Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

Arctic tundra ecosystems will play 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)
and to characterize them, sampled 92 study plots for plant and soil
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. We found that soils ranged from mineral soils in bare
soil and lichen tundra LCTs to soils of high percentage of organic matter
(OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top
soil 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, total
vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI)
from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm
depth were on average 25 ◦C in bare soil and lichen tundra, and varied
from 5 to 9 ◦C in other LCTs. On average, depth of the biologically
active, unfrozen soil layer doubled from early July to mid-August. When
contrasted across study plots, moss biomass was positively associated with
soil OM % and OM content and negatively associated with soil temperature,
explaining 14–34 % of variation. Vascular shoot mass and LAI were also
positively associated with soil OM content, and LAI with active layer
depth, but only explained 6–15 % of variation. NDVI captured variation in
vascular LAI better than in moss biomass, but while this difference was
significant with late season NDVI, it was minimal with early season NDVI.
For this reason, soil attributes associated with moss mass were better
captured by early season NDVI. Topographic attributes were related to LAI
and many soil attributes, but not to moss biomass and could not increase
the amount of spatial variation explained in plant and soil attributes
above that achieved by NDVI. The LCT map we produced had low to moderate
uncertainty in predictions for plant and soil properties except for moss
biomass and bare soil and lichen tundra LCTs. 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, topography or
a LCT map. Despite the general accuracy of landscape level predictions in
our LCT approach, this indicates challenges in the spatial extrapolation
of some of those vegetation and soil attributes that are relevant for the
regional ecosystem and global climate models.