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 thus fail to reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions are controlled and most terrestrial species reside. Here we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0-5 and 5-15 cm 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-km² pixels (summarized from 8500 unique temperature sensors) across all of 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 2 m 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 warmer than gridded air temperature), whereas soils in warm and humid environments are on average slightly cooler (0.7 ± 2.3°C cooler). The observed substantial and biome-specific offsets underpin that the projected impacts of climate and climate change on 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 global gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

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Research in environmental science relies heavily on global climatic grids derived from estimates of air temperature at around 2 meter above ground1-3. These climatic grids however fail to reflect conditions near and below the soil surface, where critical ecosystem functions such as soil carbon storage are controlled and most biodiversity resides4-8. By using soil temperature time series from over 8500 locations across all of the world’s terrestrial biomes4, we derived global maps of soil temperature-related variables at 1 km resolution for the 0–5 and 5–15 cm depth horizons. Based on these maps, we show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C, with substantial variation across biomes and seasons. Soils in cold and/or dry biomes are annually substantially warmer (3.6°C ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are slightly cooler (0.7 ± 2.3°C). As a result, annual soil temperature varies less (by 17%) across the globe than air temperature. The effect of macroclimatic conditions on the difference between soil and air temperature highlights the importance of considering that macroclimate warming may not result in the same level of soil temperature warming. Similarly, changes in precipitation could alter the relationship between soil and air temperature, with implications for soil-atmosphere feedbacks9. Our results underpin that the impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments.

Abstract. Soil organic matter is a vast store of carbon, with a critical role in the global carbon cycle. Despite its importance, the dynamics of soil organic carbon decomposition, under the impact of climate change or changing litter inputs, are poorly understood. Current biogeochemical models usually lack microbial processes and thus miss an important feedback when considering the fate of carbon. Here we use a series of modelling experiments to evaluate two different model structures: one with a standard first-order kinetic representation of soil decomposition (DecoChem v1.0, hereafter chemical model) and one with control of soil decomposition through microbial activity (DecoBio v1.0, hereafter biological model). The biological model includes cycling of organic matter into and out of microbial biomass, and simulates the decay rate as a functional of microbial activity. We tested two hypotheses. First, we hypothesized different responses in the two models to increased litter inputs and glucose additions. In the microbial model we hypothesized that this perturbation would prime microbial activity and reduce soil carbon stocks; in the chemical model we expected this perturbation to increase C stocks. In the biological model, responses to changed litter quantity were more rapid, but with the residence time of soil C altering such that soil C stocks were buffered. However, in the biological model there was a strong response to increased glucose additions (i.e. changes in litter quality), with significant losses to soil C stocks over time, driven by priming. Secondly, we hypothesized that warming will stimulate decomposition in the chemical model and loss of C, but in the biological model soil C will be less sensitive to warming, due to complex microbial feedbacks. The numerical experiments supported this hypothesis, with the chemical model soil C residence times and steady-state C stocks adjusting strongly with temperature changes, extending over decades. On the other hand, the biological model showed a rapid response to temperature that subsided after a few years, with total soil C stocks largely unchanged. The microbial model shows qualitative agreement with experimental warming studies that found transient increases in soil respiration that decline within a few years. In conclusion, the biological model is largely buffered against bulk changes in litter inputs and climate, unlike the chemical model, while the biological model displays a strong priming response to additions of labile litter. Our results have therefore highlighted significantly different sensitivities between chemical and biological modelling approaches for soil decomposition.

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