Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km²resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km²pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Miniaturized thermal infrared (TIR) cameras that measure surface temperature are increasingly available for use with unmanned aerial vehicles (UAVs). However, deriving accurate temperature data from these cameras is non-trivialsince they are highly sensitive to changes in their internal temperature and low-cost models are often not radiometrically calibrated. We present the results of laboratory and field experiments that tested the extent of the temperature-dependency of a non-radiometric FLIR Vue Pro 640. We found that a simple empirical line calibration using at least three ground calibration points was sufficient to convert camera digital numbers to temperature values for images captured during UAV flight. Although the camera performed well under stable laboratory conditions (accuracy ±0.5 °C), the accuracy declined to ±5 °C under the changing ambient conditions experienced during UAV flight. The poor performance resulted from the non-linear relationship between camera output and sensor temperature, which was affected by wind and temperature-drift during flight. The camera’s automated non-uniformity correction (NUC) could not sufficiently correct for these effects. Prominent vignetting was also visible in images captured under both stable and changing ambient conditions. The inconsistencies in camera output over time and across the sensor will affect camera applications based on relative temperature differences as well as user-generated radiometric calibration. Based on our findings, we present a set of best practices for UAV TIR camera sampling to minimize the impacts of the temperature dependency of these systems.

The extreme 2018 hot drought that affected central and northern Europe led to the worst wildfire season in Sweden in over a century. The Ljusdal fire complex, the largest area burnt that year (8995 ha), offered a rare opportunity to quantify the combined impacts of wildfire and post‐fire management on Scandinavian boreal forests. We present chamber measurements of soil CO₂ and CH₄ fluxes, soil microclimate and nutrient content from five Pinus sylvestris sites for the first growing season after the fire. We analysed the effects of three factors on forest soils: burn severity, salvage‐logging and stand age. None of these caused significant differences in soil CH₄ uptake. Soil respiration, however, declined significantly after a high‐severity fire (complete tree mortality) but not after a low‐severity fire (no tree mortality), despite substantial losses of the organic layer. Tree root respiration is thus key in determining post‐fire soil CO₂ emissions and may benefit, along with heterotrophic respiration, from the nutrient pulse after a low‐severity fire. Salvage‐logging after a high‐severity fire had no significant effects on soil carbon fluxes, microclimate or nutrient content compared with leaving the dead trees standing, although differences are expected to emerge in the long term. In contrast, the impact of stand age was substantial: a young burnt stand experienced more extreme microclimate, lower soil nutrient supply and significantly lower soil respiration than a mature burnt stand, due to a thinner organic layer and the decade‐long effects of a previous clear‐cut and soil scarification. Disturbance history and burn severity are, therefore, important factors for predicting changes in the boreal forest carbon sink after wildfires. The presented short‐term effects and ongoing monitoring will provide essential information for sustainable management strategies in response to the increasing risk of wildfire.

Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO₂) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO₂ balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO₂ fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R² = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R² = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO₂ fluxes.

An increased frequency of droughts due to anthropogenic climate change can lead to considerable stress for soil microorganisms and their functioning within northern peatlands. A better understanding of the diversity and relative abundance of methane producing and oxidizing taxa, and their functional genes, can help predict the functional potential of peatlands and how the microorganisms respond to disturbances such as drought. To address knowledge gaps in the understanding of how functional genetic diversity shifts under drought conditions, we investigated a hemi boreal mire in Southern Sweden. Environmental parameters, including soil and air temperature, precipitation, and water table depth, as well as methane flux data were collected during the summer of 2017 under typical growing conditions, and in 2018 during a drought. In addition, the diversity and composition of genes encoding for methane metabolism were determined using the captured metagenomics technique. During drought we observed a substantial increase in air and soil temperature, reduced precipitation, and a lower water table depth. Taxonomic and functional gene composition significantly changed during the drought, while diversity indices, such as alpha and beta diversity, remained similar. These results indicate that methane producing and oxidizing microbial communities, and their functional genes, displayed a resilience to drought with specific genera having the ability to outcompete others under stress. Furthermore, our results show that although methane emissions are substantially reduced during drought, we can expect to see a shift toward more resilient methanogens and methanotrophs under future climate conditions.