Search

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.

Arctic soils play an important role in Earth's climate system, as they store large amounts of carbon that, if released, could strongly increase greenhouse gas levels in our atmosphere. Most research to date has focused on how the turnover of organic matter in these soils is regulated by abiotic factors, and few studies have considered the potential role of biotic regulation. However, arctic soils are currently missing important groups of soil organisms, and here, we highlight recent empirical evidence that soil organisms' presence or absence is key to understanding and predicting future climate feedbacks from arctic soils. We propose that the arrival of soil organisms into arctic soils may introduce “novel functions”, resulting in increased rates of, for example, nitrification, methanogenesis, litter fragmentation, or bioturbation, and thereby alleviate functional limitations of the current community. This alleviation can greatly enhance decomposition rates, in parity with effects predicted due to increasing temperatures. We base this argument on a series of emerging experimental evidence suggesting that the dispersal of until-then absent micro-, meso-, and macroorganisms (i.e. from bacteria to earthworms) into new regions and newly thawed soil layers can drastically affect soil functioning. These new observations make us question the current view that neglects organism-driven “alleviation effects” when predicting future feedbacks between arctic ecosystems and our planet's climate. We therefore advocate for an updated framework in which soil biota and the functions by which they influence ecosystem processes become essential when predicting the fate of soil functions in warming arctic ecosystems.

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9days advance and 5.5days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56days) or among years (mean range 32days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season's start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover's role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. We also compare studies of natural snow gradients with snow manipulation studies, altering snow depth and duration, to assess time scale difference of these approaches. The number of studies on snow in tundra ecosystems has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. In specific, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by manipulative studies (average 7.9 days advance, 5.5 days delay) were substantially lower than those observed over spatial gradients (mean range of 56 days) or due to interannual variation (mean range of 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates. This work was funded by the National Science Foundation (NSF grants ArcSEES-1233854, ARC 1023623, OPP-1722572, OPP-1820883, OPP-1806213, NNA-1928237).

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. We also compare studies of natural snow gradients with snow manipulation studies, altering snow depth and duration, to assess time scale difference of these approaches. The number of studies on snow in tundra ecosystems has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. In specific, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by manipulative studies (average 7.9 days advance, 5.5 days delay) were substantially lower than those observed over spatial gradients (mean range of 56 days) or due to interannual variation (mean range of 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates. publishedVersion

Supplementary File: Digital, Three-Dimensional Visualization of Root Systems in Peat

Supplementary Files: Digital, Three-Dimensional Visualization of Root Systems in Peat

Decomposition of plant litter is a key control over carbon (C) storage in the soil. The biochemistry of the litter being produced, the environment in which the decomposition is taking place, and the community composition and metabolism of the decomposer organisms exert a combined influence over decomposition rates. As deciduous shrubs and trees are expanding into tundra ecosystems as a result of regional climate warming, this change in vegetation represents a change in litter input to tundra soils and a change in the environment in which litter decomposes. To test the importance of litter biochemistry and environment in determining litter mass loss, we reciprocally transplanted litter between heath (Empetrum nigrum), shrub (Betula nana) and forest (Betula pubescens) at a sub-arctic tree-line in Sweden. As expansion of shrubs and trees promotes deeper snow, we also used a snow fence experiment in a tundra heath environment to understand the importance of snow depth, relative to other factors, in the decomposition of litter. Our results show that B. pubescens and B. nana leaf litter decomposed at faster rates than E. nigrum litter across all environments, while all litter species decomposed at faster rates in the forest and shrub environments than in the tundra heath. The effect of increased snow on decomposition was minimal, leading us to conclude that microbial activity over summer in the productive forest and shrub vegetation is driving increased mass loss compared to the heath. Using B. pubescens and E. nigrum litter, we demonstrate that degradation of carbohydrate-C is a significant driver of mass loss in the forest. This pathway was less prominent in the heath, which is consistent with observations that tundra soils typically have high concentrations of ‘labile’ C. This experiment suggests that further expansion of shrubs and trees may stimulate the loss of undecomposed carbohydrate-C in the tundra.

International audience

International audience; Predictions of soil organic carbon (SOC) losses in the northern circumpolar permafrost area converge around 15% (± 3% standard error) of the initial C pool by 2100 under the RCP 8.5 warming scenario. Yet, none of these estimates consider plant-soil interactions such as the rhizosphere priming effect (RPE). While laboratory experiments have shown that the input of plant-derived compounds can stimulate SOC losses by up to 1200%, the magnitude of RPE in natural ecosystems is unknown and no methods for upscaling exist so far. We here present the first spatial and depth explicit RPE model that allows estimates of RPE on a large scale (PrimeSCale). We combine available spatial data (SOC, C/N, GPP, ALT and ecosystem type) and new ecological insights to assess the importance of the RPE at the circumpolar scale. We use a positive saturating relationship between the RPE and belowground C allocation and two ALT-dependent rooting-depth distribution functions (for tundra and boreal forest) to proportionally assign belowground C allocation and RPE to individual soil depth increments. The model permits to take into account reasonable limiting factors on additional SOC losses by RPE including interactions between spatial and/or depth variation in GPP, plant root density, SOC stocks and ALT. We estimate potential RPE-induced SOC losses at 9.7 Pg C (5 - 95% CI: 1.5 - 23.2 Pg C) by 2100 (RCP 8.5). This corresponds to an increase of the current permafrost SOC-loss estimate from 15% of the initial C pool to about 16%. If we apply an additional molar C/N threshold of 20 to account for microbial C limitation as a requirement for the RPE, SOC losses by RPE are further reduced to 6.5 Pg C (5 - 95% CI: 1.0 - 16.8 Pg C) by 2100 (RCP 8.5). Although our results show that current estimates of permafrost soil C losses are robust without taking into account the RPE, our model also highlights high-RPE risk in Siberian lowland areas and Alaska north of the Brooks Range. The small overall impact of the RPE is largely explained by the interaction between belowground plant C allocation and SOC depth distribution. Our findings thus highlight the importance of fine scale interactions between plant and soil properties for large scale carbon fluxes and we provide a first model that bridges this gap and permits the quantification of RPE across a large area.

Fine roots constitute a large part of the primary production in northern (arctic and boreal) ecosystems, and are key players in ecosystem fluxes of water, nutrients and carbon. Data on root dynamics are generally rare, especially so in northern ecosystems. However, those ecosystems undergo the most rapid climatic changes on the planet and a profound understanding of form, function and dynamics of roots in such ecosystems is essential. This thesis aimed to advance our knowledge about fine root dynamics in northern ecosystems, with a focus on fine root phenology in natural plant communities and how climate change might alter it. Factors considered included thickness and duration of snow cover, thawing of permafrost, as well as natural gradients in temperature. Experiments and observational studies were located around Abisko (68°21' N, 18°45' E), and in a boreal forest close to Vindeln (64°14'N, 19°46'E), northern Sweden. Root responses included root growth, total root length, and root litter input, always involving seasonal changes therein, measured with minirhizotrons. Root biomass was also determined with destructive soil sampling. Additionally, aboveground response parameters, such as phenology and growth, and environmental parameters, such as air and soil temperatures, were assessed. This thesis reveals that aboveground patterns or responses cannot be directly translated belowground and urges a decoupling of above- and belowground phenology in terrestrial biosphere models. Specifically, root growth occurred outside of the photosynthetically active period of tundra plants. Moreover, patterns observed in arctic and boreal ecosystems diverged from those of temperate systems, and models including root parameters may thus need specific parameterization for northern ecosystems. In addition, this thesis showed that plant communities differ in root properties, and that changes in plant community compositions can thus induce changes in root dynamics and functioning. This underlines the importance of a thorough understanding of root dynamics in different plant community types in order to understand and predict how changes in plant communities in response to climate change will translate into root dynamics. Overall, this thesis describes root dynamics in response to a variety of factors, because a deeper knowledge about root dynamics will enable a better understanding of ecosystem processes, as well as improve model prediction of how northern ecosystems will respond to climate change.