DOI: 10.5061/dryad.8382j4r
title: Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

description: 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.
description: Plant, soil and remote
 sensing attributes of a Siberian Arctic sitePlant and soil data of
 study plots were collected in the field in summer 2014. NDVI and
 topographical attributes were later extracted from three satellite images,
 portraying the field site and vegetation in three different years at 180,
 220 and 750 DD (growing degree days with 0 C threshold). Plant species
 presence (1 in data) and absence (0 in data) in study plots is available
 for dicotyledonous vascular plants. Land cover types are based on
 ground-based visual judgement.Mikola et al.
 2018_Biogeosciences.xlsx