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Species at their warm range margin are potentially threatened by higher temperatures, but may persist in microrefugia. Whether such microsites occur due to more suitable microclimate or due to lower biotic pressure from, for example competitive species, is still not fully resolved. We examined whether boreal bryophytes and lichens show signs of direct climate limitation, that is whether they perform better in cold and/or humid microclimates at their warm range margin. We transplanted a moss, a liverwort and a lichen to 58 boreal forest sites with different microclimates at the species' southern range margin in central Sweden. Species were grown in garden soil patches to control the effects of competitive exclusion and soil quality. We followed the transplanted species over three growing seasons (2016–2018) and modelled growth and vitality for each species as a function of subcanopy temperature, soil moisture, air humidity and forest type. In 2018, we also recorded the cover of other plants having recolonized the garden soil patches and modelled this potential future competition with the same environmental variables plus litter. Species performance increased with warmer temperatures, which was often conditional on high soil moisture, and at sites with more conifers. Soil moisture had a positive effect, especially on the moss in the last year 2018, when the growing season was exceptionally hot and dry. The lichen was mostly affected by gastropod grazing. Recolonization of other plants was also faster at warmer and moister sites. The results indicate that competition, herbivory, shading leaf litter and water scarcity might be more important than the direct effects of temperature for performance at the species' warm range margin. Synthesis. In a transplant experiment with three boreal understorey species, we did not find signs of direct temperature limitation towards the south. Forest microrefugia, that is habitats where these species could persist regional warming, may instead be sites with fewer competitors and enemies, and with sufficient moisture and more conifers in the overstorey. Royal Swedish Academy of Sciences 2014-00530

The CCI Soil Moisture dataset (CCI SM, Dorigo et al., 2017) is the most extensive climate data record (CDR) of satellite soil moisture to date and is based on observations from multiple active and passive microwave satellite sensors. It provides coverage all the way back to 1978 and is updated yearly both in terms of algorithm and temporal coverage. In order to maximize its function as a CDR, both long term consistency and (model-)independence are high priorities in its development. Two important satellite missions integrated into the CCI SM are the ESA Soil Moisture and Ocean Salinity mission (SMOS, Kerr et al., 2010) and the NASA Soil Moisture Active Passive mission (SMAP, Entekhabi et al., 2010). These missions distinguish themselves with their unique L-band (1.4 GHz) radiometers, which are theoretically more suitable for soil moisture retrieval than the prior available higher frequencies like C- X- and Ku-band (6.9 to 18.0 GHz). However, these L-band missions are lacking onboard sensors for observations from higher frequencies Ku-, K- and Ka-band, which are normally used within the Land Parameter Retrieval Model (Owe et al., 2008), the baseline algorithm for passive microwave retrievals within the CCI SM, for retrieving the effective temperature (Holmes et al., 2009) and providing filters for snow/frozen conditions (Van der Vliet et al., 2020). Therefore, the retrievals from the current L-band missions make use of temperature and filters derived from global Land Surface Models (LSM, Van der Schalie et al., 2016). For a CDR that should function as an independent climate benchmark, this is a strong disadvantage.Within this study the aim is to evaluate the impact of replacing the LSM based input for L-band soil moisture retrievals with one that comes from passive microwave observations. We use an inter-calibrated dataset existing of 6 different sensors that cover the complete SMOS and SMAP historical record (and further), consisting of AMSR2, AMSR-E, TRMM, GPM, Fengyun-3B and Fengyun-3D. These satellites are merged together using a minimization function that also penalizes errors in the Microwave Polarization Difference Index (MPDI) for a higher level of stability compared to using traditional linear regressions.As currently the 6 am L-band retrievals are seen as the most reliable, and are currently the only ones used within the CCI, the main focus will be on the effects of using the 1:30 am observations from the inter-calibrated dataset as input. However, to make the method also applicable for daytime observations, the 6 pm retrievals have also been tested using an average of 1:30 pm and 1:30 am (next day) observations. This evaluation will provide an overview of the differences, giving insight on how this affects coverage, mean values, standard deviations and their inter-correlation. Secondly, we will test the resulting quality against both in situ observations and ERA5. A similar performance of this new dataset shows this is a good way to standardize input on temperature and filtering within the CCI SM, further improving its consistency and function as a model-independent CDR.

Exploration practices for oil sands developments in the boreal forest of western Canada create a network of thousands of kilometers of linear features, particularly seismic lines that dissect these forests posing significant environmental challenges. As wildfire is one of the prevalent stand‐replacing natural disturbances in the Canadian boreal forest, it is an important driver of environmental change and stand development that may contribute to the mitigation of such linear industrial footprint. Here, we evaluate the short‐term cumulative (also known as combined) effects of seismic lines and wildfire on biodiversity and site conditions. One year after the Horse River (Fort McMurray, Alberta, Canada) fire event in the spring of 2016, we compared dissected and undisturbed forests in burned and unburned boreal peatlands, assessing changes in overall stand structure and the responses of a variety of organisms. Soil moisture was significantly higher on seismic lines than in the adjacent forest, suggesting why most of the study sites within the fire perimeter showed little evidence of burning at the line in relation to the adjacent forest. Low fire severity on seismic lines seemed an important driver of local species diversity for ants, beetles, spiders, and plants in disturbed peatlands, resulting in similar species composition on seismic lines both within and outside the burned area, but different assemblages in burned and unburned adjacent forests. Our results suggest that fire did not erase seismic lines; rather, wildfire might increase the influence of this footprint on the recovering adjacent forest. Longer‐term monitoring will be necessary to understand how boreal treed peatlands respond to the cumulative effect of wildfire and linear disturbances.

Boreal wildfires are increasing in intensity, extent, and frequency, potentially intensifying carbon emissions and transitioning the region from a globally significant carbon sink to a source. The productive southern boreal forests of central Canada already experience relatively high frequencies of fire, and as such may serve as an analog of future carbon dynamics for more northern forests. Fire–carbon dynamics in southern boreal systems are relatively understudied, with limited investigation into the drivers of pre-fire carbon stocks or subsequent combustion. As part of NASA's Arctic-Boreal Vulnerability Experiment, we sampled 79 stands (47 burned, 32 unburned) throughout central Saskatchewan to characterize above- and belowground carbon stocks and combustion rates in relation to historical land use, vegetation characteristics, and geophysical attributes. We found southern boreal forests emitted an average of 3.3 ± 1.1 kg C/m2 from field sites. The emissions from southern boreal stands varied as a function of stand age, fire weather conditions, ecozone, and soil moisture class. Sites affected by historical timber harvesting had greater combustion rates due to faster carbon stock recovery rates than sites recovering from wildfire events, indicating that different boreal forest land use practices can generate divergent carbon legacy effects. We estimate the 2015 fire season in Saskatchewan emitted a total of 36.3 ± 15.0 Tg C, emphasizing the importance of southern boreal fires for regional carbon budgets. Using the southern boreal as an analog, the northern boreal may undergo fundamental shifts in forest structure and carbon dynamics, becoming dominated by stands 2 less than current mature northern boreal stands. Our latitudinal approach reinforces previous studies showing that northern boreal stands are at a high risk of holding less carbon under changing disturbance conditions.

For this study, we characterized the dependence of fire counts (FCs) on soil moisture (SM) at global and sub-global scales using 15 years of remote sensing data. We argue that this mathematical relationship serves as an effective way to predict fire because it is a proxy for the semi-quantitative fire&ndash, productivity relationship that describes the tradeoff between fuel availability and climate as constraints on fire activity. We partitioned the globe into land-use and land-cover (LULC) categories of forest, grass, cropland, and pasture to investigate how the fire&ndash, soil moisture (fire&ndash, SM) behavior varies as a function of LULC. We also partitioned the globe into four broadly defined biomes (Boreal, Grassland-Savanna, Temperate, and Tropical) to study the dependence of fire&ndash, SM behavior on LULC across those biomes. The forest and grass LULC fire&ndash, SM curves are qualitatively similar to the fire&ndash, productivity relationship with a peak in fire activity at intermediate SM, a steep decline in fire activity at low SM (productivity constraint), and gradual decline as SM increases (climate constraint), but our analysis highlights how forests and grasses differ across biomes as well. Pasture and cropland LULC are a distinctly human use of the landscape, and fires detected on those LULC types include intentional fires. Cropland fire&ndash, SM curves are similar to those for grass LULC, but pasture fires are evident at higher SM values than other LULC. This suggests a departure from the expected climate constraint when burning is happening at non-optimal flammability conditions. Using over a decade of remote sensing data, our results show that quantifying fires relative to a single physical climate variable (soil moisture) is possible on both cultivated and uncultivated landscapes. Linking fire to observable soil moisture conditions for different land-cover types has important applications in fire management and fire modeling.

Understanding the hydrological dynamics of boreal wetland ecosystems (peatlands) is essential in order to better manage hydropower inter-annual productivity at the La Grande basin (Northern Quebec, QC, Canada). Given the remoteness and the huge dimension of the La Grande basin, it is imperative to develop remote sensing monitoring techniques to retrieve hydrological parameters. The main objective of this study is to find out if multi-date and multi-polarization Radar Satellite 2 (RADARSAT-2) (C-band) image analysis could detect seasonal variations of surface soil moisture conditions of the acrotelm. A change detection approach through the use of multi temporal indexes was chosen based on the assumption that the temporal variability of surface roughness and natural vegetation biomass is generally at a much longer time scale than that of surface soil moisture (Δ-Index is based on a reference image that represents dry soil, in order to maximize the sensitivity of σ° to changes in soil moisture with respect to the same location when soil is wet). The Δ-Index approach was tested with each polarization: σ° for fully polarimetric mode (HH, HV, VV) and the cross-polarization coefficient (HV/HH). Results show that the best regression adjustment with regard to surface soil moisture content in boreal wetlands was obtained with the cross-polarization coefficient. The cross-polarization multi-temporal index enables precise volumetric surface soil moisture estimation and monitoring on boreal wetlands, regardless of the influence of vegetation cover and surface roughness conditions (bias was under 1%, standard deviation and RMSE were under 10% for almost all estimation errors). Surface soil moisture estimation was more precise over permanently flooded areas than seasonally flooded ones (standard deviation is systematically greater for the seasonally flooded areas, at all analyzed scales), although the overall quality of the estimation is still precise. Cross-polarization ratio image analysis appears to be a useful mean to exploit radar data spatially, as we were able to relate changes in wetland eco-hydrological dynamics to variations in the intensity of the ratio.

Recent warming has stimulated the productivity of boreal and Arctic vegetation by reducing temperature limitations. However, several studies have hypothesized that warming may have also increased moisture limitations because of intensified summer drought severity. Establishing the connections between warming and drought stress has been difficult because soil moisture observations are scarce. Here we use recently developed gridded datasets of moisture variability to investigate the links between warming and changes in available soil moisture and summer vegetation photosynthetic activity at northern latitudes (greater than 45N) based on the Normalized Difference Vegetation Index (NDVI) since 1982. Moisture and temperature exert a significant influence on the inter-annual variability of summer NDVI over about 29% (mean r(sup 2) = 0.29 +/ 0.16) and 43% (mean r(sup 2 = 0.25 +/- 0.12) of the northern vegetated land, respectively. Rapid summer warming since the late 1980s (approximately 0.7deg C) has increased evapotranspiration demand and consequently summer drought severity, but contrary to earlier suggestions it has not changed the dominant climate controls of NDVI over time. Furthermore, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and NDVI in moisture-sensitive regions of the boreal forest. In boreal North America, forest NDVI declines are more consistent with reduced snowpack rather than with temperature-induced increases in evaporative demand as suggested in earlier studies. Moreover, summer NDVI variability over about 28% of the northern vegetated land is not significantly associated with moisture or temperature variability, yet most of this land shows increasing NDVI trends. These results suggest that changes in snow accumulation and melt, together with other possibly non-climatic factors are likely to play a significant role in modulating regional ecosystem responses to the projected warming and increase in evapotranspiration demand during the coming decades.

The National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis models are compared with First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) grassland data from Kansas in 1987 and Boreal Ecosystem-Atmosphere Study (BOREAS) data from an old black spruce site in 1996 near Thompson, Manitoba. Some aspects of the comparison are similar for the two ecosystems. Over grassland and after snowmelt in the boreal forest, both models represent the seasonal cycle of near-surface temperature well. The two models have quite different soil hydrology components. The ECMWF model includes soil water nudging based on low level humidity errors. While this works quite well for the FIFE grassland, it appears to give too high evaporation over the boreal forest. The NCEP/NCAR model constrains long-term drifts by nudging deep soil water toward climatology. Over the FIFE site, this seems to give too low evaporation in midsummer, while at the BOREAS site, evaporation in this model is high. Both models have some difficulty representing the surface diurnal cycle of humidity. In the NCEP/NCAR reanalysis this leads to errors primarily in June, when the surface boundary layer stays saturated and too much precipitation occurs. In the ECMWF reanalysis there is a morning peak of mixing ratio, which an earlier work showed resulted from too shallow a boundary layer in the morning. Over the northern boreal forest there are important physical processes, which are not represented in either reanalysis model. In particular very high model albedos in spring, when there is snow under the forest canopy, lead to a very low daytime net radiation. This in turn leads to a large underestimate of the daytime surface fluxes, particularly the sensible heat flux, and to daytime model surface temperatures that are as much as 15 K low. In addition, the models do not account for the reduction in evaporation associated with frozen soil, and they generally have too large evapotranspiration in June and July, probably because they do not model the tight stomatal control of the coniferous forest.