(Table 3) Leaf area and leaf nitrogen for deciduous, evergreen, forb and graminoid species at Barrow, Svalbard and Zackenberg

Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub-Arctic tundra are leaf area index (LT) and total foliar nitrogen (NT). LT and NT have been shown to be tightly coupled across PFTs in sub-Arctic tundra vegetation, which simplifies up-scaling by allowing quantification of the main drivers of P from remotely sensed LT. Our objective was to test the LT-NT relationship across multiple Arctic latitudes and to assess LT as a predictor of P for the pan-Arctic. Including PFT-specific parameters in models of LT-NT coupling provided only incremental improvements in model fit, but significant improvements were gained from including site-specific parameters. The degree of curvature in the LT-NT relationship, controlled by a fitted canopy nitrogen extinction co-efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (NM), and we show for the first time that LT-NT coupling is achieved across latitudes via canopy-scale trade-offs between NM and leaf mass per unit leaf area (LM). Site-specific parameters provided small but significant improvements in models of P based on LT and moss cover. Our results suggest that differences in LT-NT coupling between sites could be used to improve pan-Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.

Environmental characteristics, and growth traits and leaf chemistry of tundra plants in a warming experiment at Alexandra Fiord

Understanding plant trait responses to elevated temperatures in the Arctic is critical in light of recent and continuing climate change, especially because these traits act as key mechanisms in climate-vegetation feedbacks. Since 1992, we have artificially warmed three plant communities at Alexandra Fiord, Nunavut, Canada (79°N). In each of the communities, we used open-top chambers (OTCs) to passively warm vegetation by 1-2 °C. In the summer of 2008, we investigated the intraspecific trait responses of five key species to 16 years of continuous warming. We examined eight traits that quantify different aspects of plant performance: leaf size, specific leaf area (SLA), leaf dry matter content (LDMC), plant height, leaf carbon concentration, leaf nitrogen concentration, leaf carbon isotope discrimination (LCID), and leaf d15N. Long-term artificial warming affected five traits, including at least one trait in every species studied. The evergreen shrub Cassiope tetragona responded most frequently (increased leaf size and plant height/decreased SLA, leaf carbon concentration, and LCID), followed by the deciduous shrub Salix arctica (increased leaf size and plant height/decreased SLA) and the evergreen shrub Dryas integrifolia (increased leaf size and plant height/decreased LCID), the forb Oxyria digyna (increased leaf size and plant height), and the sedge Eriophorum angustifolium spp. triste (decreased leaf carbon concentration). Warming did not affect d15N, leaf nitrogen concentration, or LDMC. Overall, growth traits were more sensitive to warming than leaf chemistry traits. Notably, we found that responses to warming were sustained, even after many years of treatment. Our work suggests that tundra plants in the High Arctic will show a multifaceted response to warming, often including taller shoots with larger leaves.

Time-series of snow spectral albedo and superficial snow specific surface area at Dome C in Antarctica, 2012-2015

Spectral albedo has been measured at Dome C since December 2012 in the visible and near infrared (400 - 1050 nm) at sub-hourly resolution using a home-made spectral radiometer. Superficial specific surface area (SSA) has been estimated by fitting the observed albedo spectra to the analytical Asymptotic Approximation Radiative Transfer theory (AART). The dataset includes fully-calibrated albedo and SSA that pass several quality checks as described in the companion article. Only data for solar zenith angles less than 75° have been included, which theoretically spans the period October-March. In addition, to correct for residual errors still affecting data after the calibration, especially at the solar zenith angles higher than 60°, we produced a higher quality albedo time-series as follows: In the SSA estimation process described in the companion paper, a scaling coefficient A between the observed albedo and the theoretical model predictions was introduced to cope with these errors. This coefficient thus provides a first order estimate of the residual error. By dividing the albedo by this coefficient, we produced the "scaled fully-calibrated albedo". We strongly recommend to use the latter for most applications because it generally remains in the physical range 0-1. The former albedo is provided for reference to the companion paper and because it does not depend on the SSA estimation process and its underlying assumptions.

Responses of three tropical seagrass species to CO2 enrichment

Increased atmospheric carbon dioxide leads to ocean acidification and carbon dioxide (CO2) enrichment of seawater. Given the important ecological functions of seagrass meadows, understanding their responses to CO2 will be critical for the management of coastal ecosystems. This study examined the physiological responses of three tropical seagrasses to a range of seawater pCO2 levels in a laboratory. Cymodocea serrulata, Halodule uninervis and Thalassia hemprichii were exposed to four different pCO2 treatments (442-1204 µatm) for 2 weeks, approximating the range of end-of-century emission scenarios. Photosynthetic responses were quantified using optode-based oxygen flux measurements. Across all three species, net productivity and energetic surplus (PG:R) significantly increased with a rise in pCO2 (linear models, P < 0.05). Photosynthesis-irradiance curve-derived photosynthetic parameters-maximum photosynthetic rates (P max) and efficiency (alpha) also increased as pCO2 increased (linear models, P < 0.05). The response for productivity measures was similar across species, i.e. similar slopes in linear models. A decrease in compensation light requirement (Ec) with increasing pCO2 was evident in C. serrulata and H. uninervis, but not in T. hemprichii. Despite higher productivity with pCO2 enrichment, leaf growth rates in C. serrulata did not increase, while those in H. uninervis and T. hemprichii significantly increased with increasing pCO2 levels. While seagrasses can be carbon-limited and productivity can respond positively to CO2 enrichment, varying carbon allocation strategies amongst species suggest differential growth response between species. Thus, future increase in seawater CO2 concentration may lead to an overall increase in seagrass biomass and productivity, as well as community changes in seagrass meadows.

European Leaf Physiognomic Approach ELPA

Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.

Effects of plant functional traits on soil stability: intraspecific variability matters

This data set describes different vegetation, soil and plant functional traits (PFTs) of 15 plant species in 30 sampling plots of an agricultural landscape in the Haean-myun catchment in South Korea. We divided the data set into two main tables, the first one includes the PFTs data of the 15 studied plant species, and the second one includes the soil and vegetation characteristics of the 30 sampling plots. For a total of 150 individuals, we measures the maximum plant height (cm) and leaf size (cm**2), which means the leaf surface area for the aboveground compartment of each individual. For the belowground compartment, we measured root horizontal width, which is the maximum horizontal spread of the root, rooting length, which is the maximum rooting depth, root diameter, which is the average root diameter of a the whole root, specific root length (SRL), which is the root length divided by the root dry mass, and root/shoot ratio, which is the root dry mass divided by the shoot dry mass. At each of the 30 studied plots, we estimated three different variables describing the vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and root density (estimated using a 30 cm x 30 cm metallic frame divided into nine 10 cm x 10 cm grids placed on the soil profile), as we calculated the total number of roots that appear in each of the nine grids and then we converted it into percentage based on the root count, following. Moreover, in each plot we estimated six different soil variables: Bulk density (g/cm**3), clay % (i.e. percentage of clay), silt % (i.e. percentage of silt), soil aggregate stability, using mean weight diameter (MWD), penetration resistance (kg/cm**2), using pocket penetrometer and soil shear vane strength (kPa).

Eddy covariance and environmental data of boreal bogs plant species

In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in photosynthetic rate and leaf area of different species. Photosynthetic properties (light-response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specific net and gross photosynthesis rates (PN and PG, respectively), which were summed to express ecosystem-level PN and PG. The ecosystem-level PG was compared with a gross primary production (GPP) estimate derived from eddy covariance measurements (EC). Species areal cover rather than differences in photosynthetic properties determined the species with the highest PG of both vascular plants and Sphagna. Species-specific contributions to the ecosystem PG varied over the growing season, which in turn determined the seasonal variation in ecosystem PG. The upscaled growing-season PG estimate, 230 g C/m**2, agreed well with the GPP estimated by the EC, 243 g C/m**2. Sphagna were superior to vascular plants in ecosystem-level PG throughout the growing season but had a lower PN. PN results indicated that areal cover of the species together with their differences in photosynthetic parameters shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efficiency appear to be potentially important for the ecosystem C sink. Results imply that functional diversity may increase the stability of C sink of boreal bogs.