Victoria L. Sloan

The unseen iceberg: plant roots in arctic tundra

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits - including distribution, chemistry, anatomy and resource partitioning - play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions.

Ecosystem change and stability over multiple decades in the Swedish subarctic: complex processes and multiple drivers

The subarctic environment of northernmost Sweden has changed over the past century, particularly elements of climate and cryosphere. This paper presents a unique geo-referenced record of environmental and ecosystem observations from the area since 1913. Abiotic changes have been substantial. Vegetation changes include not only increases in growth and range extension but also counterintuitive decreases, and stability: all three possible responses. Changes in species composition within the major plant communities have ranged between almost no changes to almost a 50 per cent increase in the number of species. Changes in plant species abundance also vary with particularly large increases in trees and shrubs (up to 600%). There has been an increase in abundance of aspen and large changes in other plant communities responding to wetland area increases resulting from permafrost thaw. Populations of herbivores have responded to varying management practices and climate regimes, particularly changing snow conditions. While it is difficult to generalize and scale-up the site-specific changes in ecosystems, this very site-specificity, combined with projections of change, is of immediate relevance to local stakeholders who need to adapt to new opportunities and to respond to challenges. Furthermore, the relatively small area and its unique datasets are a microcosm of the complexity of Arctic landscapes in transition that remains to be documented.

A pan-Arctic synthesis of CH4 and CO2 production from anoxic soil incubations

Permafrost thaw can alter the soil environment through changes in soil moisture, frequently resulting in soil saturation, a shift to anaerobic decomposition, and changes in the plant community. These changes, along with thawing of previously frozen organic material, can alter the form and magnitude of greenhouse gas production from permafrost ecosystems. We synthesized existing methane (CH4 ) and carbon dioxide (CO2 ) production measurements from anaerobic incubations of boreal and tundra soils from the geographic permafrost region to evaluate large-scale controls of anaerobic CO2 and CH4 production and compare the relative importance of landscape-level factors (e.g., vegetation type and landscape position), soil properties (e.g., pH, depth, and soil type), and soil environmental conditions (e.g., temperature and relative water table position). We found fivefold higher maximum CH4 production per gram soil carbon from organic soils than mineral soils. Maximum CH4 production from soils in the active layer (ground that thaws and refreezes annually) was nearly four times that of permafrost per gram soil carbon, and CH4 production per gram soil carbon was two times greater from sites without permafrost than sites with permafrost. Maximum CH4 and median anaerobic CO2 production decreased with depth, while CO2 :CH4 production increased with depth. Maximum CH4 production was highest in soils with herbaceous vegetation and soils that were either consistently or periodically inundated. This synthesis identifies the need to consider biome, landscape position, and vascular/moss vegetation types when modeling CH4 production in permafrost ecosystems and suggests the need for longer-term anaerobic incubations to fully capture CH4 dynamics. Our results demonstrate that as climate warms in arctic and boreal regions, rates of anaerobic CO2 and CH4 production will increase, not only as a result of increased temperature, but also from shifts in vegetation and increased ground saturation that will accompany permafrost thaw.

Advancing the use of minirhizotrons in wetlands

BackgroundWetlands store a substantial amount of carbon (C) in deep soil organic matter deposits, and play an important role in global fluxes of carbon dioxide and methane. Fine roots (i.e., ephemeral roots that are active in water and nutrient uptake) are recognized as important components of biogeochemical cycles in nutrient-limited wetland ecosystems. However, quantification of fine-root dynamics in wetlands has generally been limited to destructive approaches, possibly because of methodological difficulties associated with the unique environmental, soil, and plant community characteristics of these systems. Non-destructive minirhizotron technology has rarely been used in wetland ecosystems.ScopeOur goal was to develop a consensus on, and a methodological framework for, the appropriate installation and use of minirhizotron technology in wetland ecosystems. Here, we discuss a number of potential solutions for the challenges associated with the deployment of minirhizotron technology in wetlands, including minirhizotron installation and anchorage, capture and analysis of minirhizotron images, and upscaling of minirhizotron data for analysis of biogeochemical pools and parameterization of land surface models.ConclusionsThe appropriate use of minirhizotron technology to examine relatively understudied fine-root dynamics in wetlands will advance our knowledge of ecosystem C and nutrient cycling in these globally important ecosystems.

The role of mosses in carbon uptake and partitioning in arctic vegetation

The Arctic is already experiencing changes in plant community composition, so understanding the contribution of different vegetation components to carbon (C) cycling is essential in order to accurately quantify ecosystem C balance. Mosses contribute substantially to biomass, but their impact on carbon use efficiency (CUE) - the proportion of gross primary productivity (GPP) incorporated into growth - and aboveground versus belowground C partitioning is poorly known. We used (13) C pulse-labelling to trace assimilated C in mosses (Sphagnum sect. Acutifolia and Pleurozium schreberi) and in dwarf shrub-P. schreberi vegetation in sub-Arctic Finland. Based on (13) C pools and fluxes, we quantified the contribution of mosses to GPP, CUE and partitioning. Mosses incorporated 20 ± 9% of total ecosystem GPP into biomass. CUE of Sphagnum was 68-71%, that of P. schreberi was 62-81% and that of dwarf shrub-P. schreberi vegetation was 58-74%. Incorporation of C belowground was 10 ± 2% of GPP, while vascular plants alone incorporated 15 ± 4% of their fixed C belowground. We have demonstrated that mosses strongly influence C uptake and retention in Arctic dwarf shrub vegetation. They increase CUE, and the fraction of GPP partitioned aboveground. Arctic C models must include mosses to accurately represent ecosystem C dynamics.

Leaf and fine root carbon stocks and turnover are coupled across Arctic ecosystems.

Estimates of vegetation carbon pools and their turnover rates are central to understanding and modelling ecosystem responses to climate change and their feedbacks to climate. In the Arctic, a region containing globally important stores of soil carbon, and where the most rapid climate change is expected over the coming century, plant communities have on average sixfold more biomass below ground than above ground, but knowledge of the root carbon pool sizes and turnover rates is limited. Here, we show that across eight plant communities, there is a significant positive relationship between leaf and fine root turnover rates (r(2) = 0.68, P < 0.05), and that the turnover rates of both leaf (r(2) = 0.63, P < 0.05) and fine root (r(2) = 0.55, P < 0.05) pools are strongly correlated with leaf area index (LAI, leaf area per unit ground area). This coupling of root and leaf dynamics supports the theory of a whole-plant economics spectrum. We also show that the size of the fine root carbon pool initially increases linearly with increasing LAI, and then levels off at LAI = 1 m(2) m(-2), suggesting a functional balance between investment in leaves and fine roots at the whole community scale. These ecological relationships not only demonstrate close links between above and below-ground plant carbon dynamics but also allow plant carbon pool sizes and their turnover rates to be predicted from the single readily quantifiable (and remotely sensed) parameter of LAI, including the possibility of estimating root data from satellites.

Long-term nitrogen deposition depletes grassland seed banks

Nitrogen (N) pollution is a global threat to the biodiversity of many plant communities, but its impacts on grassland soil seed banks are unknown. Here we show that size and richness of an acid grassland seed bank is strongly reduced after 13 years of simulated N deposition. Soils receiving 140 kg N ha(-1) per year show a decline in total seed abundance, seed species richness, and the abundance of forbs, sedges and grasses. These results reveal larger effects of N pollution on seed banks than on aboveground vegetation as cover and flowering is not significantly altered for most species. Further, the seed bank shows no recovery 4 years after the cessation of N deposition. These results provide insights into the severe negative effects of N pollution on plant communities that threaten the stability of populations, community persistence and the potential for ecosystems to recover following anthropogenic disturbance or climate change.

Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450–510 nm, 630–690 nm and 705–745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450–510 nm and 630–690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments.

Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic

Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C (Vc,max.25 and Jmax.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We measured photosynthetic CO2 response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of Vc,max and Jmax were 17% lower than commonly used values. When scaled to 25°C, Vc,max.25 and Jmax.25 were two- to five-fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf-level modeling demonstrated that current parameterization of TBMs resulted in a two-fold underestimation of the capacity for leaf-level CO2 assimilation in Arctic vegetation. This study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems

Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales.