The fate of rice crop residues and context-dependent greenhouse gas emissions: Model-based insights from Eastern India.

Crop residue burning is a common practice in many parts of the world that causes air pollution and greenhouse gas (GHG) emissions. Regenerative practices that return residues to the soil offer a 'no burn' pathway for addressing air pollution while building soil organic carbon (SOC). Nevertheless, GHG emissions in rice-based agricultural systems are complex and difficult to anticipate, particularly in production contexts with highly variable hydrologic conditions. Here we predict long-term net GHG fluxes for four rice residue management strategies in the context of rice-wheat cropping systems in Eastern India: burning, soil incorporation, livestock fodder, and biochar. Estimations were based on a combination of Tier 1, 2, and 3 modelling approaches, including 100-year DNDC simulations across three representative soil hydrologic categories (i.e., dry, median, and wet). Overall, residue burning resulted in total direct GHG fluxes of 2.5, 6.1, and 8.7 Mg CO2-e in the dry, median, and wet hydrologic categories, respectively. Relative to emissions from burning (positive values indicate an increase) for the same dry to wet hydrologic categories, soil incorporation resulted in a -0.2, 1.8, or 3.1 Mg CO2-e change in emissions whereas use of residues for livestock fodder increased emissions by 2.0, 2.1, or 2.3 Mg CO2-e. Biochar reduced emissions relative to burning by 2.9 Mg CO2-e in all hydrologic categories. This study showed that the production environment has a controlling effect on methane and, therefore, net GHG balance. For example, wetter sites had 2.8-4.0 times greater CH4 emissions, on average, than dry sites when rice residues were returned to the soil. To effectively mitigate burning without undermining climate change mitigation goals, our results suggest that geographically-target approaches should be used in the rice-based systems of Eastern India to incentivize the adoption of regenerative 'no burn' residue management practices.

High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts.

Global rice cultivation is estimated to account for 2.5% of current anthropogenic warming because of emissions of methane (CH4), a short-lived greenhouse gas. This estimate assumes a widespread prevalence of continuous flooding of most rice fields and hence does not include emissions of nitrous oxide (N2O), a long-lived greenhouse gas. Based on the belief that minimizing CH4 from rice cultivation is always climate beneficial, current mitigation policies promote increased use of intermittent flooding. However, results from five intermittently flooded rice farms across three agroecological regions in India indicate that N2O emissions per hectare can be three times higher (33 kg-N2O⋅ha-1⋅season-1) than the maximum previously reported. Correlations between N2O emissions and management parameters suggest that N2O emissions from rice across the Indian subcontinent might be 30-45 times higher under intensified use of intermittent flooding than under continuous flooding. Our data further indicate that comanagement of water with inorganic nitrogen and/or organic matter inputs can decrease climate impacts caused by greenhouse gas emissions up to 90% and nitrogen management might not be central to N2O reduction. An understanding of climate benefits/drawbacks over time of different flooding regimes because of differences in N2O and CH4 emissions can help select the most climate-friendly water management regimes for a given area. Region-specific studies of rice farming practices that map flooding regimes and measure effects of multiple comanaged variables on N2O and CH4 emissions are necessary to determine and minimize the climate impacts of rice cultivation over both the short term and long term.

A physicochemical model for analyzing DNA sequences.

In search of an ab initio model to characterize DNA sequences as genes and nongenes, we examined some physicochemical properties of each trinucleotide (codon), which could accomplish this task. We constructed three-dimensional vectors for each double-helical trinucleotide sequence considering hydrogen-bonding energy, stacking energy, and a third parameter, which we provisionally identified with DNA-protein interactions. As this three-dimensional vector moves along any genome, the net orientation of the resultant vector should differ significantly for gene and nongene regions to make a distinction feasible, if the underlying model has some merits. An analysis of 331 prokaryotic genomes comprising a total of 294 786 experimentally verified genes (nonoverlapping) and an equal number of nongenes presents a proof of concept of the model without the need for further parametrization. Also, initial analyses on Saccharomyces cerevisiae and Arabidopsis thaliana suggest that the methodology is extendable to eukaryotes. The physicochemical model (ChemGenome1.0) introduced has the potential to be developed into a gene-finding algorithm and, more pressingly, could be employed for an independent assessment of the annotation of DNA sequences.