Permafrost thaw resulting from climate warming is threatening to release carbon from high latitude peatlands. The aim of this research was to determine subsidence rates linked to permafrost thaw in sub-Arctic peatlands in Sweden using historical orthophotographic (orthophotos), Unoccupied Aerial Vehicle (UAV), and Interferometric Synthetic Aperture Radar (InSAR) data. The orthophotos showed that the permafrost palsa on the study sites have been contracting in their areal extent, with the greatest rates of loss between 2002 and 2008. The surface motion estimated from differential digital elevation models from the UAV data showed high levels of subsidence (maxi-mum of −25 cm between 2017 and 2020) around the edges of the raised palsa plateaus. The InSAR data analysis showed that raised palsa areas had the greatest subsidence rates, with maximum subsidence rates of 1.5 cm between 2017 and 2020; however, all wetland vegetation types showed sub-sidence. We suggest that the difference in spatial units associated with each sensor explains parts of the variation in the subsidence levels recorded. We conclude that InSAR was able to identify the areas most at risk of subsidence and that it can be used to investigate subsidence over large spatial extents, whereas UAV data can be used to better understand the dynamics of permafrost degradation at a local level. These findings underpin a monitoring approach for these peatlands.
In arctic ecosystems, climate change has increased plant productivity. As arctic carbon (C) stocks predominantly are located belowground, the effects of greater plant productivity on soil C storage will significantly determine the net sink/source potential of these ecosystems, but vegetation controls on soil CO2 efflux remain poorly resolved.
In order to identify the role of canopy‐forming species in belowground C dynamics, we conducted a girdling experiment with plots distributed across 1 km2 of treeline birch (Betula pubescens ) forest and willow (Salix lapponum ) patches in northern Sweden and quantified the contribution of canopy vegetation to soil CO2 fluxes and belowground productivity.
Girdling birches reduced total soil CO2 efflux in the peak growing season by 53%, which is double the expected amount, given that trees contribute only half of the total leaf area in the forest. Root and mycorrhizal mycelial production also decreased substantially. At peak season, willow shrubs contributed 38% to soil CO2 efflux in their patches.
Our findings indicate that C, recently fixed by trees and tall shrubs, makes a substantial contribution to soil respiration. It is critically important that these processes are taken into consideration in the context of a greening arctic because productivity and ecosystem C sequestration are not synonymous.
In the face of climate change, it is important to estimate changes in key ecosystem properties such as plant biomass and gross primary productivity (GPP). Ground truth estimates and especially experiments are performed at small spatial scales (0.01-1 m(2)) and scaled up using coarse scale satellite remote sensing products. This will lead to a scaling bias for non-linearly related properties in heterogeneous environments when the relationships are not developed at the same spatial scale as the remote sensing products. We show that unmanned aerial vehicles (UAVs) can reliably measure normalized difference vegetation index (NDVI) at centimeter resolution even in highly heterogeneous Arctic tundra terrain. This reveals that this scaling bias increases most at very fine resolution, but UAVs can overcome this by generating remote sensing products at the same scales as ecological changes occur. Using ground truth data generated at 0.0625 m(2)and 1 m(2)with Landsat 30 m scale satellite imagery the resulting underestimation is large (8.9%-17.0% for biomass and 5.0%-9.7% for GPP(600)) and of a magnitude comparable to the expected effects of decades of climate change. Methods to correct this upscaling bias exist but rely on sub-pixel information. Our data shows that this scale-dependency will vary strongly between areas and across seasons, making it hard to derive generalized functions compensating for it. This is particularly relevant to Arctic greening with a predominantly heterogeneous land cover, strong seasonality and much experimental research at sub-meter scale, but also applies to other heterogeneous landscapes. These results demonstrate the value of UAVs for satellite validation. UAVs can bridge between plot scale used in ecological field investigations and coarse scale in satellite monitoring relevant for Earth System Models. Since future climate changes are expected to alter landscape heterogeneity, seasonally updated UAV imagery will be an essential tool to correctly predict landscape-scale changes in ecosystem properties.
Understanding how herbivores shape plant biomass and distribution is a core challenge in ecology. Yet, the lack of suitable remote sensing technology limits our knowledge of temporal and spatial impacts of mammal herbivores in the Earth system. The regular interannual density fluctuations of voles and lemmings are exceptional with their large reduction of plant biomass in Arctic landscapes during peak years (12–24%) as previously shown at large spatial scales using satellites. This provides evidence that herbivores are important drivers of observed global changes in vegetation productivity. Here, we use a novel approach with repeated unmanned aerial vehicle (UAV) flights, to map vegetation impact by rodents, indicating that many important aspects of vegetation dynamics otherwise hidden by the coarse resolution of satellite images, including plant–herbivore interactions, can be revealed using UAVs. We quantify areas impacted by rodents at four complex Arctic landscapes with very high spatial resolution UAV imagery to get a new perspective on how herbivores shape Arctic ecosystems. The area impacted by voles and lemmings is indeed substantial, larger at higher altitude tundra environments, varies between habitats depending on local snow cover and plant community composition, and is heterogeneous even within habitats at submeter scales. Coupling this with spectral reflectance of vegetation (NDVI), we can show that the impact on central ecosystem properties like GPP and biomass is stronger than currently accounted for in Arctic ecosystems. As an emerging technology, UAVs will allow us to better disentangle important information on how herbivores maintain spatial heterogeneity, function and diversity in natural ecosystems.