Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra - coupling field observations with remote sensing data.

Arctic tundra ecosystems will have a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) - bare soil, lichen tundra, shrub tundra, flood meadow, graminoid tundra, bog, dry fen, wet den and water - to classify the variation in our site. To characterize the LCTs, we sampled 92 study plots for plant (biomass and leaf area index, LAI) and soil (organic matter OM%, bulk density, moisture, pH, litter layer depth, litter mass loss, temperature and active layer depth) attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images (QuickBird and WorldView-2, portraying vegetation at 180, 220 and 750 growing degree days, DD with 0 °C threshold) and a digital elevation model (derived from a WV-2 stereo-pair image). We found that soils in our site ranged from mineral soils in bare soil and lichen tundra (on average 3.9 % OM) to soils of high OM% in graminoid tundra, bog, dry fen and wet fen (38 %), with shrub tundra and flood meadow being intermediate (21 %). Soil OM content was on average 14 g dm^-3 in bare soil and lichen tundra and 89 g dm^-3 in other LCTs. Total moss biomass varied from 0 to 820 g m^-2 among LCTs and high moss mass was associated with high soil OM%, except that wet fens with high OM% sustained low moss mass. Total vascular shoot mass was 7 g m^-2 in bare soil, on average 53 g m^-2 in lichen tundra and dry fen and 91 g m^-2 in other LCTs. Vascular LAI was on average 0.12 in bare soil and lichen tundra, 0.50 in bog, dry fen, shrub tundra and graminoid tundra, and 0.90 in flood meadow and wet fen. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, 9 °C in flood meadow and wet fen and 6 °C in other LCTs. Depth of the active soil layer doubled from early July to middle August, when it reached on average 42 cm in flood meadow and wet fen, 35 cm in bog, dry fen and graminoid tundra and 26 cm in bare soil and lichen and shrub tundra. When contrasted across study plots, total moss biomass was positively associated with soil OM% and OM content and negatively with soil temperature, explaining 14-34 % of variation in soil attributes. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but the amount of variation explained was significantly lower (6-15 %). NDVI captured variation in peak season vascular LAI better than variation in moss biomass, but the difference depended on the phase of the growing season in the image: 180-DD, 220-DD and 750-DD NDVI captured 23, 17 and 7 % of moss mass variation and 25, 34 and 50 % of vascular LAI variation, respectively. For this reason, soil attributes associated with moss mass were better captured by early season NDVI and those associated with LAI by late season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and they could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM% and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance or topography. This suggests that using simple reflectance indices and DEM for spatial extrapolation of those vegetation and soil attributes that are relevant for regional ecosystem and global climate models warrants further inspection. Meanwhile, land cover maps of LCTs and their attributes, derived from remote sensing data and effective field sampling in different LCTs, seem to provide the most reliable way to extrapolate vegetation and soil properties within Arctic tundra landscapes. [ABSTRACT FROM AUTHOR]