Multi-experiment assessment of soil nitrous oxide emissions in sugarcane

Soil nitrous oxide (N 2O) fluxes comprise a significant part of the greenhouse gas emissions of agricultural products but are spatially and tempo-rally variable, due to complex interactions between climate, soil and management variables. This study aimed to identify the main factors that affect N2Oemissions under sugarcane, using a multi-site data-base from field experiments. Greenhouse gas fluxes, soil, climate, and management data were obtained from 13 field trials spanning the 2011–2017 period. We conducted exploratory, descriptive and inferential data analyses in experiments with varying fertiliser and stillage (vinasse) type and rate, and crop residue rates. The most relevant period of high N2O fluxes was the first 46 days after fertiliser application. The results indicate a strong positive correlation of cumulative N2O with nitrogen (N) fertiliser rate, soil fungi community (18S rRNA gene), soil ammonium(NH 4+ ) and nitrate (NO3−); and a moderate negative correlation with amoA genes of ammonia-oxidising archaea (AOA) and soil organic matter content. The regression analysis revealed that easily routinely measured climate and management-related variables explained over 50% of the variation in cumulativeN2O emissions, and that additional soil chemical and physical parameters improved the regression fit within R2 = 0.65. Cross-wavelet analysis indicated significant correlations of N2O fluxes with rainfall and air temperature up to 64 days, associated with temporal lags of 2 to 4 days in some experiments, and presenting a good environmental control over fluxes in general. The nitrogen fertiliser mean emission factors ranged from 0.03 to 1.17% of N applied, with urea and ammonium nitrate plus vinasse producing high emissions, while ammonium sulphate, ammonium nitrate without vinasse, calcium nitrate, and mitigation alternatives (nitrification inhibitors and timing of vinasse application) producing low N2O-EFs. Measurements from multiple sites spanning several crop-ping seasons were useful for exploring the influence of environmental and management-related variables on soil N 2O emissions in sugarcane production, providing support for global warming mitigation strategies, nitrogen management policies, and increased agricultural input efficiency

Importance of including soil moisture in drought monitoring over the Brazilian semiarid region: An evaluation using the JULES model, in situ observations, and remote sensing

Soil moisture information is essential to monitoring of the intensity of droughts, the start of the rainy season, planting dates and early warnings of yield losses. We assess spatial and temporal trends of drought over the Brazilian semiarid region by combining soil moisture observations from 360 stations, root zone soil moisture from a leading land surface model, and a vegetation health index from remote sensing. The soil moisture dataset was obtained from the network of stations maintained by the National Center of Monitoring and Early Warning of Natural Disasters (Cemaden), in Brazil. Soil water content at 10 to 35 cm depth, for the period 1979–2018, was obtained from running the JULES land surface model (the Joint UK Land Environment Simulator). The modelled soil moisture was correlated with measurements in the common period of 2015–2018, resulting in an average correlation coefficient of 0.48 across the domain. The standardized soil moisture anomaly (SMA) was calculated for the long-term modelled soil moisture and revealed strong negative values during well-known drought periods in the region, especially during El-Niño years. The performance of SMA in identifying droughts during the first 2 months of the raining and cropping season was similar to the Standardized Precipitation Index (SPI), commonly used for drought assessment: 12–14 events were identified by both indices. Finally, the temporal relationship between both SMA and SPI with the Vegetation Health Index (VHI) was assessed using the cross-wavelet transform. The results indicated lagged correlations of 1 to 1.5 months in the annual scale, suggesting that negative trends in SMA and SPI can be an early warning to yield losses during the growing season. Public policies on drought assessment should consider the combination of multiple drought indices, including soil moisture anomaly

Dataset for "Nitrogen pollution in Brazil: a policy coherence analysis of current N-related regulations for a potential integrated approach"

This study aims to assess a set of current nitrogen-related policies in Brazil by applying the Policy Coherence Analytical Framework, in order to show the coherences and incoherences of these policies and how they can impact the development of a potential integrated nitrogen policy approach. We follow the analytical framework proposed by Nilsson et al., (2016, 2012), using a seven-point scoring system, where positive interactions receive scores of +1 (enabling), +2 (reinforcing), or +3 (indivisible), negative interactions are scored as -1 (constraining), -2 (counteracting), or -3 (cancelling), and neutral score (0) is assigned when no significant positive or negative interactions occur between targets. This scale of interactions allows the identification of potential synergies between policy instruments (when one policy reinforce the achievement of another) and the trade-offs that should properly be managed (when policies cancel each other), thus highlighting priorities for potential integrated policies. This dataset contains all data used to apply the Policy Coherence Analytical Framework, including the list of selected policies, description of policy goals, policy classifications, links to official policy documents (in Portuguese), and results of coherence analysis

Dataset for "Nitrogen pollution in Brazil: a policy coherence analysis of current N-related regulations for a potential integrated approach"

This study aims to assess a set of current nitrogen-related policies in Brazil by applying the Policy Coherence Analytical Framework, in order to show the coherences and incoherences of these policies and how they can impact the development of a potential integrated nitrogen policy approach. We follow the analytical framework proposed by Nilsson et al., (2016, 2012), using a seven-point scoring system, where positive interactions receive scores of +1 (enabling), +2 (reinforcing), or +3 (indivisible), negative interactions are scored as -1 (constraining), -2 (counteracting), or -3 (cancelling), and neutral score (0) is assigned when no significant positive or negative interactions occur between targets. This scale of interactions allows the identification of potential synergies between policy instruments (when one policy reinforce the achievement of another) and the trade-offs that should properly be managed (when policies cancel each other), thus highlighting priorities for potential integrated policies. This dataset contains all data used to apply the Policy Coherence Analytical Framework, including the list of selected policies, description of policy goals, policy classifications, links to official policy documents (in Portuguese), and results of coherence analysis.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Dataset for "How sustainable is the nitrogen management in Brazil? A sustainability assessment using the Entropy Weight Method"

The main objective of this study is to assess the condition of nitrogen sustainability in Brazil over almost 20 years, considering the main sources of nitrogen pollution linked to agriculture and energy sectors, and related to the Sustainable Development Goals. For this, we compiled data from 31 indicators at the national level for the period 2000-2018, grouped into four subsystems (environmental, economic, social, and institutional). We applied the Entropy Weight Method (EWM) to measure the relevance of each indicator in each of the four subsystems, as well as the weight of each subsystem in the global outcome, that is, the nitrogen sustainability index. This dataset contains all data used to apply the EWM, as well as the results and graphics presented in the manuscript. It includes information such as data description, sources, and references. The application of the EWM was done step-by-step to facilitate its understanding (the methodological steps and all equations are also in the manuscript).THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Dataset for "How sustainable is the nitrogen management in Brazil? A sustainability assessment using the Entropy Weight Method"

The main objective of this study is to assess the condition of nitrogen sustainability in Brazil over almost 20 years, considering the main sources of nitrogen pollution linked to agriculture and energy sectors, and related to the Sustainable Development Goals. For this, we compiled data from 31 indicators at the national level for the period 2000-2018, grouped into four subsystems (environmental, economic, social, and institutional). We applied the Entropy Weight Method (EWM) to measure the relevance of each indicator in each of the four subsystems, as well as the weight of each subsystem in the global outcome, that is, the nitrogen sustainability index. This dataset contains all data used to apply the EWM, as well as the results and graphics presented in the manuscript. It includes information such as data description, sources, and references. The application of the EWM was done step-by-step to facilitate its understanding (the methodological steps and all equations are also in the manuscript).THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV