Embedded Files
Does the interaction between years and treatment affect the CO2 and N2O fluxes?
To evaluate if the interaction between years and treatment affect the CO2 and N2O fluxes, I conducted a two-factor Analysis of Variance (ANOVA), and found that for both CO2 flux (p = 0.4416) and N2O flux (p = 0.1812) the interaction is not significant (p > 0.05), which means that the consecutive years did not affect the GHG emissions. This suggests that the differences observed in Figures 5 and 10 likely reflect underlying environmental variation rather than a changing effect of treatments over time.
Do organic soil treatments influence CO₂ and N₂O emissions over time?
Since the interaction between years and treatments did not significantly affect seasonal CO₂ and N₂O fluxes, effect size analysis was conducted by combining mean values across years and blocks using the emmeans function in R. Figures 11 and 12 are a plot of estimated marginal means (emmeans) for CO₂ flux and N2O flux across treatments, with a red dashed line on the synthetic fertilizer (SF) control, which allows us to observe which treatments emit more or less compared to the SF control. The error bar is one standard error calculated with the emmeans function in R. The treatment "Control", with no additions, serves to identify if there was an error during experimental set up, however it does not represent a realistic control to compare the potential improvements from our applied treatments. For this experiment, the treatment "SF" is the true control because it represents what the current agricultural practice is, therefore it will be referred to as SF control. I conducted a test of inferiority comparing each treatment against the SF control, and the p-values in Figure 11 and 12 were calculated using the contrast function in R.
Figure 11: Mean seasonal CO2 flux.
Figure 11 represents the mean seasonal CO2 flux obtained from our blocks across the years. On the right part of the graph, the p-values were tested against the alternate hypothesis that organic treatments would have less CO2 emissions than our SF control. We can observe that the treatment using compost, biochar, wood ash, gypsum and SF was the one with the smallest CO2 emissions. However, this difference when compared to our SF control does not represent a statistical significance, with a p=value of 0.8260. The p-values were tested against the alpha-level of 0.05, and since for all treatments the p-value is greater than 0.05, none of the treatments have a significant difference to our SF control and we reject the alternate hypothesis. In other words, none of the organic treatments significantly reduced CO2 emissions.
Figure 12: Mean seasonal N2O flux.
Similar to Figure 11, the Figure 12 represents the mean seasonal N2O flux obtained from our blocks across the years. On the right part of the graph, the p-values were tested against the alternate hypothesis that organic treatments would have less N2O emissions than our SF control.
In terms of N2O, the difference between the treatments and our SF control is even less significant, with the smallest p-value of 0.9996 for the treatment with compost and wood ash. With these values, we reject the alternate hypothesis for every treatment applied. These results show us that the organic treatments applied did not have a significant impact on N2O emissions.
Conclusion
This study aimed to understand the influence of organic soil treatments on CO₂ and N₂O emissions over time, determine whether these emissions vary by year, and assess whether organic treatments reduce greenhouse gas (GHG) emissions. The results from Figures 11 and 12 suggest that treatments with organic amendments generally result in lower CO₂ and N₂O emissions, supporting the hypothesis that organic amendments can reduce GHG impacts compared to the current practice of applying synthetic fertilizers. However, the differences observed are not statistically significant. Therefore, we can conclude that neither years or treatments significantly impact the GHG emissions, both for CO2 and N2O greenhouse gases.
From figures 5 and 10 from the Data Exploration section, we observe a decreasing trend in CO2 emissions over time, and reduced N2O emissions in 2024. These findings suggest that organic amendments may have cumulative benefits over time, possibly due to improved soil conditions from organic matter input. Specifically in terms of N2O, a potential reason for the reduced emissions in 2024 is because fava beans is a legume, and legumes are known for fixing atmospheric nitrogen, therefore reducing its concentration in the atmosphere.
Overall, while organic treatments show promise for reducing GHG emissions, the effects are relatively small and sensitive to annual environmental variations and, potentially, crop rotations. If the research is continued long-term, we will be able to evaluate whether GHG emissions are consistently reduced after continuous application of organic amendments.
Given the current results, none of the treatments can be definitively recommended, and treatment selection should instead be guided by other considerations, such as soil quality and nutrient availability. For future work, another relevant response variable will be yield data. Correlating yield with GHG emissions will allow us to identify treatments that are both sustainable and productive. Additionally, I would use mixed models and include soil moisture and soil temperature as covariates, year and block as random effect, treatment as fixed effect, and cumulative seasonal GHG flux and crop yield as response variable. Using soil moisture and temperature as covariates is important because they can account for undesired variations in GHG fluxes, while years and blocks can be added as random effects to account for variability introduced by the repeated measurements. Other variables that could be investigated more in-depth are crop type, carbon to nitrogen ratio, and nutrients in the soil, as they could give valuable influence of the results as a fixed effect or random effect, depending on the specific research questions.
Page updated
Report abuse