Focus on Recent, Present and Future Arctic and Boreal Productivity and Biomass Changes

The reduction of cold temperature constraints on photosynthesis in recent decades has led to extended growing seasons and increased plant productivity (greening) in significant parts of Polar, Arctic and Boreal regions, here called northern lands. However, most territories within these regions display stable productivity in recent years. Smaller portions of Arctic and Boreal regions show reduced productivity (browning). Summer drought and wildfires are the best documented drivers causing browning of continental areas. Yet factors like winter warming events dampening the greening effect of more maritime regions have remained elusive, least monitored and least understood. A Norway-US network project called ArcticBiomass was launched in 2013 to further reveal both positive and negative effects of climate change on biomass in Arctic and Boreal regions. This focus collection named Focus on Recent, Present and Future Arctic and Boreal Productivity and Biomass Changes includes 24 articles and is an important outcome of this work and addresses recent changes in phenology, biomass and productivity and the mechanisms. These mechanisms include former human interactions (legacies) and drivers that control such changes (both greening and browning), along with consequences for local, regional and global scale processes. We complete our synthesis by stressing remaining challenges and knowledge gaps, and provide an outlook on future needs and research questions in the study of climate and human driven interactions in terrestrial Arctic and Boreal ecosystems.

Europe's and the World's northernmost agriculture is very vulnerable to harsh overwintering conditions. It is important from both an economic and societal standpoint to have accurate methods of predicting the severity and impact of the current snow season. Technology has advanced to enable such measurements to be regularly recorded but despite this, a detailed assessment, involving remote sensing , of the impacts of various types of snow season on agricultural yields in northernmost Europe has not previously been undertaken. Here we characterize variation in snow types and concomitant soil frost and ground-ice accumulation at a Norwegian sub-Arctic, maritime-buffered site (Tromsø, Troms County, 69 °N) during the period 1989/90 to 2013/14 and analyse how winter conditions affect agricultural productivity (both measured in the field and using remote sensing). These data were then used to build important predictive modelling approaches. In total, five contrasting types of snow season were identified, from snow-rich with no soil frost and no ground-ice to low snow and considerable soil frost and ground-ice. Conditions of low snow and low soil frost and ground-ice that result from numerous warming events were rare within the time period studied but are predicted to become the dominant snow season type. Agricultural productivity was lowest and claim settlements paid to farmers were highest after winters with high accumulation of plant-damaging, hermetic ground-ice. Deep soil frost per se did not affect primary productivity. Overall, our results together with information from other sources, suggest that icy, low snow conditions are the most challenging of all seasonal types for both the environment and livelihoods in sub-Arctic Norway. Winters with extremely deep snow also cause considerable problems. As winters are expected to warm more than summers, it is likely that the winter climate will become an even stronger regulator of northern primary productivity. To better understand the physical and biological effects of the changing winter climate, there is a requirement for continued and increasing monitoring of winter processes, especially related to frost and ice in the rhizosphere, as this is currently not well covered in national monitoring programs. Continued monitoring will enable further refinement of predictions and will support the better community planning for greatest agricultural benefit.

To understand how the Siberian boreal forests may respond to near-future climate change, we employed a modeling approach and examined thresholds for significant and irreversible changes in forest structure and composition that are likely to be reached by mid-21st century. We applied the new spatially-explicit gap-dynamics model SIBBORK toward the understanding of how transition zones, namely treelines, which are notoriously undersampled and difficult to model, may change in the near future. We found that a 2 °C change in annual average air temperature significantly altered the structure, composition, and productivity of boreal forests stands both in the northern and the southern treeline ecotones. Treeline migration occurs at smaller temperature changes. Based on the current (1990–2014) observed warming trends, a 2 °C increase in annual average temperature compared to historical climate (1961–1990) is likely to be experienced at the northern treeline by 2040 and at the southern treeline by 2050. With regards to the forest biome, the most significant warming to date has been predicted and observed in Siberia. A 2 °C increase in annual average temperature compared to the second half of the 19th century is smaller than the predictions of even the most conservative RCP2.6 climate change scenario (IPCC 2013), and has previously been assumed to not likely result in dramatic changes to ecosystems or biome shifts. We show that at a +2 °C change, biome shifts from forest to steppe are likely to occur across a large area in southern Siberia. These changes in land cover will inevitably result in changes in the biodiversity, carbon storage, and the ecosystem services provided by the boreal forests of southern Siberia.

Climate has warmed substantially in interior Alaska and several remote sensing studies have documented a decadal-scale decline in the normalized difference vegetation index (NDVI) termed a 'browning trend'. Reduced summer soil moisture due to changing climatic factors such as earlier springs, less snowpack, and summer drought may reduce boreal productivity and NDVI. However, the relative importance of these climatic factors is poorly understood in boreal interior Alaska. In this study, I used the remotely sensed peak summer NDVI as an index of boreal productivity at 250 m pixel size from 2000 to 2014. Maximum summer NDVI was related to last day of spring snow, early spring snow water equivalent (SWE), and a summer moisture index. There was no significant correlation between early spring SWE and peak summer NDVI. There was a significant correlation between the last day of spring snow and peak summer NDVI, but only for a few higher elevation stations. This was likely due to snowmelt occurring later at higher elevations, thus having a greater effect on summer soil moisture relative to lower elevation sites. For most of boreal interior Alaska, summer drought was likely the dominant control on peak summer NDVI and this effect may persist for several years. Peak summer NDVI declined at all 26 stations after the 2004 drought, and the decline persisted for 2 years at all stations. Due to the shallow rooting zone of most boreal plants, even cool and moist sites at lower elevations are likely vulnerable to drought. For example the peak summer NDVI response following the 2004 drought was similar for adjacent cold and warm watershed basins. Thus, if frequent and severe summer droughts continue, moisture stress effects are likely to be widespread and prolonged throughout most of interior boreal Alaska, including relatively cool, moist sites regardless of spring snowpack conditions or spring phenology.

Shrub expansion in tundra ecosystems may act as a positive feedback to climate warming, the strength of which depends on its spatial extent. Recent studies have shown that shrub expansion is more likely to occur in areas with high soil moisture and nutrient availability, conditions typically found in sub-surface water channels known as water tracks. Water tracks are 5–15 m wide channels of subsurface water drainage in permafrost landscapes and are characterized by deeper seasonal thaw depth, warmer soil temperatures, and higher soil moisture and nutrient content relative to adjacent tundra. Consequently, enhanced vegetation productivity, and dominance by tall deciduous shrubs, are typical in water tracks. Quantifying the distribution of water tracks may inform investigations of the extent of shrub expansion and associated impacts on tundra ecosystem carbon cycling. Here, we quantify the distribution of water tracks and their contribution to growing season CO₂ dynamics for a Siberian tundra landscape using satellite observations, meteorological data, and field measurements. We find that water tracks occupy 7.4% of the 448 km² study area, and account for a slightly larger proportion of growing season carbon uptake relative to surrounding tundra. For areas inside water tracks dominated by shrubs, field observations revealed higher shrub biomass and higher ecosystem respiration and gross primary productivity relative to adjacent upland tundra. Conversely, a comparison of graminoid-dominated areas in water tracks and inter-track tundra revealed that water track locations dominated by graminoids had lower shrub biomass yet increased net uptake of CO₂. Our results show water tracks are an important component of this landscape. Their distribution will influence ecosystem structural and functional responses to climate, and is therefore of importance for modeling.

Arctic ecosystems are undergoing rapid changes as a result of climate warming and more frequent disturbances. Disturbances can have particularly large effects on high-latitude ecosystems when ecosystem structure and function is controlled by strong feedbacks between soil conditions, vegetation, and ground thermal regime. In this study we investigated the impact of road construction and maintenance on vegetation structure and biomass along the Dempster Highway where it crosses the Peel Plateau in the Northwest Territories. To explore drivers of tall shrub proliferation and to quantify shrub proliferation in this region of continuous permafrost, greyscale air photos (1975) and Quickbird satellite imagery (2008) were used to map landcover change within two 0.6 km² belts next to the road and two 0.6 km² belts 500 m away from the road. Maps showing areas where: 1) tall shrubs expanded, and 2) dwarf shrub tundra resisted invasion were then used to select field sites where a suite of biophysical variables were measured. Rapid tall shrub proliferation and greater biomass adjacent to the road indicate that disturbance can facilitate vegetation change in tundra environments. Our field data also suggests that increased shrub proliferation adjacent to the road was caused by greater soil moisture. Tall shrub proliferation adjacent to the road occurred at lower elevation sites characterized by wetter soils with thicker organic layers. Areas that resisted tall shrub encroachment were located at higher elevations and had drier soils with thin organic layers. Our observations also support previous work illustrating that tall shrub expansion next to the highway promotes strong positive feedbacks to ongoing shrub growth and proliferation.

Climate warming is known to increase the aboveground productivity of tundra ecosystems. Recently, belowground biomass is receiving more attention, but the effects of climate warming on belowground productivity remain unclear. Enhanced understanding of the belowground component of the tundra is important in the context of climate warming, since most carbon is sequestered belowground in these ecosystems. In this study we synthesized published tundra belowground biomass data from 36 field studies spanning a mean annual temperature (MAT) gradient from −20 °C to 0 °C across the tundra biome, and determined the relationships between different plant biomass pools and MAT. Our results show that the plant community biomass–temperature relationships are significantly different between above and belowground. Aboveground biomass clearly increased with MAT, whereas total belowground biomass and fine root biomass did not show a significant increase over the broad MAT gradient. Our results suggest that biomass allocation of tundra vegetation shifts towards aboveground in warmer conditions, which could impact on the carbon cycling in tundra ecosystems through altered litter input and distribution in the soil, as well as possible changes in root turnover.

Satellite-derived remote-sensing products are providing a modern circumpolar perspective of Arctic vegetation and its changes, but this new view is dependent on a long heritage of ground-based observations in the Arctic. Several products of the Conservation of Arctic Flora and Fauna are key to our current understanding. We review aspects of the PanArctic Flora, the Circumpolar Arctic Vegetation Map, the Arctic Biodiversity Assessment, and the Arctic Vegetation Archive (AVA) as they relate to efforts to describe and map the vegetation, plant biomass, and biodiversity of the Arctic at circumpolar, regional, landscape and plot scales. Cornerstones for all these tools are ground-based plant-species and plant-community surveys. The AVA is in progress and will store plot-based vegetation observations in a public-accessible database for vegetation classification, modeling, diversity studies, and other applications. We present the current status of the Alaska Arctic Vegetation Archive (AVA-AK), as a regional example for the panarctic archive, and with a roadmap for a coordinated international approach to survey, archive and classify Arctic vegetation. We note the need for more consistent standards of plot-based observations, and make several recommendations to improve the linkage between plot-based observations biodiversity studies and satellite-based observations of Arctic vegetation.

Monitoring and understanding climate-induced changes in the boreal and arctic vegetation is critical to aid in prognosticating their future. We used a 33 year (1982–2014) long record of satellite observations to robustly assess changes in metrics of growing season (onset: SOS, end: EOS and length: LOS) and seasonal total gross primary productivity. Particular attention was paid to evaluating the accuracy of these metrics by comparing them to multiple independent direct and indirect growing season and productivity measures. These comparisons reveal that the derived metrics capture the spatio-temporal variations and trends with acceptable significance level (generally p < 0.05). We find that LOS has lengthened by 2.60 d dec⁻¹ (p < 0.05) due to an earlier onset of SOS (−1.61 d dec⁻¹, p < 0.05) and a delayed EOS (0.67 d dec⁻¹, p < 0.1) at the circumpolar scale over the past three decades. Relatively greater rates of changes in growing season were observed in Eurasia (EA) and in boreal regions than in North America (NA) and the arctic regions. However, this tendency of earlier SOS and delayed EOS was prominent only during the earlier part of the data record (1982–1999). During the later part (2000–2014), this tendency was reversed, i.e. delayed SOS and earlier EOS. As for seasonal total productivity, we find that 42.0% of northern vegetation shows a statistically significant (p < 0.1) greening trend over the last three decades. This greening translates to a 20.9% gain in productivity since 1982. In contrast, only 2.5% of northern vegetation shows browning, or a 1.2% loss of productivity. These trends in productivity were continuous through the period of record, unlike changes in growing season metrics. Similarly, we find relatively greater increasing rates of productivity in EA and in arctic regions than in NA and the boreal regions. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation during last three decades.

Satellite data from the circumpolar Arctic have shown increases in vegetation indices correlated to warming air temperatures (e.g. Bhatt et al 2013 Remote Sensing 5 4229–54). However, more information is needed at finer scales to relate the satellite trends to vegetation changes on the ground. We examined changes using Landsat TM and ETM+ data between 1985 and 2011 in the central Alaska North Slope region, where the vegetation and landscapes are relatively well-known and mapped. We calculated trends in the normalized difference vegetation index (NDVI) and tasseled-cap transformation indices, and related them to high-resolution aerial photographs, ground studies, and vegetation maps. Significant, mostly negative, changes in NDVI occurred in 7.3% of the area, with greater change in aquatic and barren types. Large reflectance changes due to erosion, deposition and lake drainage were evident. Oil industry-related changes such as construction of artificial islands, roads, and gravel pads were also easily identified. Regional trends showed decreases in NDVI for most vegetation types, but increases in tasseled-cap greenness (56% of study area, greatest for vegetation types with high shrub cover) and tasseled-cap wetness (11% of area), consistent with documented degradation of polygon ice wedges, indicating that increasing cover of water may be masking increases in vegetation when summarized using the water-sensitive NDVI.

Shrub expansion is increasingly observed in arctic and subarctic environments. The development of shrub structure may significantly impact the abiotic environment at the local scale. Our objective was to reconstruct the development of the vertical structure of Betula glandulosa Michx. and to evaluate its effects on winter and summer soil temperature and on snow depth. Stratified sampling of the shrub revealed that shrub biomass distribution followed a similar pattern in stands of contrasting heights. Woody biomass was maximal in the lower stratum and relatively stable in the intermediate strata, while the foliar biomass tracked the vertical development of the shrub structure. Dendrochronological analysis revealed that shrub stands are relatively young; most of the dominant stems started their development after 1990. Shrub height was positively associated with both the dominant stem age and its vertical growth rate. Temperature differences among sites were greater during winter (ca 10 °C) than during summer (ca 2 °C), while the sum of freezing degree-days varied from 680 °C to 2125 °C. Shrub height was the most plausible variable explaining snow depth, winter ground level temperature and the sum of freezing degree-days. However, woody biomass in the 30–40 cm strata best explained summer ground level temperature. Our results suggest that the development of a shrub structure will have far-reaching consequences on the abiotic environment of subarctic ecosystems.

In arctic tundra and boreal forest ecosystems vegetation structural and functional influences on the surface energy balance can strongly influence permafrost soil temperatures. As such, vegetation changes will likely play an important role in permafrost soil carbon dynamics and associated climate feedbacks. Processes that lead to changes in vegetation, such as wildfire or ecosystem responses to rising temperatures, are of critical importance to understanding the impacts of arctic and boreal ecosystems on future climate. Yet these processes vary within and between ecosystems and this variability has not been systematically characterized across the arctic-boreal region. Here we quantify the distribution of vegetation productivity trends, wildfire, and near-surface soil carbon, by vegetation type, across the zones of continuous and discontinuous permafrost. Siberian larch forests contain more than one quarter of permafrost soil carbon in areas of continuous permafrost. We observe pervasive positive trends in vegetation productivity in areas of continuous permafrost, whereas areas underlain by discontinuous permafrost have proportionally less positive productivity trends and an increase in areas exhibiting negative productivity trends. Fire affects a much smaller proportion of the total area and thus a smaller amount of permafrost soil carbon, with the vast majority occurring in deciduous needleleaf forests. Our results indicate that vegetation productivity trends may be linked to permafrost distribution, fire affects a relatively small proportion of permafrost soil carbon, and Siberian larch forests will play a crucial role in the strength of the permafrost carbon climate feedback.

Satellite-aided studies of vegetation cover, biomass and productivity are becoming increasingly important for monitoring the effects of a changing climate on the biosphere. With their large spatial coverage and good temporal resolution, space-borne instruments are ideal to observe remote areas over extended time periods. However, long time series datasets with global coverage have in many cases too low spatial resolution for sparsely vegetated high latitude areas. This study has made use of a newly developed 30 year 1 km spatial resolution dataset from 1986 to 2015, provided by the NOAA AVHRR series of satellites, in order to calculate the annual maximum NDVI over parts of Svalbard (78°N). This parameter is indicative of vegetation productivity and has therefore enabled us to study long-term changes in greening within the Inner Fjord Zone on Svalbard. In addition, local meteorological data are available to link maximum NDVI values to the temporal behavior of the mean growing season (summer) temperature for the study area. Over the 30 year period, we find positive trends in both maximum NDVI (average increase of 29%) and mean summer temperature (59%), which were significantly positively correlated with each other. This suggests a temporal greening trend mediated by summer warming. However, as also recently reported for lower latitudes, the strength of the year-to-year correlation between maximum NDVI and mean summer temperature decreased, suggesting that the response of vegetation to summer warming has not remained the same over the entire study period.

Studies of the normalized difference vegetation index (NDVI) have found broad changes in vegetation productivity in high northern latitudes in the past decades, including increases in NDVI ('greening') in tundra regions and decreases ('browning') in forest regions. The causes of these changes are not well understood but have been attributed to a variety of factors. We use Moderate Resolution Imaging Spectrometer (MODIS) satellite data for 2000–2014 and focus on northern West Siberia—a hot spot of extensive landcover change due to rapid resource development, geomorphic change, climate change and reindeer grazing. The region is relatively little-studied in terms of vegetation productivity patterns and trends. This study examines changes between and within bioclimatic sub-zones and reveals differences between forest and treeless areas and differences in productivity even down to the tree species level. Our results show that only 18% of the total northern West Siberia area had statistically significant changes in productivity, with 8.4% increasing (greening) and 9.6% decreasing (browning). We find spatial heterogeneity in the trends, and contrasting trends both between and within bioclimatic zones. A key finding is the identification of contrasting trends for different species within the same bioclimatic zone. Browning is most prominent in areas of denser tree coverage, and particularly in evergreen coniferous forest with dark (Picea abie, Picea obovata) or light (Pinus sylvestris) evergreen and evergreen-majority mixed forests. In contrast, low density deciduous needle-leaf forest dominated by larch (Larix sibirica), shows a significant increase in productivity, even while neighboring different species show productivity decrease. These results underscore the complexity of the patterns of variability and trends in vegetation productivity, and suggest the need for spatially and thematically detailed studies to better understand the response of different northern forest types and species to climate and environmental change.

The projected alterations to climate in the High Arctic are likely to result in changes to the short growing season, particularly with varying predicted effects on winter snowfall, the timing of summer snowmelt and air temperatures. These changes are likely to affect the phenology of interacting species in a variety of ways, but few studies have investigated the effects of combined climate drivers on plant–pollinator interactions in the High Arctic. In this study, we alter the timing of flowering phenology using a field manipulation experiment in which snow depth is increased using snow fences and temperatures are enhanced by open-top chambers (OTCs). We used this experiment to quantify the combined effects of treatments on the flowering phenology of six dominant plant species (Dryas octopetala, Cassiope tetragona, Bistorta vivipara, Saxifraga oppositifolia, Stellaria crassipes and Pedicularis hirsuita), and to simulate differing responses to climate between plants and pollinators in a subset of plots. Flowers were counted regularly throughout the growing season of 2015, and insect visitors were caught on flowers during standardised observation sessions. As expected, deep snow plots had delayed snow melt timing and this in turn delayed the first and peak flowering dates of the plants and shortened the prefloration period overall. The OTCs counteracted the delay in first and peak flowering to some extent. There was no effect of treatment on length of flowering season, although for all variables there were species-specific responses. The insect flower–visitor community was species poor, and although evidence of disruption to phenological overlaps was not found, the results do highlight the vulnerability of the plant–pollinator network in this system with differing phenological shifts between insects and plants and reduced visitation rates to flowers in plots with deep snow.

Satellites provide the only practical source of data for estimating biomass of large and remote areas such as the Alaskan Arctic. Researchers have found that the normalized difference vegetation index (NDVI) correlates well with biomass sampled on the ground. However, errors in NDVI and biomass estimates due to bidirectional reflectance distribution function (BRDF) effects are not well reported in the literature. Sun-sensor-object geometries and sensor band-width affect the BRDF, and formulas relating NDVI to ground-sampled biomass vary between projects. We examined the effects of these different variables on five studies that estimated above-ground tundra biomass of two common arctic vegetation types that dominate the Alaska tundra, moist acidic tussock tundra (MAT) and moist non-acidic tundra (MNT). We found that biomass estimates were up to 33% (excluding extremes) more sensitive than NDVI to BRDF effects. Variation between the sensors resulted in differences in NDVI of under 3% over all viewing geometries, and wider bands were more stable in their biomass estimates than narrow bands. MAT was more sensitive than MNT to BRDF effects due to irregularities in surface reflectance created by the tussocks. Finally, we found that studies that sampled only a narrow range of biomass and NDVI produced equations that were more difficult to correct for BRDF effects.

The duration and extent of snow cover is expected to change rapidly with climate change. Therefore, there is a need for improved monitoring of snow for the benefit of forecasting, impact assessments and the population at large. Remotely sensed techniques prove useful for remote areas where there are few field-based monitoring stations. This paper reports on a study of snow season using snow cover area fraction data from the two northernmost counties in Norway, Troms and Finnmark. The data are derived from the daily 500 m standard snow product (MOD10A1) from the NASA Terra MODerate Resolution Imaging Spectroradiometer (MODIS) sensor for the 2000–2010 period. This dataset has been processed with multi-temporal interpolation to eliminate clouds. The resulting cloud-free daily time series of snow cover fraction maps, have subsequently been used to derive the first and last snow-free day for the entire study area. In spring, the correlation between the first snow-free day mapped by MODIS data and snow data from 40 meteorological stations was highly significant (p < 0.05) for 36 of the stations, and with a of bias of less than 10 days for 34 of the stations. In autumn, 31 of the stations show highly significant (p < 0.05) correlation with MODIS data, and the bias was less than 10 days for 27 of the stations. However, in some areas and some years, the start and end of the snow season could not be detected due to long overcast periods. In spring 2002 and 2004 the first snow-free day was early, but arrived late in 2000, 2005 and 2008. In autumn 2009 snowfall arrived more than 7 days earlier in 50% of the study area as compared to the 2000–2010 average. MODIS-based snow season products will be applicable for a wide range of sectors including hydrology, nature-based industries, climate change studies and ecology. Therefore refinement and further testing of this method should be encouraged.

The duration of specific periods within a plant's life cycle are critical for plant growth and performance. In the High Arctic, the start of many of these phenological periods is determined by snowmelt date, which may change in a changing climate. It has been suggested that the end of these periods during late-season are triggered by external cues, such as day length, light quality or temperature, leading to the hypothesis that earlier or later snowmelt dates will lengthen or shorten the duration of these periods, respectively, and thereby affect plant performance. We tested whether snowmelt date controls phenology and phenological period duration in High Arctic Svalbard using a melt timing gradient from natural and experimentally altered snow depths. We investigated the response of early- and late-season phenophases from both vegetative and reproductive phenological periods of eight common species. We found that all phenophases follow snowmelt patterns, irrespective of timing of occurrence, vegetative or reproductive nature. Three of four phenological period durations based on these phenophases were fixed for most species, defining the studied species as periodic. Periodicity can thus be considered an evolutionary trait leading to disadvantages compared with aperiodic species and we conclude that the mesic and heath vegetation types in Svalbard are at risk of being outcompeted by invading, aperiodic species from milder biomes.

Previous studies have shown that climate warming is causing shrub cover to increase at high latitudes. Increased shrub cover generally lowers surface albedo, which results in higher energy absorption and further warming. In parts of Fennoscandia, herbivory is known to control vegetation height and abundance, and thus preventing this positive feedback. Here, we combine field measurements of albedo, herbivory and vegetation characteristics in four topographically-defined vegetation types of varying shrub height and abundance with land surface modeling (JULES) to investigate if reindeer grazing can influence the energy balance of an arctic tundra. We find that when reindeer reduces shrub height and abundance, summer albedo increases in both Betula nana-dominated heath vegetation and Salix glauca-dominated willow depressions. Model results reveal associated lower net radiation, and latent and sensible heat fluxes in heavily-grazed sites in all shrub-dominated vegetation types. Our results also suggest that the structural shift from graminoid to shrub tundra drives the difference in summer albedo, rather than shifts from dwarf-shrub to tall-shrub tundra. Reindeer has thus a potential cooling effect on climate by increasing summer albedo and decreasing net radiation, which highlights the importance of mammalian herbivores for the earth system beyond their local grazing impacts. However, the strong effects of reindeer on albedo are probably restricted to areas with high reindeer densities, since a dramatic vegetation change is essential. The importance of these processes across the whole range of reindeer densities found in the arctic tundra needs to be further evaluated.

Climate change is occurring across the world, with effects varying by ecosystem and region but already occurring quickly in high-latitude and high-altitude regions. Biotic interactions are important in determining ecosystem response to such changes, but few studies have been long-term in nature, especially in the High Arctic. Mesic tundra plots on Svalbard, Norway, were subjected to grazing at two different intensities by captive Barnacle geese from 2003–2005, in a factorial design with warming by Open Top Chambers. Warming manipulations were continued through 2014, when we measured vegetation structure and composition as well as growth and reproduction of three dominant species in the mesic meadow. Significantly more dead vascular plant material was found in warmed compared to ambient plots, regardless of grazing history, but in contrast to many short-term experiments no difference in the amount of living material was found. This has strong implications for nutrient and carbon cycling and could feed back into community productivity. Dominant species showed increased flowering in warmed plots, especially in those plots where grazing had been applied. However, this added sexual reproduction did not translate to substantial shifts in vegetative cover. Forbs and rushes increased slightly in warmed plots regardless of grazing, while the dominant shrub, Salix polaris, generally declined with effects dependent on grazing, and the evergreen shrub Dryas octopetala declined with previous intensive grazing. There were no treatment effects on community diversity or evenness. Thus despite no changes in total live abundance, a typical short-term response to environmental conditions, we found pronounced changes in dead biomass indicating that tundra ecosystem processes respond to medium- to long-term changes in conditions caused by 12 seasons of summer warming. We suggest that while high arctic tundra plant communities are fairly resistant to current levels of climate warming, underlying ecosystem processes are beginning to change. In addition, even short bouts of intense herbivory can have long-term consequences for some species in these communities.

Warming in the Arctic has resulted in a lengthening of the growing season and changes to the distribution and composition of tundra vegetation including increased biomass quantities in the Low Arctic. Biomass has commonly been estimated using broad-band greenness indices such as NDVI; however, vegetation changes in the Arctic are occurring at spatial scales within a few meters. The aim of this paper is to assess the ability of hyperspectral remote sensing data to estimate biomass quantities among different plant tissue type categories at the North Slope site of Ivotuk, Alaska. Hand-held hyperspectral data and harvested biomass measurements were collected during the 1999 growing season. A subset of the data was used as a training set, and was regressed against the hyperspectral bands using LASSO. LASSO is a modification of SPLS and is a variable selection technique that is useful in studies with high collinearity among predictor variables such as hyperspectral remote sensing. The resulting equations were then used to predict biomass quantities for the remaining Ivotuk data. The majority of significant biomass-spectra relationships (65%) were for shrubs categories during all times of the growing season and bands in the blue, green, and red edge wavelength regions of the spectrum. The ability to identify unique biomass-spectra relationships per community is decreased at the height of the growing season when shrubs obscure lower-lying vegetation such as mosses. The results of this study support previous research arguing that shrubs are dominant controls over spectral reflectance in Low Arctic communities and that this dominance results in an increased ability to estimate shrub component biomass over other plant functional types.

Potential climate drivers of Arctic tundra vegetation productivity are investigated to understand recent greening and browning trends documented by maximum normalized difference vegetation index (NDVI) (MaxNDVI) and time-integrated NDVI (TI-NDVI) for 1982–2015. Over this period, summer sea ice has continued to decline while oceanic heat content has increased. The increases in summer warmth index (SWI) and NDVI have not been uniform over the satellite record. SWI increased from 1982 to the mid-1990s and remained relatively flat from 1998 onwards until a recent upturn. While MaxNDVI displays positive trends from 1982–2015, TI-NDVI increased from 1982 until 2001 and has declined since. The data for the first and second halves of the record were analyzed and compared spatially for changing trends with a focus on the growing season. Negative trends for MaxNDVI and TI-NDVI were more common during 1999–2015 compared to 1982–1998.

Trend analysis within the growing season reveals that sea ice decline was larger in spring for the 1982–1998 period compared to 1999–2015, while fall sea ice decline was larger in the later period. Land surface temperature trends for the 1982–1998 growing season are positive and for 1999–2015 are positive in May–June but weakly negative in July–August. Spring biweekly NDVI trends are positive and significant for 1982–1998, consistent with increasing open water and increased available warmth in spring. MaxNDVI trends for 1999–2015 display significant negative trends in May and the first half of June.

Numerous possible drivers of early growing season NDVI decline coincident with warming temperatures are discussed, including increased standing water, delayed spring snow-melt, winter thaw events, and early snow melt followed by freezing temperatures. Further research is needed to robustly identify drivers of the spring NDVI decline.

Woody shrubs have increased in biomass and expanded into new areas throughout the Pan-Arctic tundra biome in recent decades, which has been linked to a biome-wide observed increase in productivity. Experimental, observational, and socio-ecological research suggests that air temperature—and to a lesser degree precipitation—trends have been the predominant drivers of this change. However, a progressive decoupling of these drivers from Arctic vegetation productivity has been reported, and since 2010, vegetation productivity has also been declining. We created a protocol to (a) identify the suite of controls that may be operating on shrub growth and expansion, and (b) characterise the evidence base for controls on Arctic shrub growth and expansion. We found evidence for a suite of 23 proximal controls that operate directly on shrub growth and expansion; the evidence base focused predominantly on just four controls (air temperature, soil moisture, herbivory, and snow dynamics). 65% of evidence was generated in the warmest tundra climes, while 24% was from only one of 28 floristic sectors. Temporal limitations beyond 10 years existed for most controls, while the use of space-for-time approaches was high, with 14% of the evidence derived via experimental approaches. The findings suggest the current evidence base is not sufficiently robust or comprehensive at present to answer key questions of Pan-Arctic shrub change. We suggest future directions that could strengthen the evidence, and lead to an understanding of the key mechanisms driving changes in Arctic shrub environments.

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R²_adj. 0.42–0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000−2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000−2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R² = 0.51 and 0.44, respectively). The commonly used 'maximum NDVI' plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.