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.

Remote sensing-based evapotranspiration (ET) models with various levels of sophistication have emerged recently with the possibilities of user-defined model calibrations. Their application for water resources management and climate studies from regional to global scale has been rapidly increasing, which makes it important to validate field scale ET in a complex crop assemblage before operational use. Based on in situ flux-tower measurements by the eddy-covariance (EC) system, this study tested three single-source energy balance models for estimating daily ET from fennel/maize/ryegrass-clover cropland rotations in a Mediterranean context in southern Italy. The sensitivity of three user-friendly ET models (SEBS, QWaterModel, and METRIC-EEFlux) with reference to the EC system over a center pivot irrigated cropland is discussed in detail. Results in terms of statistical indicators revealed that SEBS and METRIC-EEFlux showed reasonable agreements with measured ET (r² = 0.59_SEBS, RMSE = 0.71 mm day⁻¹; r² = 0.65_METRIC, RMSE = 1.13 mm day⁻¹) in terms of trends and magnitudes. At 30 m spatial resolution, both models were able to capture the in-field variations only during the maize development stage. The presence of spurious scan lines due to sensor defects in Landsat L7 ETM+ can contribute to the qualities of the METRIC-Efflux’s ET product. In our observation, the QWaterModel did not perform well and showed the weakest congruency (r² = 0.08_QWaterModel) with ground-based ET estimates. In a nutshell, the study evaluated these automated remote sensing-based ET estimations and suggested improvements in the context of a generic approach used in their underlying algorithm for robust ET retrievals in rotational cropland ecosystems.

Modeling approaches have emerged to address uncertainties arising from N₂O emissions variability, representing a powerful methodology to investigate the two emitting processes (i.e., nitrification and denitrification) and to represent the interconnected dynamics among soil, atmosphere, and crops. This work offers an extensive overview of the widely used models simulating N₂O under different cropping systems and management practices. We selected process-based models, prioritizing those with well-documented algorithms found in recently published scientific articles or having published source codes. We reviewed and compared the algorithms employed to simulate N₂O emissions, adopting a unified symbol system. The selected models (APSIM, ARMOSA, CERES-EGC, CROPSYST, CoupModel, DAYCENT, DNDC, DSSAT, EPIC, SPACSYS, and STICS) were categorized by the approaches used to model nitrification and denitrification processes, discriminating between implicit or explicit consideration of the microbial pool and according to the formalization of the main environmental drivers of these processes (soil nitrogen concentration, temperature, moisture, and acidity). Models’ setting and performance assessments were also discussed. From the appraisal of these approaches, it emerged that soil chemical–physical properties and weather conditions are the main drivers of N cycling and the consequent gaseous emissions.

Biogenic volatile organic compounds (BVOCs) might affect air quality and regional climate and their emissions strongly depend from plants. BVOCs exchanges are related to plant species and environmental factors, as temperature, radiation and water availability. Since Sorghum bicolor L. is becoming an increasingly valid alternative to maize in Southern Europe as well as in any non-irrigated region with limited precipitation, is important understand its potential BVOCs exchanges pattern. Up to now, only few studies have focused on BVOCs exchanges at ecosystem scale over an entire growing season, and no one investigated sorghum or other crops in the Mediterranean area. For the first time in this paper, BVOCs fluxes in a sorghum field at ecosystem scale over a whole growing season in Southern Italy are presented. Using online PTR-TOF BVOCs detection and eddy covariance technique, we continuously followed BVOCs exchanges for about 3 months. Methanol was the main emitted compound with a total average emission of 0.1 nmol m-2 s-1, followed by acetaldehyde, with a total average emission of 0.04 nmol m-2 s-1. Their fluxes were correlated with developing and cutting, following the plant growth and the escaping routes from intracellular storage. Other oxygenated compounds (OVOCs) like formaldehyde acetone, acetic acid, formic acid, MVK/MAC, were also exchanged. Monoterpenes were mainly taken up, with a total average uptake of -0.015 nmol m-2 s-1. Net emissions of green leaves volatiles (GLVs) during the stages where lodging and cutting occurred, are related to mechanical stress. These results show variable dynamics for the investigated BVOCs. The exchanges match with those observed on other croplands (mainly maize) for some compounds, meanwhile for other compounds they seem to be different, revealing a variability related to species and world region. Finally, is to be considered that not only weather and seasonality determine BVOCs exchanges patterns, but also phenology, crop management and stress. Therefore, BVOCs can be used to predict changes in phenology or the onset of stress, helping to determine the health state of crops in a climate changes scenarios.

To assess the land atmosphere exchanges linked to agricultural management activities, we conducted two field campaigns over the ICOS-candidate ecosystem site of Borgo Cioffi, a rotation cropland in Southern Italy, measuring fluxes of CH 4 and CO 2 as well as N 2 O, obtaining the temporal evolution of the exchange dynamics for the prevailing GHG. The interested crops were Lolium italicum and Sorghum bicolor, two fodder crops very common in the region. The results showed that the tilled field acted as a source for all GHGs in both cases.