• Energy Research
• European Marine Science close

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

AbstractEnvironmental manipulation studies are integral to determining biological consequences of climate warming. Open Top Chambers (OTCs) have been widely used to assess summer warming effects on terrestrial biota, with their effects during other seasons normally being given less attention even though chambers are often deployed year‐round. In addition, their effects on temperature extremes and freeze‐thaw events are poorly documented. To provide robust documentation of the microclimatic influences of OTCs throughout the year, we analysed temperature data from 20 studies distributed across polar and alpine regions. The effects of OTCs on mean temperature showed a large range (−0.9 to 2.1 °C) throughout the year, but did not differ significantly between studies. Increases in mean monthly and diurnal temperature were strongly related (R2 = 0.70) with irradiance, indicating that PAR can be used to predict the mean warming effect of OTCs. Deeper snow trapped in OTCs also induced higher temperatures at soil/vegetation level. OTC‐induced changes in the frequency of freeze‐thaw events included an increase in autumn and decreases in spring and summer. Frequency of high‐temperature events in OTCs increased in spring, summer and autumn compared with non‐manipulated control plots. Frequency of low‐temperature events was reduced by deeper snow accumulation and higher mean temperatures. The strong interactions identified between aspects of ambient environmental conditions and effects of OTCs suggest that a detailed knowledge of snow depth, temperature and irradiance levels enables us to predict how OTCs will modify the microclimate at a particular site and season. Such predictive power allows a better mechanistic understanding of observed biotic response to experimental warming studies and for more informed design of future experiments. However, a need remains to quantify OTC effects on water availability and wind speed (affecting, for example, drying rates and water stress) in combination with microclimate measurements at organism level.

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.