Noninvasive ¹³C-octanoic acid breath test shows delayed gastric emptying in patients with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive loss of motor neurons. However, ALS has been recognized to also involve non-motor systems. Subclinical involvement of the autonomic system in ALS has been described. The recently developed C-13-octanoic acid breath test allows the noninvasive measurement of gastric emptying. With this new technique we investigated 18 patients with ALS and 14 healthy volunteers. None of the patients had diabetes mellitus or other disorders known to cause autonomic dysfunction. The participants received a solid standard test meal labeled with C-13-octanoic acid. Breath samples were taken at 15-min intervals for 5 h and were analyzed for (CO2)-C-13 by isotope selective nondispersive infrared spectrometry. Gastric emptying peak time (t(peak)) and emptying half time (t(1/2)) were determined. All healthy volunteers displayed normal gastric emptying with a mean emptying t(1/2) of 138 +/- 34 (range 68-172) min. Gastric emptying was delayed (t(1/2) > 160 min) in 15 of 18 patients with ALS. Emptying t(1/2) in ALS patients was 218 +/- 48 (range 126-278) min (p < 0.001). These results are compatible with autonomic involvement in patients with ALS, causing delayed gastric emptying of solids and encouraging the theory that ALS is a multisystem disease rather than a disease of the motor neurons only

Using the atmospheric CO2 growth rate to constrain the CO2 flux from land use and land cover change since 1900

We explore the ability of the atmospheric CO2 record since 1900 to constrain the source of CO2 from land use and land cover change (hereafter “land use”), taking account of uncertainties in other terms in the global carbon budget. We find that the atmospheric constraint favors land use CO2 flux estimates with lower decadal variability and can identify potentially erroneous features, such as emission peaks around 1960 and after 2000, in some published estimates. Furthermore, we resolve an offset in the global carbon budget that is most plausibly attributed to the land use flux. This correction shifts the mean land use flux since 1900 across 20 published estimates down by 0.35 PgC year−1 to 1.04 ± 0.57 PgC year−1, which is within the range but at the low end of these estimates. We show that the atmospheric CO2 record can provide insights into the time history of the land use flux that may reduce uncertainty in this term and improve current understanding and projections of the global carbon cycle. © 2022 The Authors. Global Change Biology published by John Wiley Sons Ltd

Land-use change emissions based on high-resolution activity data substantially lower than previously estimated

Land-use and land-cover changes (LULCCs) contributed around one third to the cumulative, anthropogenic CO2 emissions from 1850 to 2019. Despite its great importance, estimates of the net CO 2 fluxes from LULCC (E LUC ) have high uncertainties, compared to other components of the global carbon cycle. One major source of uncertainty roots in the underlying LULCC forcing data. In this study, we implemented a new high-resolution LULCC dataset (HILDA + ) in a bookkeeping model (BLUE) and compared the results to estimates from simulations based on LUH2, which is the LULCC dataset most commonly used in global carbon cycle models. Compared to LUH2-based estimates, results based on HILDA + show lower total E LUC (global mean difference 1960–2019: 541 TgC yr ⁻¹ , 65%) and large spatial and temporal differences in component fluxes (e.g. CO 2 fluxes from deforestation). In general, the congruence of component fluxes is higher in the mid-latitudes compared to tropical and subtropical regions, which is to some degree explained with the different implementations of shifting cultivation in the underlying LULCC datasets. However, little agreement is reached on the trend of the last decade between E LUC estimates based on the two LULCC reconstructions. Globally and in many regions, E LUC estimates based on HILDA + have decreasing trends, whereas estimates based on LUH2 indicate an increase. Furthermore, we analyzed the effect of different resolutions on E LUC estimates. By comparing estimates from simulations at 0.01 ∘ and 0.25 ∘ resolution, we find that component fluxes of estimates based on the coarser resolution tend to be larger compared to estimates based on the finer resolution, both in terms of sources and sinks (global mean difference 1960–2019: 36 TgC yr ⁻¹, 96%). The reason for these differences are successive transitions: these are not adequately represented at coarser resolution, which has the effect that—despite capturing the same extent of transition areas—overall less area remains pristine at the coarser resolution compared to the finer resolution

Simulating growth-based harvest adaptive to future climate change

Forests are the main source of biomass production from solar energy and take up around 2.4±0.4&thinsp;PgC per year globally. Future changes in climate may affect forest growth and productivity. Currently, state-of-the-art Earth system models use prescribed wood harvest rates in future climate projections. These rates are defined by integrated assessment models (IAMs), only accounting for regional wood demand and largely ignoring the supply side from forests. Therefore, we assess how global growth and harvest potentials of forests change when they are allowed to respond to changes in environmental conditions. For this, we simulate wood harvest rates oriented towards the actual rate of forest growth. Applying this growth-based harvest rule (GB) in JSBACH, the land component of the Max Planck Institute's Earth system model, forced by several future climate scenarios, we realized a growth potential 2 to 4 times (3–9&thinsp;PgC&thinsp;yr−1) the harvest rates prescribed by IAMs (1–3&thinsp;PgC&thinsp;yr−1). Limiting GB to managed forest areas (MF), we simulated a harvest potential of 3–7&thinsp;PgC&thinsp;yr−1, 2 to 3 times higher than IAMs. This highlights the need to account for the dependence of forest growth on climate. To account for the long-term effects of wood harvest as integrated in IAMs, we added a life cycle analysis, showing that the higher supply with MF as an adaptive forest harvesting rule may improve the net mitigation effects of forest harvest during the 21st century by sequestering carbon in anthropogenic wood products.</p

The impact of land cover change on surface energy and water balance in Mato Grosso, Brazil

The sensitivity of surface energy and water fluxes to recent land cover changes is simulated for a small region in northern Mato Grosso, Brazil. The Simple Biosphere Model (SiB2) is used, driven by biophysical parameters derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution, to compare the effects of different land conversion types. The mechanisms through which changes in vegetation alter surface fluxes of energy, momentum, water, and carbon are analyzed for both wet and dry seasons. It is found that morphological changes contribute to warming and drying of the atmosphere while physiological changes, particularly those associated with a plant’s photosynthetic pathway, counterbalance or exacerbate the warming depending on the type of conversion and the season. Furthermore, this study’s results indicate that initial clearing of evergreen and transition forest to bare ground increases canopy temperature by up to 1.7°C. For subsequent land use such as pasture or cropland, the largest effect is seen for the conversion of evergreen forest to C3 cropland during the wet season, with a 21% decrease of the latent heat flux and 0.4°C increase in canopy temperature. The secondary conversion of pasture to cropland resulted in slight warming and drying during the wet season driven mostly by the change in carbon pathway from C4 to C3. For all conversions types, the daily temperature range is amplified, suggesting that plants replacing forest clearing require more temperature tolerance than the trees they replace. The results illustrate that the effect of deforestation on climate depends not only on the overall extent of clearing but also on the subsequent land use type

Tracking 21st century anthropogenic and natural carbon fluxes through model-data integration

Monitoring the implementation of emission commitments under the Paris agreement relies on accurate estimates of terrestrial carbon fluxes. Here, we assimilate a 21st century observation-based time series of woody vegetation carbon densities into a bookkeeping model (BKM). This approach allows us to disentangle the observation-based carbon fluxes by terrestrial woody vegetation into anthropogenic and environmental contributions. Estimated emissions (from land-use and land cover changes) between 2000 and 2019 amount to 1.4 PgC yr−1, reducing the difference to other carbon cycle model estimates by up to 88% compared to previous estimates with the BKM (without the data assimilation). Our estimates suggest that the global woody vegetation carbon sink due to environmental processes (1.5 PgC yr−1) is weaker and more susceptible to interannual variations and extreme events than estimated by state-of-the-art process-based carbon cycle models. These findings highlight the need to advance model-data integration to improve estimates of the terrestrial carbon cycle under the Global Stocktake

Differences in land-based mitigation estimates reconciled by separating natural and land-use CO2 fluxes at the country level

Anthropogenic and natural CO2 fluxes on land constitute substantial CO2 emissions and removals but are usually not well distinguished in national greenhouse gas reporting. Instead, countries frequently combine natural and indirect human-induced CO2 fluxes on managed land in their reports, which diminishes their usefulness for designing policies consistent with climate mitigation targets. Here, we separate natural and land-use-related CO2 fluxes from national reports in eight countries using global models to improve the assessment of attribution of terrestrial CO2 fluxes to direct anthropogenic activities. In most investigated countries, the gap between model-based and report-based CO2 flux estimates is reduced if natural and indirect human-induced CO2 fluxes on managed land are considered. Further examinations show that remaining differences are linked to country-specific discrepancies between model-based and report-based estimates. Separating natural and land-use-related CO2 fluxes at national scales supports a fair burden sharing of climate mitigation across countries and facilitates the assessment of land-based mitigation ambitions. © 2022 The Author

Advances in land surface modelling

Land surface models have an increasing scope. Initially designed to capture the feedbacks between the land and the atmosphere as part of weather and climate prediction, they are now used as a critical tool in the urgent need to inform policy about land-use and water-use management in a world that is changing physically and economically. This paper outlines the way that models have evolved through this change of purpose and what might the future hold. It highlights the importance of distinguishing between advances in the science within the modelling components, with the advances of how to represent their interaction. This latter aspect of modelling is often overlooked but will increasingly manifest as an issue as the complexity of the system, the time and space scales of the system being modelled increase. These increases are due to technology, data availability and the urgency and range of the problems being studied. © 2021, The Author(s)