ABSTRACT
The ongoing climate crisis merits an urgent need to devise management approaches and new technologies to reduce atmospheric greenhouse gas concentrations (GHG) in the near term. However, each year that GHG concentrations continue to rise, pressure mounts to develop and deploy atmospheric CO2 removal pathways as a complement to, and not replacement for, emissions reductions. Soil carbon sequestration (SCS) practices in working lands provide a low-tech and cost-effective means for removing CO2 from the atmosphere while also delivering co-benefits to people and ecosystems. Our model estimates suggest that, assuming additive effects, the technical potential of combined SCS practices can provide 30%-70% of the carbon removal required by the Paris Climate Agreement if applied to 25%-50% of the available global land area, respectively. Atmospheric CO2 drawdown via SCS has the potential to last decades to centuries, although more research is needed to determine the long-term viability at scale and the durability of the carbon stored. Regardless of these research needs, we argue that SCS can at least serve as a bridging technology, reducing atmospheric CO2 in the short term while energy and transportation systems adapt to a low-C economy. Soil C sequestration in working lands holds promise as a climate change mitigation tool, but the current rate of implementation remains too slow to make significant progress toward global emissions goals by 2050. Outreach and education, methodology development for C offset registries, improved access to materials and supplies, and improved research networks are needed to accelerate the rate of SCS practice implementation. Herein, we present an argument for the immediate adoption of SCS practices in working lands and recommendations for improved implementation.
Subject(s)
Greenhouse Effect , Soil , Humans , Ecosystem , Carbon Dioxide/analysis , Carbon Sequestration , Carbon , Technology , AgricultureABSTRACT
Large CH and NO fluxes can occur from flooded rice ( L.) systems following end-of-season drainage, which contribute significantly to the total growing-season greenhouse gas (GHG) emissions. Field and laboratory studies were conducted to determine under what soil water conditions these emissions occur. In three field studies, GHG fluxes and dissolved CH in the soil pore water were measured before and after drainage. Across all fields, approximately 10% of the total seasonal CH emissions and 27% of the total seasonal NO emissions occurred following the final drain, confirming the importance of quantifying postdrainage CH and NO emissions. Preplant fertilizer N had no effect on CH emissions or dissolved CH; however, increased postdrainage NO fluxes were observed at higher N rates. To determine when postdrainage sampling needs to take place, our laboratory incubation study measured CH and NO fluxes from intact soil cores from these fields as the soil dried. Across fields, maximum CH emissions occurred at approximately 88% water-filled pore space (WFPS), but emissions were observed between 47 and 156% WFPS. In contrast, maximum NO emissions occurred between 45 and 71% WFPS and were observed between 16 and 109% WFPS. For all fields, gas samplings between 76 and 100% WFPS for CH emissions and between 43 and 78% WFPS for NO emissions was necessary to capture 95% of these postdrainage emissions. We recommend that frequent gas sampling following drainage be included in the GHG protocol of total GHG emissions.
ABSTRACT
An understanding of cultivar effects on field greenhouse gas (GHG) emissions in rice ( L.) systems is needed to improve the accuracy of predictive models used for estimating GHG emissions and to evaluate the GHG mitigation potential of different cultivars. We compared CH and NO emissions, global warming potential (GWP = NO + CH), yield-scaled GWP (GWP = GWP Mg grain), and plant growth characteristics of eight cultivars within four study sites in California and Arkansas. Nitrous oxide emissions were negligible (<10% of GWP) and were not different among cultivars. Seasonal CH emissions differed between cultivars by a factor of 2.1 and 1.4 at one California and one Arkansas site, respectively. Plant growth characteristics were generally not correlated with seasonal CH emissions; however, the strongest correlations were observed for shoot and total plant (root + shoot) biomass at heading ( = 0.60) at one California site and for grain at maturity ( = -0.95) at one Arkansas site. Although differences in GWP and GWP were observed, there were inconsistencies across sites, indicating the importance of the genotype × environment interaction. Overall, the cultivars with the lowest CH emissions, GWP, and GWP at the California and Arkansas sites were the lowest and highest yielding, respectively. These findings highlight the potential for breeding high-yielding cultivars with low GWP, the ideal scenario to achieve low GWP, but environmental conditions must also be considered.
ABSTRACT
Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats-instructions, templates, and tools for consistently formatting data within a discipline-can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.
Subject(s)
Environmental Science , Research Design , Metadata , WorkflowABSTRACT
The effectiveness of land-based climate mitigation strategies is generally estimated on a case-by-case basis without considering interactions with other strategies or influencing factors. Here we evaluate a new, comprehensive approach that incorporates interactions among multiple management strategies, land use/cover change, wildfire, and climate, although the potential effects of climate change are not evaluated in this study. The California natural and working lands carbon and greenhouse gas model (CALAND) indicates that summing individual practice estimates of greenhouse gas impacts may underestimate emission reduction benefits in comparison with an integrated estimate. Annual per-area estimates of the potential impact of specific management practices on landscape emissions can vary based on the estimation period, which can be problematic for extrapolating such estimates over space and time. Furthermore, the actual area of implementation is a primary factor in determining potential impacts of management on landscape emissions. Nonetheless, less intensive forest management, avoided conversion to urban land, and urban forest expansion generally create the largest annual per-area reductions, while meadow restoration and forest fuel reduction and harvest practices generally create the largest increases with respect to no management. CALAND also shows that data uncertainty is too high to determine whether California land is a source or a sink of carbon emissions, but that estimating effects of management with respect to a baseline provides valid results. Important sources of this uncertainty are initial carbon density, net ecosystem carbon accumulation rates, and land use/cover change data. The appropriate choice of baseline is critical for generating valid results.