Soil pH is undoubtedly one of the key environmental parameters influencing soil biology and biogeochemistry. Nevertheless, measuring soil pH at in situ like conditions is not trivial. The current gold standard requires preparing a soil suspension with water or CaCl2, in which the soil pH can be assessed. Obviously, this is far from in situ conditions. In this study we evaluate optical pH sensors, so-called pH optodes, as an alternative technology to measure soil pH both in wet and dry soils. Our results indicate that pH optodes have the potential to sense soil pH in a wide range of soil water contents. We also compared our results to the standard slurry method and to measurements using a classical glass pH electrode.
Globally, organic soils of natural and semi-natural ecosystems have been considered as an important source of atmospheric nitrous oxide (N2O), a powerful greenhouse gas. However, we have little understanding of how and to what extent the magnitude of N2O emissions from such soils is mediated by variation in environmental controls. This knowledge is critical for scaling up the results of measurements from local to regional or global scales. Here we report on two-year field measurements of N2O fluxes from various alpine land use/cover types at 24 sites across an altitudinal gradient in a catchment on the eastern Tibetan Plateau. We found that annual N2O emissions varied between 0.05 and 1.39 kg N ha−1 yr−1, with non-growing season contributing 11–60% to these annual budgets. Our field results, together with published data from 43 studies on organic soils globally (natural and semi-natural ecosystems) showed that across all datasets, annual N2O fluxes were more closely related to the soil C/N ratio. Weaker relationships were found to the mean water table depth (WTD) and soil total N content. In contrast to the general assumption that soil N2O emissions may consistently increase with a narrowing of the organic soil C/N ratio, we found strong indications that the relationship of annual N2O fluxes to soil C/N ratio followed an optimum Gaussian curve, with a threshold at a C/N ratio of about 18–19. Moreover, there was a tendency towards high N2O emissions for sites with a mean annual WTD > 0.15 m, indicating a potential risk for increased N2O emissions from global organic soils under water table drawdown driven by climate drying or peatland drainage. Overall, our results suggest that the soil C/N ratio could be used as an indicator to better constrain the contribution of organic soils to N2O emissions from landscape at global scales.
Accurate quantification of landscape soil greenhouse gas (GHG) exchange from chamber measurements is challenging due to the high spatial-temporal variability of fluxes, which results in large uncertainties in upscaled regional and global flux estimates. We quantified landscape-scale (6 km2 in central Germany) soil/ecosystem respiration (SR/ER-CO2), methane (CH4), and nitrous oxide (N2O) fluxes at stratified sites with contrasting landscape characteristics using the fast-box chamber technique. We assessed the influence of land use (forest, arable, and grassland), seasonality (spring, summer, and autumn), soil types, and slope on the fluxes. We also evaluated the number of chamber measurement locations required to estimate landscape fluxes within globally significant uncertainty thresholds. The GHG fluxes were strongly influenced by seasonality and land use rather than soil type and slope. The number of chamber measurement locations required for robust landscape-scale flux estimates depended on the magnitude of fluxes, which varied with season, land use, and GHG type. Significant N2O-N flux uncertainties greater than the global mean flux (0.67 kg ha−1 yr−1) occurred if landscape measurements were done at <4 and <22 chamber locations (per km2) in forest and arable ecosystems, respectively, in summer. For CO2 and CH4 fluxes, uncertainties greater than the global median CO2-C flux (7,500 kg ha−1 yr−1) and the global mean forest CH4-C uptake rate (2.81 kg ha−1 yr−1) occurred at <2 forest and <6 arable chamber locations. This finding suggests that more chamber measurement locations are required to assess landscape-scale N2O fluxes than CO2 and CH4, based on these GHG-specific uncertainty thresholds.
Background: Globally, rice systems are a major source of atmospheric CH4 and for major rice-producing countries, such as Vietnam, CH4 as well as N2O emissions from agricultural land used for rice production may represent about one-fourth of total national anthropogenic greenhouse gas (GHG) emissions. However, national-scale estimates of GHG emissions from rice systems are uncertain with regard to its magnitude, spatial distribution, and seasonality.
Aims: Here, we used the biogeochemical model, LandscapeDNDC, to calculate emissions of CH4 and N2O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N2O to the total non-CO2 (CH4+N2O) GHG balance of rice systems as well as the seasonal and interannual variability of fluxes in dependence of uncertain input data on field management.
Methods: The biogeochemical model, LandscapeDNDC, was linked to publicly available information on climate, soils, and land management (fertilization, irrigation, crop rotation) for calculating a national inventory in daily time steps of CH4 and N2O emissions from rice systems at a spatial resolution of 0.083◦ × 0.083◦. Uncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH4 and N2O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions.
Results: Our study shows that CH4 and N2O fluxes from rice systems in Vietnam are highly seasonal, with national CH4 and N2O emissions totaling to about 2600 Gg CH4 y–1 and 42 Gg N2O y–1, respectively. Highest emissions were simulated for double and triple rice cropping systems in the Mekong Delta region. Yield-scaled emissions varied largely in a range of 300–3000 kg CO2-eq Mg–1 y–1, with CH4 emissions during the rice season(s) dominating (>82%) the total annual non-CO2 GHG balance of rice systems. In our study, uncertainty in field management information (nitrogen fertilization, ratio synthetic to organic fertilization, residue management, availability of irrigation water) were major drivers of uncertainty of the national CH4 and N2O emission inventory.
Livestock are an important source of livelihoods in agricultural systems in sub-Saharan Africa (SSA), while also being the largest source of national greenhouse gas (GHG) emissions in most African countries. As a consequence, there is a critical need for data on livestock GHG sources and sinks to develop national inventories, as well as conduct baseline measurements and intervention testing to mitigate GHG emissions and meet ambitious national climate goals. Our objective was to review studies on GHG emissions from livestock systems in SSA, as well as soil carbon storage in livestock-dominated systems (i.e., grasslands and rangelands), to evaluate best current data and suggest future research priorities. To this end, we compiled studies from SSA that determined emission factors (EFs) for enteric methane and manure emissions, along with studies on soil organic carbon (SOC) stocks in SSA. We found that there has been limited research on livestock GHG emissions and SOC relative to national ambitions for climate change mitigation in SSA. Enteric methane emission factors (EFs) in low productivity cattle systems may be lower than IPCC Tier 1 default EFs, whereas small ruminants (i.e. sheep and goats) had higher EFs compared to IPCC Tier 1 EFs. Manure EFs were equal to or lower than IPCC Tier 1 EFs for deposited manure (while grazing), manure applied as fertilizer, and manure management. SOC stocks for grasslands and rangelands in SSA show broad agreement with IPCC estimates, but there was a strong geographic bias and many studies did not report soil type, bulk density, or SOC stocks at >30 cm depth. In general, the largest data gaps included information for manure (quantity, quality, management), small ruminants, agropastoral/pastoralist systems, and in general from West Africa. Future research should focus on filling major data gaps on locally appropriate mitigation interventions and improving livestock activity data for developing Tier 2 GHG inventories in SSA. At the science-policy interface, all parties would benefit from enhanced coordination within the research community and between researchers and African governments to improve Tier 2 inventories and harmonize measurement for mitigation in livestock systems in SSA.
Climate change is increasingly putting milk production from cattle-based dairy systems in north sub-Saharan Africa (NSSA) under stress, threatening livelihoods and food security. Here we combine livestock heat stress frequency, dry matter feed production and water accessibility data to understand where environmental changes in NSSA’s drylands are jeopardizing cattle milk production. We show that environmental conditions worsened for ∼17% of the study area. Increasing goat and camel populations by ∼14% (∼7.7 million) and ∼10% (∼1.2 million), respectively, while reducing the dairy cattle population by ∼24% (∼5.9 million), could result in ∼0.14 Mt (+5.7%) higher milk production, lower water (−1,683.6 million m3, −15.3%) and feed resource (−404.3 Mt, −11.2%) demand—and lower dairy emissions by ∼1,224.6 MtCO2e (−7.9%). Shifting herd composition from cattle towards the inclusion of, or replacement with, goats and camels can secure milk production and support NSSA’s dairy production resilience against climate change.