• Energy Research

AbstractResearch 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.

AbstractMicrobial activity is highly dependent on climatic factors (moisture and temperature) and edaphic characteristics in temperate ecosystems. Moreover, soil microbial community composition in high mountain areas is less known when compared to plant communities. In this study we investigated the soil microbial community from a functional perspective using PLFA (phospholipid fatty acid) methods in the four aspects of four summits (2,242 – 3,012 m above sea level) in the Spanish Central Pyrenees. Soil organic carbon (C), microbial biomass and nutrient dynamics ($$N{H}_{4}^{+}$$NH4+ + $$N{O}_{3}^{-}$$NO3−, N mineralization and nitrification potential) were also determined. Microbial biomass C was highest in the lowermost summit and decreased by approximately 50, 14 and 12% with increasing altitude. In each summit soil$$N{H}_{4}^{+}$$NH4+and$$N{O}_{3}^{-}$$NO3−concentrations differed significantly among summits and aspects. Soil nitrification potential varied significantly between the factors summit and aspects, e.g., southerly vs. northerly, easterly vs. westerly aspects. Gram negative bacteria and Actinobacteria functional groups dominated the microbial community, with almost 40% of the total PLFA. Non-metric multidimensional scale (NMS) analysis showed that most of the PLFA functional groups were present in all summits and aspects, although with specific biomarkers. A high abundance of biomarkers 16:1ω9c and 16:0 2OH (gram negative bacteria) were obtained in the lowermost summit, while the biomarkers 16.1ω7cDMA (anaerobes) and 19:3ω6c (Eukaryote) were only found in the uppermost summit. Linear mixed model (lmm) analysis was used with summit as fixed effect and aspect as random effect. In general, our results demonstrate a fundamental role for environment, principally moisture, temperature and organic matter in explaining the pattern observed for soil PLFA biomarkers. Under a global change scenario, we need to shed light on the relationships between soil microbial functional groups and soil nutrient-related variables in order to identify the associated patterns of decomposition rates and soil processes driven by microbial communities in mountain areas. The results could thus be used in global predictive models on climate change impact on C or N cycles in these environments.

AbstractCurrent analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long‐term average thermal conditions at coarse spatial resolutions only. Hence, many climate‐forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold‐air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free‐air temperatures, microclimatic ground and near‐surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near‐surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.