlier onset of spring phenophases due to climate warming. Rapid recent temperature increases on the Tibetan Plateau (TP) have triggered changes in the spring phenology of the local vegetation. However, remote sensing studies of the land surface phenology have reached conflicting interpretations about green-up patterns observed on the TP since the mid-1990s. We investigated this issue using field phenological observations from 1990 to 2006, for 11 dominant plants on the TP at the levels of species, families (Gramineae—grasses and Cyperaceae—sedges) and vegetation communities (alpine meadow and alpine steppe). We found a significant trend of earlier leaf-out dates for one species (Koeleria cristata). The leaf-out dates of both Gramineae and Cyperaceae had advanced (the latter significantly, starting an average of 9 days later per year than the former), but the correlation between them was significant. The leaf-out dates of both vegetation communities also advanced, but the pattern was only significant in the alpine meadow. This study provides the first field evidence of advancement in spring leaf phenology on the TP and suggests that the phenology of the alpine steppe can differ from that of the alpine meadow. These findings will be useful for understanding ecosystem responses to climate change and for grassland management on the TP.     

Use of digital cameras for phenological observations

Vegetation phenology such as the onset of green-up and senescence is strongly controlled by climate and other environmental factors, and in turn affects the terrestrial carbon balance. Therefore, phenological observation is important as an indicator of global warming and for estimation of the terrestrial carbon balance. Because phenological responses differ from species to species, precise monitoring from the species scale to the global scale is required. In this study, we analyzed images from digital cameras, which have proliferated in recent years, to investigate their utility as remote sensors. We collected daily images taken by digital cameras in national parks across Japan over 8 years in wetland mixed deciduous forest, and evergreen broadleaved forest. Values of red, green, and blue (RGB) channels in each pixel within images were extracted, and a vegetation green excess index (2G-RBi) was calculated to detect phenology. The time series of 2G-RBi showed clear phenological patterns of each vegetation type in each year at the species or community scale. Even physiological damage due to a typhoon was detected. The dates of green-up were estimated easily and objectively from the second derivative of 2G-RBi, and a trend in yearly green-up dates of various types of vegetation was demonstrated. Furthermore, a strong correlation between interannual variations in green-up dates and local spring temperature was found, and the sensitivity of green-up date to temperature was revealed. The results suggest the utility of digital cameras for phenological observations at precise temporal and spatial resolutions, despite a year-to-year drift of color balance of camera as a technical device. As a form of near-surface remote sensing, digital cameras could obtain significant ecological information. Establishing camera networks could help us understand phenological responses at a wide range of scales.     

Initial Stages of Tundra Shrub Litter Decomposition May Be Accelerated by Deeper Winter Snow But Slowed Down by Spring Warming

The Arctic climate is projected to change during the coming century, with expected higher air temperatures and increased winter snowfall. These climatic changes might alter litter decomposition rates, which in turn could affect carbon (C) and nitrogen (N) cycling rates in tundra ecosystems. However, little is known of seasonal climate change effects on plant litter decomposition rates and N dynamics, hampering predictions of future arctic vegetation composition and the tundra C balance. We tested the effects of snow addition (snow fences), warming (open top chambers), and shrub removal (clipping), using a full-factorial experiment, on mass loss and N dynamics of two shrub tissue types with contrasting quality: deciduous shrub leaf litter (Salix glauca) and evergreen shrub shoots (Cassiope tetragona). We performed a 10.5-month decomposition experiment in a low-arctic shrub tundra heath in West-Greenland. Field incubations started in late fall, with harvests made after 249, 273, and 319 days of field incubation during early spring, summer and fall of the next year, respectively. We observed a positive effect of deeper snow on winter mass loss which is considered a result of observed higher soil winter temperatures and corresponding increased winter microbial litter decomposition in deep-snow plots. In contrast, warming reduced litter mass loss during spring, possibly because the dry spring conditions might have dried out the litter layer and thereby limited microbial litter decomposition. Shrub removal had a small positive effect on litter mass loss for C. tetragona during summer, but not for S. glauca. Nitrogen dynamics in decomposing leaves and shoots were not affected by the treatments but did show differences in temporal patterns between tissue types: there was a net immobilization of N by C. tetragona shoots after the winter incubation, while S. glauca leaf N-pools were unaltered over time. Our results support the widely hypothesized positive linkage between winter snow depth and litter decomposition rates in tundra ecosystems, but our results do not reveal changes in N dynamics during initial decomposition stages. Our study also shows contrasting impacts of spring warming and snow addition on shrub decomposition rates that might have important consequences for plant community composition and vegetation-climate feedbacks in rapidly changing tundra ecosystems.     

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.     

Satellite monitoring of phenological events

A technique used to investigate broad scale phenological events by means of repetitive satellite observations is described. The temporal sequence of leaf development and senescence of deciduous forest and crop canopies is characterized by changes in their reflectance of solar energy at several wavelength intervals. Correlation with simultaneous ground observations is used to develop relationships between normalized reflectivity ratios derived from multispectral satellite data and the areal percentage of green vegetative material present in the canopy. Satellite observations made over a nationwide network of test sites during the years 1972 and 1973, provide estimates of the amount of green canopy present as it developes during the spring season as well as estimates of the percentage of leaf coloration and abscission during the autumnal period.Presented at the Seventh International Biometeorological Congress, 17–23 August 1975, College Park, Maryland, USA.     

High‐resolution prediction of leaf onset date in Japan in the 21st century under the IPCC A1B scenario

Reports indicate that leaf onset (leaf flush) of deciduous trees in cool‐temperate ecosystems is occurring earlier in the spring in response to global warming. In this study, we created two types of phenology models, one driven only by warmth (spring warming [SW] model) and another driven by both warmth and winter chilling (parallel chill [PC] model), to predict such phenomena in the Japanese Islands at high spatial resolution (500 m). We calibrated these models using leaf onset dates derived from satellite data (Terra/MODIS) and in situ temperature data derived from a dense network of ground stations Automated Meteorological Data Acquisition System. We ran the model using future climate predictions created by the Japanese Meteorological Agency's MRI‐AGCM3.1S model. In comparison to the first decade of the 2000s, our results predict that the date of leaf onset in the 2030s will advance by an average of 12 days under the SW model and 7 days under the PC model throughout the study area. The date of onset in the 2090s will advance by 26 days under the SW model and by 15 days under the PC model. The greatest impact will occur on Hokkaido (the northernmost island) and in the central mountains.     

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。     

A generalized, bioclimatic index to predict foliar phenology in response to climate

The phenological state of vegetation significantly affects exchanges of heat, mass, and momentum between the Earth's surface and the atmosphere. Although current patterns can be estimated from satellites, we lack the ability to predict future trends in response to climate change. We searched the literature for a common set of variables that might be combined into an index to quantify the greenness of vegetation throughout the year. We selected as variables: daylength (photoperiod), evaporative demand (vapor pressure deficit), and suboptimal (minimum) temperatures. For each variable we set threshold limits, within which the relative phenological performance of the vegetation was assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) was derived as the product of the three indices. Ten‐day mean GSI values for nine widely dispersed ecosystems showed good agreement (r>0.8) with the satellite‐derived Normalized Difference Vegetation Index (NDVI). We also tested the model at a temperate deciduous forest by comparing model estimates with average field observations of leaf flush and leaf coloration. The mean absolute error of predictions at this site was 3 days for average leaf flush dates and 2 days for leaf coloration dates. Finally, we used this model to produce a global map that distinguishes major differences in regional phenological controls. The model appears sufficiently robust to reconstruct historical variation as well as to forecast future phenological responses to changing climatic conditions.     

Leaf mineral nutrition of Arctic plants in response to warming and deeper snow in northern Alaska

Articulating the consequences of global climate change on terrestrial ecosystem biogeochemistry is a critical component of Arctic system studies. Leaf mineral nutrition responses of tundra plants is an important measure of changes in organismic and ecosystem attributes because leaf nitrogen and carbon contents effect photosynthesis, primary production, carbon budgets, leaf litter, and soil organic matter decomposition as well as herbivore forage quality. In this study, we used a longterm experiment where snow depth and summer temperatures were increased independently and together to articulate how a series of climate change scenarios would affect leaf N, leaf C, and leaf C:N for vegetation in dry and moist tussock tundra in northern Alaska, USA. Our findings were: 1) moist tundra vegetation is much more responsive to this suite of climate change scenarios than dry tundra with up to a 25% increase in leaf N; 2) life forms exhibit divergence in leaf C, N, and C:N with deciduous shrubs and graminoids having almost identical leaf N contents; 3) for some species, leaf mineral nutrition responses to these climate change scenarios are tundra type dependent ( Betula ), but for others ( Vaccinium vitis-idaea ), strong responses are exhibited regardless of tundra type; and 4) the seasonal patterns and magnitudes of leaf C and leaf N in deciduous and evergreen shrubs were responsive to conditions of deeper snow in winter. Leaf N is was generally higher immediately after emergence from the deep snow experimental treatments and leaf N was higher during the subsequent summer and fall, and the leaf C:N were lower, especially in deciduous shrubs. These findings indicate that coupled increases in snow depth and warmer summer temperatures will alter the magnitudes and patterns of leaf mineral nutrition and that the long term consequences of these changes may feed-forward and affect ecosystem processes.     

Phosphate absorption and root respiration of different plant growth forms from northern Alaska

Rate of phosphate absorption measured on field-collected, excised roots of eight species from a tundra site and a taiga forest was more strongly correlated with growth form traits than with type of community. In the taiga forest phosphate absorption rate ranged tenfold among species and was higher in graminoids than in shrubs. In both sites deciduous shrubs tended to have higher rates than evergreens. Phosphate absorption rate was not strongly reduced at low temperature in any species examined and there was a temperature optimum of about 20°C in Eriophorum vaginatum . Phosphate absorption rates were higher in lateral than primary roots, although both root types had substantial respiration rates. At one tundra site, calculations suggest that roots of E. vaginatum require 30–40 d to absorb a quantity of phosphorus equivalent to that required to synthesize the root and another 5–6 d to provide the net phosphorus requirements for the remainder of the plant.     

Phytophenological trends in Switzerland

Nation-wide phenological observations have been made in Switzerland since 1951. In addition to these observation programmes, there are two very long phenological series in Switzerland: leaf bud burst of horse-chestnut trees has been observed in Geneva since 1808 and full flowering of cherry trees in Liestal since 1894. In addition to the presentation of these two long phenological series, trends for 896 phenological time series have been calculated with national data from 1951 to 1998. The earlier bud burst of horse-chestnut trees in Geneva can be attributed mainly to the city effect (warmth island). This phenomenon was not observed with the cherry tree flowering in Liestal. A clear trend towards earlier appearance dates in spring and a weak tendency towards later appearance dates in autumn could be shown with data from the national observation network. It must be noted that different phenophases and plant species react differently to various environmental influences. Received: 25 October 2000 / Revised: 9 May 2001 / Accepted: 4 June 2001     

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997–2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041–2070 and 2071–2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March–April and October–November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.     

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.     

Russian Arctic warming and ‘greening’ are closely tracked by tundra shrub willows

Growth in arctic vegetation is generally expected to increase under a warming climate, particularly among deciduous shrubs. We analyzed annual ring growth for an abundant and nearly circumpolar erect willow (Salix lanata L.) from the coastal zone of the northwest Russian Arctic (Nenets Autonomous Okrug). The resulting chronology is strongly related to summer temperature for the period 1942–2005. Remarkably high correlations occur at long distances (>1600 km) across the tundra and taiga zones of West Siberia and Eastern Europe. We also found a clear relationship with photosynthetic activity for upland vegetation at a regional scale for the period 1981–2005, confirming a parallel ‘greening’ trend reported for similarly warming North American portions of the tundra biome. The standardized growth curve suggests a significant increase in shrub willow growth over the last six decades. These findings are in line with field and remote sensing studies that have assigned a strong shrub component to the reported greening signal since the early 1980s. Furthermore, the growth trend agrees with qualitative observations by nomadic Nenets reindeer herders of recent increases in willow size in the region. The quality of the chronology as a climate proxy is exceptional. Given its wide geographic distribution and the ready preservation of wood in permafrost, S. lanata L. has great potential for extended temperature reconstructions in remote areas across the Arctic.     

Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

The need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.