This study was initiated to analyze the effect of increased snow cover on plant photosynthesis in subarctic mires underlain by permafrost. Snow fences were used to increase the accumulation of snow on a subarctic permafrost mire in northern Sweden. By measuring reflected photosynthetic active radiation (PAR) the effect of snow thickness and associated delay of the start of the growing season was assessed in terms of absorbed PAR and estimated gross primary production (GPP). Six plots experienced increased snow accumulation and six plots were untreated. Incoming and reflected PAR was logged hourly from August 2010 to October 2013. In 2010 PAR measurements were coupled with flux chamber measurements to assess GPP and light use efficiency of the plots. The increased snow thickness prolonged the duration of the snow cover in spring. The delay of the growing season start in the treated plots was 18 days in 2011, 3 days in 2012 and 22 days in 2013. Results show higher PAR absorption, together with almost 35 % higher light use efficiency, in treated plots compared to untreated plots. Estimations of GPP suggest that the loss in early season photosynthesis, due to the shortening of the growing season in the treatment plots, is well compensated for by the increased absorption of PAR and higher light use efficiency throughout the whole growing seasons. This compensation is likely to be explained by increased soil moisture and nutrients together with a shift in vegetation composition associated with the accelerated permafrost thaw in the treatment plots.

Climate change has pronounced impacts on plants, particularly in environments vulnerable to warming such as alpine zones. Although plant responses in tundra and alpine environments from high latitudes have been well-studied at the community level, the overall effect of warming on global alpine plant populations and species remains unclear. We collated global data from 46 open-top chamber (OTC) studies conducted on alpine plants from mountain belts worldwide and assessed potential effects of warming on plant performance. In addition, we examined warming responses of plants from the tundra zone (Arctic tundra and alpine tundra) in circumpolar regions. In terms of growth and reproductive output, the overall response of 91 plant species was highly positive. Shrubs grew significantly larger and expressed higher reproduction under warming compared to forbs and graminoids. Arctic tundra plants tended to respond more positively to warming compared to alpine tundra plants. We also found that plant responses were greater with increasing precipitation across circumpolar tundra, but not across alpine zones. Phenotypic plasticity in size- and fitness-related traits were similar for both alpine and tundra zones. Our findings support the notion that global warming can cause significant changes to alpine environments. Due to changes in biotic interactions, alpine tundra plants may be more negatively affected by warming compared to Arctic tundra plants which responded more positively to warming. Similarly, if shrubs are most advantaged under warming, their invasion into higher elevations may threaten the ecological functioning of alpine ecosystems, which is another serious challenge from climate change.

Recent work has provided ample evidence that nonlinear methods of time series analysis potentially allow for detecting periods of anomalous dynamics in paleoclimate proxy records that are otherwise hidden to classical statistical analysis. Following upon these ideas, in this study, we systematically test a set of Late Holocene terrestrial paleoclimate records from Northern Europe for indications of intermittent periods of time- irreversibility during which the data are incompatible with a stationary linear-stochastic process. Our analysis reveals that the onsets of both the Medieval Climate Anomaly and the Little Ice Age, the end of the Roman Warm Period, and the Late Antique Little Ice Age have been characterized by such dynamical anomalies. These findings may indicate qualitative changes in the dominant regime of interannual climate variability in terms of large-scale atmospheric circulation patterns, ocean-atmosphere interactions, and external forcings affecting the climate of the North Atlantic region.

Extreme precipitation events (EPEs) have a major impact across Arctic Fennoscandia (AF). Here we examine the spatial variability of seasonal 50-year trends in three EPEs across AF for 1968–2017, using daily precipitation data from 46 meteorological stations, and analyse how these are related to contemporaneous changes in the principal atmospheric circulation patterns that impact AF climate. Positive trends in seasonal wet-day precipitation (PRCPTOT) are widespread across AF in all seasons except autumn. Spring (autumn) has the most widespread negative (positive) trends in consecutive dry days (CDD). There is less seasonal dependence for trends in consecutive wet days (CWDs), but the majority of the stations show an increase. Clear seasonal differences in the circulation pattern that exerted most influence on these AF EPE trends exist. In spring, PRCPTOT and CDD are most affected by the Scandinavian pattern at more than half the stations while it also has a marked influence on CWD. The East Atlantic/Western Russia pattern generally has the greatest influence on the most station EPE trends in summer and autumn, yet has no effect during either spring or winter. In winter, the dominant circulation pattern across AF varies more between the different EPEs, with the North Atlantic Oscillation, Polar/Eurasia and East Atlantic patterns all exerting a major influence. There are distinct geographical distributions to the dominant pattern affecting particular EPEs in some seasons, especially winter, while in others there is no discernible spatial relationship.

We developed calibration models and reconstructed climate for sites in the central and eastern Canadian High Arctic using dendroclimatological and stable isotope analysis techniques on the dwarf-shrub, Cassiope tetragona. Our results may suggest complex temporal and spatial patterns of climate change in the region over the past century. For sites on Bathurst and Devon Islands, we reconstructed fall mean and June-July mean temperature using multiple linear regression analysis that explained 54 % and 40 % of the variance, respectively. The predictor variables included annual growth, annual production of leaves, flower buds and annual delta A(1)A(3)C values for the Bathurst Island model, and annual growth and delta A(1)A(3)C values for the Devon Island model. Both models revealed warmer than average temperatures throughout the mid-20th century, followed by a cooling trend from the early 1960s and mid-1970s at the Devon and Bathurst Island sites, respectively. Temperatures remained cool until the early 1980s and then increased until 1998/1999 at both sites. Our models are supported by other paleoclimate proxies and the instrumental record from the Canadian Arctic. For sites on Axel Heiberg and Bathurst Islands, we developed models using multivariate regresssion for February and March total precipitation that explained 44 % and 42 % of the variance, respectively. The Axel Heiberg Island model included annual production of flowers and flower buds, as well as annual delta A(1)A(3)C values as predictor variables, while the Bathurst Island model only included the annual production of flower buds as a predictor. Both models showed lower than average precipitation from the early to mid-1900s, followed by increasing precipitation from the late 1980s to 1998/1999. Our precipitation models, supported by instrumental and proxy data, suggest a trend of increasing late-winter/early spring precipitation in the late 20th century. The lack of a single detectable climate signal across the study sites suggests local climate, topography, genetic variation and/or ecological conditions may dictate, in part, site responses and result in a heterogeneous climatescape over space and time. Yet, like other arctic paleoclimate proxies, chronology error and temporal discrepancies may complicate our interpretations. However, comparisons with other arctic proxies and the meteorological record suggest our models have also registered a regional climate signal.

We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes.

The dynamic vegetation model (LPJ-GUESS) is used to project transient impacts of changes in climate on vegetation of the Barents Region. We incorporate additional plant functional types, i.e. shrubs and defined different types of open ground vegetation, to improve the representation of arctic vegetation in the global model. We use future climate projections as well as control climate data for 1981-2000 from a regional climate model (REMO) that assumes a development of atmospheric CO(2)-concentration according to the B2-SRES scenario [IPCC, Climate Change 2001: The scientific basis. Contribution working group I to the Third assessment report of the IPCC. Cambridge University Press, Cambridge (2001)]. The model showed a generally good fit with observed data, both qualitatively when model outputs were compared to vegetation maps and quantitatively when compared with observations of biomass, NPP and LAI. The main discrepancy between the model output and observed vegetation is the overestimation of forest abundance for the northern parts of the Kola Peninsula that cannot be explained by climatic factors alone. Over the next hundred years, the model predicted an increase in boreal needle leaved evergreen forest, as extensions northwards and upwards in mountain areas, and as an increase in biomass, NPP and LAI. The model also projected that shade-intolerant broadleaved summergreen trees will be found further north and higher up in the mountain areas. Surprisingly, shrublands will decrease in extent as they are replaced by forest at their southern margins and restricted to areas high up in the mountains and to areas in northern Russia. Open ground vegetation will largely disappear in the Scandinavian mountains. Also counter-intuitively, tundra will increase in abundance due to the occupation of previously unvegetated areas in the northern part of the Barents Region. Spring greening will occur earlier and LAI will increase. Consequently, albedo will decrease both in summer and winter time, particularly in the Scandinavian mountains (by up to 18%). Although this positive feedback to climate could be offset to some extent by increased CO(2) drawdown from vegetation, increasing soil respiration results in NEE close to zero, so we cannot conclude to what extent or whether the Barents Region will become a source or a sink of CO(2).

Background insect herbivory, in addition to insect outbreaks, can have an important long term influence on the performance of tree species. Since a projected warmer climate may favour insect herbivores, we use a dynamic ecosystem model to investigate the impacts of background herbivory on vegetation growth and productivity, as well as distribution and associated changes in terrestrial ecosystems of northern Europe. We used the GUESS ecosystem modelling framework and a simple linear model for including the leaf area loss of Betula pubescens in relation to mean July temperature. We tested the sensitivity of the responses of the simulated ecosystems to different, but realistic, degrees of insect damage. Predicted temperature increases are likely to enhance the potential insect impacts on vegetation. The impacts are strongest in the eastern areas, where potential insect damage to B. pubescens can increase by 4–5%. The increase in insect damage to B. pubescens results in a reduction of total birch leaf area (LAI), total birch biomass and birch productivity (Net Primary Production). This effect is stronger than the insect damage to leaf area alone would suggest, due to its second order effect on the competition between tree species. The model's demonstration that background herbivory may cause changes in vegetation structure suggests that insect damage, generally neglected by vegetation models, can change predictions of future forest composition. Carbon fluxes and albedo are only slightly influenced by background insect herbivory, indicating that background insect damage is of minor importance for estimating the feedback of terrestrial ecosystems to climate change.