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The carbon sequestration of plants through photosynthesis is responsible for removal of a substantial amount of the man-made CO 2 emissions to the atmosphere. In recent years this so-called land-sink has removed about 30% of the man-made emissions to the atmosphere, with forests being the most important sinks. The land-sink is, however, vulnerable to changes in the environment, such as the atmospheric composition, climate change, and extreme events like storms and droughts. It is therefore important to study the effects of such change on terrestrial ecosystems to provide the basis for predicting the future of the sink. We here report the results of continuous CO 2 flux measurements over a Danish beech forest during the years 1996-2019. Over the years the forest acted as a sink of CO 2 with a net carbon sequestration ranging from about zero to 400 g C m -2 yr −1. We found significant trends in net ecosystem exchange (NEE) (increasing in absolute terms with 15 g C m -2 yr 2 ), gross ecosystem exchange (GEE) (increasing with 25 g C m -2 yr -2 ), and ecosystem respiration (RE) (increasing with 10 g C m -2 yr -2 ). A prolonged growing season explained 73% of the increase in NEE. The increasing CO 2 concentration in the atmosphere and a subsequent increase in photosynthetic capacity together with warming are the most likely main causes of the increased carbon uptake. The severe drought in the summer of 2018 resulted in a reduction of the annual NEE of 25%.

Attempts to combine biometric and eddy-covariance (EC) quantifications of carbon allocation to different storage pools in forests have been inconsistent and variably successful in the past. We assessed above-ground biomass changes at five long-term EC forest stations based on tree-ring width and wood density measurements, together with multiple allometric models. Measurements were validated with site-specific biomass estimates and compared with the sum of monthly CO2 fluxes between 1997 and 2009. Biometric measurements and seasonal net ecosystem productivity (NEP) proved largely compatible and suggested that carbon sequestered between January and July is mainly used for volume increase, whereas that taken up between August and September supports a combination of cell wall thickening and storage. The inter-annual variability in above-ground woody carbon uptake was significantly linked with wood production at the sites, ranging between 110 and 370 g Cm−2 yr−1, thereby accounting for 10–25% of gross primary productivity (GPP), 15–32% of terrestrial ecosystem respiration (TER) and 25–80% of NEP. The observed seasonal partitioning of carbon used to support different wood formation processes refines our knowledge on the dynamics and magnitude of carbon allocation in forests across the major European climatic zones. It may thus contribute, for example, to improved vegetation model parameterization and provides an enhanced framework to link tree-ring parameters with EC measurements.

Soil respiration (Rs) is an important component of ecosystem carbon balance, and accurate quantification of the diurnal and seasonal variation ofRs is crucial for a correct interpretation of the response of Rs to biotic and abiotic factors, as well as for estimating annual soil CO2 efflux rates.In this study, we measured Rs hourly for 1 year by automated closed chambers in a temperate Danish beech forest. The data showed a clear diurnal pattern of Rs across all seasons with higher rates during night-time than during daytime. However, further analysis showed a clear negative relationship between flux rates and friction velocity (u∗) above the canopy, suggesting that Rs was overestimated at low atmospheric turbulence throughout the year due to non-steady-state conditions during measurements. Filtering out data at low u∗ values removed or even inverted the observed diurnal pattern, such that the highest effluxes were now observed during daytime, and also led to a substantial decrease in the estimated annual soil CO2 efflux.By installing fans to produce continuous turbulent mixing of air around the soil chambers, we tested the hypothesis that overestimation of soil CO2 effluxes during low u∗ can be eliminated if proper mixing of air is ensured, and indeed the use of fans removed the overestimation ofRs rates during low u∗. Artificial turbulent air mixing may thus provide a method to overcome the problems of using closed-chamber gas-exchange measurement techniques during naturally occurring low atmospheric turbulence conditions. Other possible effects from using fans during soil CO2 efflux measurements are discussed. In conclusion, periods with low atmospheric turbulence may provide a significant source of error in Rs rates estimated by the use of closed-chamber techniques and erroneous data must be filtered out to obtain unbiased diurnal patterns, accurate relationships to biotic and abiotic factors, and before estimating Rs fluxes over longer timescales.

A controlled peatland rewetting experiment was conducted on two adjacent drained peatland sites in southeastern Norway. Eddy covariance monitoring of CO 2 and CH 4 fluxes at both sites began in 2019. In 2021, the Treatment Site was rewetted while the Control Site remained drained. Using nine environmental variables and the processed flux data as training data, Bayesian Additive Regression Tree (BART) models were used to generate annual flux balances for CO 2 and CH 4 . The 4-year mean annual flux at the Control Site was 17.3 ± 10 g CO 2 -C m − 2 yr − 1 and 4.6 ± 0.1 g CH 4 -C m − 2 yr − 1 . At the Treatment Site, the 2-year mean annual flux before the rewetting was 12.2  ±  3.8 g CO 2 -C m − 2 yr − 1 and 1.8  ±  0.04 g CH 4 -C m − 2 yr − 1 . In the first year after rewetting the annual flux was 53.3  ±  13 g CO 2 -C m − 2 yr − 1 and 3.8  ±  0.3 g CH 4 -C m − 2 yr − 1 , and in the second year after rewetting the annual flux was 41.2  ±  18 g CO 2 -C m − 2 yr − 1 and 3.4  ±  0.4 g CH 4 -C m − 2 yr − 1 . BART counterfactual modeling was able to estimate the effect of the rewetting on CO 2 and CH 4 fluxes. Two years after the rewetting, the BART counterfactual modeling estimated that the cumulative fluxes had increased by 80.3 ± 49 g CO 2 -C m − 2 and 3.4 ± 0.47 g CH 4 -C m − 2 because of the rewetting. Carbon flux monitoring of both sites is ongoing as the Control Site remains drained and the soil and vegetation at the Treatment Site continues to adjust to the altered hydrological regime after rewetting.

The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing the spatial variation in a heterogeneous landscapes. This study investigates the potential of 10 m resolution reflectance from the Sentinel-2 Multispectral Instrument to improve the accuracy of GPP estimation across Nordic vegetation types, compared with the 250 m and 500 m resolution reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). We applied linear regression models with inputs of two-band enhanced vegetation index (EVI2) derived from Sentinel-2 and MODIS reflectance, respectively, together with various environmental drivers to estimate daily GPP at eight Nordic eddy covariance (EC) flux tower sites. Compared with the GPP from EC measurements, the accuracies of modelled GPP were generally high (R2 = 0.84 for Sentinel-2; R2 = 0.83 for MODIS), and the differences between Sentinel-2 and MODIS were minimal. This demonstrates the general consistency in GPP estimates based on the two satellite sensor systems at the Nordic regional scale. On the other hand, the model accuracy did not improve by using the higher spatial-resolution Sentinel-2 data. More analyses of different model formulations, more tests of remotely sensed indices and biophysical parameters, and analyses across a wider range of geographical locations and times will be required to achieve improved GPP estimations from Sentinel-2 satellite data.

High resolution root-zone soil moisture (SM) maps are important for understanding the spatial variability of water availability in agriculture, ecosystems research and water resources management. Unmanned Aerial Systems (UAS) can flexibly monitor land surfaces with thermal and optical imagery at very high spatial resolution (meter level, VHR) for most weather conditions. We modified the temperature–vegetation triangle approach to transfer it from satellite to UAS remote sensing. To consider the effects of the limited coverage of UAS mapping, theoretical dry/wet edges were introduced. The new method was tested on a bioenergy willow short rotation coppice site during growing seasons of 2016 and 2017. We demonstrated that by incorporating surface roughness parameters from the structure-from-motion in the interpretation of the measured land surface-atmosphere temperature gradients, the estimates of SM significantly improved. The correlation coefficient between estimated and measured SM increased from not significant to 0.69 and the root mean square deviation decreased from 0.045 m3∙m−3 to 0.025 m3∙m−3 when considering temporal dynamics of surface roughness in the approach. The estimated SM correlated better with in-situ root-zone SM (15–30 cm) than with surface SM (0–5 cm) which is an important advantage over alternative remote sensing methods to estimate SM. The optimal spatial resolution of the triangle approach was found to be around 1.5 m, i.e. similar to the length scale of tree-crowns. This study highlights the importance of considering the 3-D fine scale canopy structure, when addressing the links between surface temperature and SM patterns via surface energy balances. Our methodology can be applied to operationally monitor VHR root-zone SM from UAS in agricultural and natural ecosystems.

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process‐based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological‐climate‐induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest‐based mitigation strategies and should be carefully considered within a portfolio of mitigation options. Key Points How will C‐fluxes, CUE, and C‐stocks of the major European forest types may respond to elevated atmospheric CO2, warming, and management in the future? Results show that managed forests left unthinned will reduce their CUE and their C‐stocks capability faster under climate change because of accelerated development Results show that thinning may have a large influence on C‐sequestration improving forest efficiency in stocking C as also in preventing risks of forest dieback

An oil and gas pipeline monitoring platform uses internet of things (IoT) to ensure safe operation in remote and unattended areas, through automatic monitoring and systematic control on equipment such as the cut-off valves and cathodic protection systems. The continuity and stability of power supplies for various equipment of an oil and gas pipeline IoT monitoring platform is crucial. There is no single universal off-grid power supply method that is optimal for an oil and gas pipeline IoT monitoring platform in all different contexts. Therefore, it is necessary to select a suitable one according to the specific geographical location and meteorological conditions. This paper proposes an off-grid power supply system comprised of a reversible solid oxide fuel cell (RESOC), photovoltaic (PV) and battery. Minimum operating costs and the reliability of system operations under constraint conditions are the key determining objectives. A “PV + battery + RESOC” system operational optimization model is established. Based on the model, three types of off-grid power supply schemes are proposed, and three geographical locations with different meteorological conditions are selected as practical application scenarios. The Matlab Cplex solver is used to solve the different power supply modes of the three regions. And finally, the power supply scheme with the best reliability and economy under different geographical environments and meteorological conditions is obtained.

Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or—more generally—for the production of organic matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings—FPE declining with age—are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate. Many models assume a universal carbon use efficiency across forest biomes, in contrast to assumptions of other process-based models. Here the authors analyse forest production efficiency across a wide range of climates to show a positive relationship with annual temperature and precipitation, indicating that ecosystem models are overestimating forest carbon losses under warming.

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.