Taiga-tundra Transition Research Articles

Methane oxidation potential of the arctic wetland soils of a taiga-tundra ecotone in northeastern Siberia

ABSTRACT Arctic wetlands are significant sources of atmospheric methane and the observed accelerated climate changes in the arctic could cause a change in methane dynamics. Methane oxidation would be the key process to control methane emission from wetlands. In this study, we determined the potential methane oxidation rate of the wetland soils of a taiga–tundra transition zone in northeastern Siberia. Peat soil samples were collected in summer from depressions covered with tussocks of sedges and Sphagnum spp. and from mounds vegetated with moss and larch trees. An aerobic bottle incubation experiment demonstrated that the soil samples collected from depressions in the moss- and sedge-dominated zones exhibited active methane oxidation with no time lag, while the mound soils showed no methane oxidation under the given conditions. The potential methane oxidation rates of the soils at 15°C ranged from 94 to 496 nmol h−1 g−1 dw. The immediate and active methane oxidation was observed over the depths studied (0–40 cm) including the water-saturated anoxic layers; the maximum methane oxidation rate was recorded in the layer above the water-saturated layer. The methane oxidation rate was temperature-dependent, but substantial methane oxidation was observed even at 0°C particularly for the moss soil samples. Soil samples collected from the frozen layer of Sphagnum peat also showed immediate methane consumption when incubated at 15°C. The present results suggest that the methane oxidizing bacteria in the wetland soils could survive under anoxic and frozen conditions keeping their potential activities and immediately utilize methane when the conditions become favorable. On the other hand, the inhibitor of methane oxidation (difluoromethane) did not affect the methane flux from the sedge and moss zones in situ, which suggested the minor role of plant-associated methane oxidation.

Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada

Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the Climate Change Initiative (CCI) LC product for use in the Canadian Land Surface Scheme (CLASS) through comparison with finer resolution datasets over Canada, assisted with reference sample data and a vegetation continuous field tree cover fraction dataset. The results show that in comparison with the finer resolution maps over Canada, the 300 m CCI product provides much improved LC distribution over that from the 1 km GLC2000 dataset currently used to provide initial surface conditions in CLASS. However, the CCI dataset appears to overestimate needleleaf forest cover especially in the taiga-tundra transition zone of northwestern Canada. This may have partly resulted from limited availability of clear sky MEdium Resolution Imaging Spectrometer (MERIS) images used to generate the CCI classification maps due to the long snow cover season in Canada. In addition, changes based on the CCI time series are not always consistent with those from the MODIS or a Landsat-based forest cover change dataset, especially prior to 2003 when only coarse spatial resolution satellite data were available for change detection in the CCI product. It will be helpful for application in global simulations to determine whether these results also apply to other regions with similar landscapes, such as Eurasia. Nevertheless, the detailed LC classes and finer spatial resolution in the CCI dataset provide an improved reference map for use in land surface models in Canada. The results also suggest that uncertainties in the current cross-walking tables are a major source of the often large differences in the plant functional types (PFT) maps, and should be an area of focus in future work.

Modelling the Arctic taiga-tundra ecotone using ALOS PALSAR and optical earth observation data

The taiga-tundra ecotone (TTE) extends over 13.400 km around the northern hemisphere and marks the transition zone between taiga and tundra. Since this area is vulnerable to climate change, human activities and natural disturbances such as wildfires, monitoring of this region is extremely important. Dealing with the characterization of this transition zone, very few studies are available on a global scale. Existing approaches lack the thorough characterization of the ecotone as they capture just a part of the complex transition zone.The objective of this research is to develop a monitoring concept for detecting the taiga-tundra interface for a designated study area in northern Siberia. We used optical and SAR remote sensing data products from 2007 to 2010, whereby the spatial resolution of all datasets were unified to 1 km. Earth Observation data and products from ALOS PALSAR, MODIS, AMSR-E were utilized in addition to digital elevation model data and the Percent Tree Cover product. Using random forest variable importance measure, most relevant statistics were selected and used for different model setups. The final random forest model setup included statistics of land surface temperature (LST), albedo, NDVI, EVI, Vegetation Continuous Fields (VCF), PALSAR HV-Polarization and LAI. Snow water equivalent (SWE) statistics had to be excluded for compensating artifacts.Since sharp distinctions between forest and tundra do not occur in nature, class probability values were computed. This allowed the unique allocation per class for each grid cell. The model setup showed high performance values, which were cross validated, with accuracies of 95.6% (± 1.5%). The model result was validated using high resolution Google Earth imagery, where an overall map accuracy of 93% (Kappa 0.89) was achieved. The assessment of the input data products revealed that statistics of LST, SWE and albedo were most important.Compared to existing circumpolar products the advantage of this approach is the derivation of continuous probability values for the taiga-tundra transition zone instead of sharp borders between the biogeographic classes. The model provides the basis for a monitoring effort aiming at detecting changes over time. This would help to understand the dynamics of ecosystem changes with respect to influencing factors.

Impact of Future Climate and Vegetation on the Hydrology of an Arctic Headwater Basin at the Tundra–Taiga Transition

Abstract The rapidly warming Arctic is experiencing permafrost degradation and shrub expansion. Future climate projections show a clear increase in mean annual temperature and increasing precipitation in the Arctic; however, the impact of these changes on hydrological cycling in Arctic headwater basins is poorly understood. This study investigates the impact of climate change, as represented by simulations using a high-resolution atmospheric model under a pseudo-global-warming configuration, and projected changes in vegetation, using a spatially distributed and physically based Arctic hydrological model, on a small headwater basin at the tundra–taiga transition in northwestern Canada. Climate projections under the RCP8.5 emission scenario show a 6.1°C warming, a 38% increase in annual precipitation, and a 19 W m−2 increase in all-wave annual irradiance over the twenty-first century. Hydrological modeling results suggest a shift in hydrological processes with maximum peak snow accumulation increasing by 70%, snow-cover duration shortening by 26 days, active layer deepening by 0.25 m, evapotranspiration increasing by 18%, and sublimation decreasing by 9%. This results in an intensification of the hydrological regime by doubling discharge volume, a 130% increase in spring runoff, and earlier and larger peak streamflow. Most hydrological changes were found to be driven by climate change; however, increasing vegetation cover and density reduced blowing snow redistribution and sublimation, and increased evaporation from intercepted rainfall. This study provides the first detailed investigation of projected changes in climate and vegetation on the hydrology of an Arctic headwater basin, and so it is expected to help inform larger-scale climate impact studies in the Arctic.

Recent changes to the hydrological cycle of an Arctic basin at the tundra–taiga transition

Abstract. The impact of transient changes in climate and vegetation on the hydrology of small Arctic headwater basins has not been investigated before, particularly in the tundra–taiga transition region. This study uses weather and land cover observations and a hydrological model suitable for cold regions to investigate historical changes in modelled hydrological processes driving the streamflow response of a small Arctic basin at the treeline. The physical processes found in this environment and explicit changes in vegetation extent and density were simulated and validated against observations of streamflow discharge, snow water equivalent and active layer thickness. Mean air temperature and all-wave irradiance have increased by 3.7 ∘C and 8.4 W m−2, respectively, while precipitation has decreased 48 mm (10 %) since 1960. Two modelling scenarios were created to separate the effects of changing climate and vegetation on hydrological processes. Results show that over 1960–2016 most hydrological changes were driven by climate changes, such as decreasing snowfall, evapotranspiration, deepening active layer thickness, earlier snow cover depletion and diminishing annual sublimation and soil moisture. However, changing vegetation has a significant impact on decreasing blowing snow redistribution and sublimation, counteracting the impact of decreasing precipitation on streamflow, demonstrating the importance of including transient changes in vegetation in long-term hydrological studies. Streamflow dropped by 38 mm as a response to the 48 mm decrease in precipitation, suggesting a small degree of hydrological resiliency. These results represent the first detailed estimate of hydrological changes occurring in small Arctic basins, and can be used as a reference to inform other studies of Arctic climate change impacts.

The Organic Component of Particulate Matter in Small Streams of the Northern Yenisei Region During the Summer-Autumn Period

A quantitative assessment is made of suspended sediment load, including particulate organic matter and organic carbon, in 2014 for the small streams of the Northern Yenisei region, in the taiga–tundra transition zone (near the city of Igarka, Krasnoyarsk krai). It was found that the suspended sediment concentration (SSC) of the streams under investigation fluctuated between 2 and 18 mg/L during the summer–autumn low-water period of 2014. The proportion of dissolved organic matter (DOM) in the total sediment yield varied from 16.4% to 74.1%, depending on landscape-geomorphological conditions for suspended sediment formation: it is higher for streams with tundra catchments and lower on forest watersheds underlain by sandy and clayey loams. The DOM content varies from catchment to catchment from 1.63 to 2.42 mg/L, and the mean concentration of dissolved organic carbon (DOC) is estimated at 0.73 to 1.09 mg C/L. It is shown that the local channel transformations serve as the main source of POM and DOC input to the water of two out of three streams under study. Surface runoff or fast subsurface flow in the organic soil horizon is the external source of DOM input to the water of the third stream during flooding. Regional empirical dependencies were obtained, which correlate the water discharge, total SSC and the proportion of DOM are obtained. The long-term proportion of DOM in the annual suspended sediment flow of the Graviika river makes up 25% and DOC, 11%, or, in absolute values, 406 and 183 t/year, and in units of layer 1.26 and 0.57 t/km2, respectively.

Biome changes and their inferred climatic drivers in northern and eastern continental Asia at selected times since 40 cal ka bp

Recent global warming is pronounced in high-latitude regions (e.g. northern Asia), and will cause the vegetation to change. Future vegetation trends (e.g. the “arctic greening”) will feed back into atmospheric circulation and the global climate system. Understanding the nature and causes of past vegetation changes is important for predicting the composition and distribution of future vegetation communities. Fossil pollen records from 468 sites in northern and eastern Asia were biomised at selected times between 40 cal ka bp and today. Biomes were also simulated using a climate-driven biome model and results from the two approaches compared in order to help understand the mechanisms behind the observed vegetation changes. The consistent biome results inferred by both approaches reveal that long-term and broad-scale vegetation patterns reflect global- to hemispheric-scale climate changes. Forest biomes increase around the beginning of the late deglaciation, become more widespread during the early and middle Holocene, and decrease in the late Holocene in fringe areas of the Asian Summer Monsoon. At the southern and southwestern margins of the taiga, forest increases in the early Holocene and shows notable species succession, which may have been caused by winter warming at ca. 7 cal ka bp. At the northeastern taiga margin (central Yakutia and northeastern Siberia), shrub expansion during the last deglaciation appears to prevent the permafrost from thawing and hinders the northward expansion of evergreen needle-leaved species until ca. 7 cal ka bp. The vegetation-climate disequilibrium during the early Holocene in the taiga-tundra transition zone suggests that projected climate warming will not cause a northward expansion of evergreen needle-leaved species.

Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model

A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

Sedimentary DNA versus morphology in the analysis of diatom-environment relationships

The Arctic treeline ecotone is characterised by a steep vegetation gradient from arctic tundra to northern taiga forests, which is thought to influence the water chemistry of thermokarst lakes in this region. Environmentally sensitive diatoms respond to such ecological changes in terms of variation in diatom diversity and richness, which so far has only been documented by microscopic surveys. We applied next-generation sequencing to analyse the diatom composition of lake sediment DNA extracted from 32 lakes across the treeline in the Khatanga region, Siberia, using a short fragment of the rbcL chloroplast gene as a genetic barcode. We compared diatom richness and diversity obtained from the genetic approach with diatom counts from traditional microscopic analysis. Both datasets were employed to investigate diversity and relationships with environmental variables, using ordination methods. After effective filtering of the raw data, the two methods gave similar results for diatom richness and composition at the genus level (DNA 12 taxa; morphology 19 taxa), even though there was a much higher absolute number of sequences obtained per genetic sample (median 50,278), compared with microscopic counts (median 426). Dissolved organic carbon explained the highest percentage of variance in both datasets (14.2 % DNA; 18.7 % morphology), reflecting the compositional turnover of diatom assemblages along the tundra-taiga transition. Differences between the two approaches are mostly a consequence of the filtering process of genetic data and limitations of genetic references in the database, which restricted the determination of genetically identified sequence types to the genus level. The morphological approach, however, allowed identifications mostly to species level, which permits better ecological interpretation of the diatom data. Nevertheless, because of a rapidly increasing reference database, the genetic approach with sediment DNA will, in the future, enable reliable investigations of diatom composition from lake sediments that will have potential applications in both paleoecology and environmental monitoring.

Pan-Arctic Climate and Land Cover Trends Derived from Multi-Variate and Multi-Scale Analyses (1981–2012)

Arctic ecosystems have been afflicted by vast changes in recent decades. Changes in temperature, as well as precipitation, are having an impact on snow cover, vegetation productivity and coverage, vegetation seasonality, surface albedo, and permafrost dynamics. The coupled climate-vegetation change in the arctic is thought to be a positive feedback in the Earth system, which can potentially further accelerate global warming. This study focuses on the co-occurrence of temperature, precipitation, snow cover, and vegetation greenness trends between 1981 and 2012 in the pan-arctic region based on coarse resolution climate and remote sensing data, as well as ground stations. Precipitation significantly increased during summer and fall. Temperature had the strongest increase during the winter months (twice than during the summer months). The snow water equivalent had the highest trends during the transition seasons of the year. Vegetation greenness trends are characterized by a constant increase during the vegetation-growing period. High spatial resolution remote sensing data were utilized to map structural vegetation changes between 1973 and 2012 for a selected test region in Northern Siberia. An intensification of woody vegetation cover at the taiga-tundra transition area was found. The observed co-occurrence of climatic and ecosystem changes is an example of the multi-scale feedbacks in the arctic ecosystems.

A pollen-climate transfer function from the tundra and taiga vegetation in Arctic Siberia and its applicability to a Holocene record

This study aims to establish, evaluate, and apply a modern pollen-climate transfer function from the transition zone between arctic tundra and light-needled taiga in Arctic Siberia. Lacustrine samples (n=96) from the northern Siberian lowlands of Yakutia were collected along four north-to-south transects crossing the arctic forest line. Samples span a broad temperature and precipitation gradient (mean July temperature, TJuly: 7.5–18.7°C; mean annual precipitation, Pann: 114–315mm/yr). Redundancy analyses are used to examine the relationship between the modern pollen signal and corresponding vegetation types and climate. Performance of transfer functions for TJuly and Pann were cross-validated and tested for spatial autocorrelation effects. The root mean square errors of prediction are 1.67°C for TJuly and 40mm/yr for Pann. A climate reconstruction based on fossil pollen spectra from a Siberian Arctic lake sediment core spanning the Holocene yielded cold conditions for the Late Glacial (1–2°C below present TJuly). Warm and moist conditions were reconstructed for the early to mid Holocene (2°C higher TJuly than present), and climate conditions similar to modern ones were reconstructed for the last 4000years. In conclusion, our modern pollen data set fills the gap of existing regional calibration sets with regard to the underrepresented Siberian tundra–taiga transition zone. The Holocene climate reconstruction indicates that the temperature deviation from modern values was only moderate despite the assumed Arctic sensitivity to present climate change.

Identification of land surface temperature and albedo trends in AVHRR Pathfinder data from 1982 to 2005 for northern Siberia

The arctic regions are highly vulnerable to climate change. Climate models predict an increase in global mean temperatures for the upcoming century. The arctic environment is subject to significant changes of the land surface. Especially the changes of vegetation pattern and the phenological cycle in the taiga–tundra transition area are of high importance in climate change research. This study focuses on time series and trend analysis of land surface temperature, albedo, snow water equivalent, and normalized difference vegetation index information in the time period of 1982–2005 for northern Siberia. The findings show strong dependencies between these parameters and their inter-annual dynamics, which indicate changes in vegetation growing period. We found a strong negative correlation between land surface temperature and albedo conditions for the beginning (60–90%) of the growing season for selected hot spot trend regions in northern Siberia.

Revealing the Hyperdiverse Mite Fauna of Subarctic Canada through DNA Barcoding

Although mites are one of the most abundant and diverse groups of arthropods, they are rarely targeted for detailed biodiversity surveys due to taxonomic constraints. We address this gap through DNA barcoding, evaluating acarine diversity at Churchill, Manitoba, a site on the tundra-taiga transition. Barcode analysis of 6279 specimens revealed nearly 900 presumptive species of mites with high species turnover between substrates and between forested and non-forested sites. Accumulation curves have not reached an asymptote for any of the three mite orders investigated, and estimates suggest that more than 1200 species of Acari occur at this locality. The coupling of DNA barcode results with taxonomic assignments revealed that Trombidiformes compose 49% of the fauna, a larger fraction than expected based on prior studies. This investigation demonstrates the efficacy of DNA barcoding in facilitating biodiversity assessments of hyperdiverse taxa.

MODIS tree cover validation for the circumpolar taiga–tundra transition zone

A validation of the 2005 500 m MODIS vegetation continuous fields (VCF) tree cover product in the circumpolar taiga–tundra ecotone was performed using high resolution Quickbird imagery. Assessing the VCF's performance near the northern limits of the boreal forest can help quantify the accuracy of the product within this vegetation transition area. The circumpolar region was divided into 7 longitudinal zones and validation sites were selected in areas of varying tree cover where Quickbird imagery is available in Google Earth. Each site was linked to the corresponding VCF pixel and overlaid with a regular dot grid within the VCF pixel's boundary to estimate percent tree crown cover in the area. Percent tree crown cover was estimated using Quickbird imagery for 396 sites throughout the circumpolar region and related to the VCF's estimates of canopy cover for 2000–2005. Regression results of VCF inter-annual comparisons (2000–2005) and VCF-Quickbird image-interpreted estimates indicate that: (1) Pixel-level, inter-annual comparisons of VCF estimates of percent canopy cover were linearly related (mean R 2 = 0.77) and exhibited an average root mean square error (RMSE) of 10.1% and an average root mean square difference (RMSD) of 7.3%. (2) A comparison of image-interpreted percent tree crown cover estimates based on dot counts on Quickbird color images by two different interpreters were more variable ( R 2 = 0.73, RMSE = 14.8%, RMSD = 18.7%) than VCF inter-annual comparisons. (3) Across the circumpolar boreal region, 2005 VCF-Quickbird comparisons were linearly related, with an R 2 = 0.57, a RMSE = 13.4% and a RMSD = 21.3%, with a tendency to over-estimate areas of low percent tree cover and anomalous VCF results in Scandinavia. The relationship of the VCF estimates and ground reference indicate to potential users that the VCF's tree cover values for individual pixels, particularly those below 20% tree cover, may not be precise enough to monitor 500 m pixel-level tree cover in the taiga–tundra transition zone.

Evaluation of global land cover data sets over the tundra–taiga transition zone in northernmost Finland

The remote sensing‐based continental to global scale land cover data sets provide several land cover depictions over the circumpolar tundra–taiga transition zone. The aim of this study was to evaluate three data sets in northernmost Finland: the Global Land Cover 2000 Northern Eurasia map (GLC2000‐NE), the MODIS global land cover map (MODIS‐IGBP) and the tree cover layer of the MODIS vegetation continuous fields product (MODIS‐VCF). The data sets were first compared both visually and statistically to biotope inventory data including tree cover, height, species composition and shrub cover information as continuous variables. The agreement with reference data was poor because the classifications do not correspond to the class descriptions. The MODIS‐VCF tree cover overestimates the tree cover in the low values and underestimates it in the high values. The agreement was relatively good when the global data sets were aggregated to a forest–non‐forest level and compared to the Finnish CORINE Land Cover 2000 map over a larger area. However, the inaccurate mapping of the deciduous broadleaf forests and mires reduced the agreement at the forest–non‐forest level. The vegetation transitions are difficult to map using low‐resolution satellite data and further improvements to the land cover characterization over the tundra–taiga transition zone are required.

Assessment of multispectral, -temporal and -angular MODIS data for tree cover mapping in the tundra–taiga transition zone

The latitudinal tree cover gradient is an important characteristic of the tundra–taiga transition zone stretching around the northern hemisphere. Accurately mapped continuous tree cover fields would enable the depiction of forest extent over this ecotone, which is sensitive to climate change, natural disturbances and human activities. The objective of this study was to assess the explanatory power of multispectral, -temporal and -angular MODIS data to estimate tree cover at the regional scale in northernmost Finland. The standard MODIS BRDF/Albedo (MOD43B) data products at approximately 1 km resolution were used. The tree cover was estimated using generalized linear models (GLM), which were calibrated and evaluated by high resolution biotope inventory data. The benefit of coupling the multispectral, -temporal and -angular variables was assessed by variation partitioning. The predicted tree cover fields were also used for the forest–non-forest classification over a larger region and compared with the forest extent of Finnish CORINE land cover 2000 data set. The results show that multitemporal and -angular variables can increase the accuracy of the tree cover estimates and mapping of the forest extent in comparison to the peak of the growing season nadir-view multispectral data. The season of the data acquisition also affect the model performance, the late-spring and early-summer data being superior to mid- and late-summer data. Although the pure effect of the multiangular variables i.e. the parameters of the MODIS BRDF model and selected multiangular indices were relatively small in the models, the inclusion of these data increased the accuracy of the tree cover estimates in the mires in comparison to the peak of the growing season nadir-view multispectral data and multitemporal variables.

Tree cover and height estimation in the Fennoscandian tundra–taiga transition zone using multiangular MISR data

The tundra–taiga transition zone stretches around the northern hemisphere separating boreal forest to the south from treeless tundra to the north. Tree cover and height are important variables to characterize this vegetation transition. Accurate continuous fields of tree cover and height would enable the delineation of the forest extent according to different criterion and provide useful data for change detection of this climatically sensitive ecotone. This study examined if multiangular remote sensing data has potential to improve the accuracy of the tree cover and height estimates in relation to nadir-view data. The satellite data consisted of Multi-angle Imaging SpectroRadiometer (MISR) data at 275 m and 1.1 km resolutions. The study area was located in the Fennoscandian tundra–taiga transition zone, in northernmost Finland. The continuous fields of tree cover and height were estimated using neural networks, which were trained and assessed by high-resolution biotope inventory data. The spectral–angular data together produced lower estimation errors than single band nadir, multispectral nadir or single band multiangular data alone. RMSE of the tree cover estimates reduced from 7.8% (relative RMSE 67.4%) to 6.5% (56.1%) at 275 m resolution, and from 5.4% (49.2%) to 4.1% (36.9%) at 1.1 km resolution, when multispectral nadir data were used together with multiangular data. RMSE of the tree height estimates reduced from 2.3 m (44.3%) to 2.0 m (37.6%) and from 1.8 m (35.4%) to 1.3 m (25.4%), respectively. The largest estimation errors occurred in mires and in areas of dense shrub cover, but the use of multiangular data also reduced estimation errors in these areas. The results suggest that directional information has potential to improve the tree cover and height estimates, and hence the accuracy of the land cover change detection in the tundra–taiga transition zone.