Methane (CH4) exchange in wetlands is complex, involving nonlinear asynchronous processes across diverse time scales. These processes and time scales are poorly characterized at the whole‐ecosystem level, yet are crucial for accurate representation of CH4 exchange in process models. We used a combination of wavelet analysis and information theory to analyze interactions between whole‐ecosystem CH4 flux and biophysical drivers in two restored wetlands of Northern California from hourly to seasonal time scales, explicitly questioning assumptions of linear, synchronous, single‐scale analysis. Although seasonal variability in CH4 exchange was dominantly and synchronously controlled by soil temperature, water table fluctuations, and plant activity were important synchronous and asynchronous controls at shorter time scales that propagated to the seasonal scale. Intermittent, subsurface water table decline promoted short‐term pulses of methane emission but ultimately decreased seasonal CH4 emission through subsequent inhibition after rewetting. Methane efflux also shared information with evapotranspiration from hourly to multiday scales and the strength and timing of hourly and diel interactions suggested the strong importance of internal gas transport in regulating short‐term emission. Traditional linear correlation analysis was generally capable of capturing the major diel and seasonal relationships, but mesoscale, asynchronous interactions and nonlinear, cross‐scale effects were unresolved yet important for a deeper understanding of methane flux dynamics. We encourage wider use of these methods to aid interpretation and modeling of long‐term continuous measurements of trace gas and energy exchange.

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality.

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We present 6.5 years of eddy covariance measurements of fluxes of methane (F CH4 ) and carbon dioxide (F CO2 ) from a flooded rice paddy in Northern California, USA. A pronounced warming trend throughout the study associated with drought and record high temperatures strongly influenced carbon (C) budgets and provided insights into biophysical controls of F CO2 and F CH4 . Wavelet analysis indicated that photosynthesis (gross ecosystem production, GEP) induced the diel pattern in F CH4 , but soil temperature (T s ) modulated its amplitude. Forward stepwise linear models and neural networking modeling were used to assess the variables regulating seasonal F CH4 . As expected due to their competence in modeling nonlinear relationships, neural network models explained considerably more of the variance in daily average F CH4 than linear models. During the growing season, GEP and water levels typically explained most of the variance in daily average F CH4 . However, T s explained much of the interannual variability in annual and growing season CH 4 sums. Higher T s also increased the annual and growing season ratio of F CH4 to GEP. The observation that the F CH4 to GEP ratio scales predictably with T s may help improve global estimates of F CH4 from rice agriculture. Additionally, T s strongly influenced ecosystem respiration, resulting in large interannual variability in the net C budget at the paddy, emphasizing the need for long-term measurements particularly under changing climatic conditions.

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