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Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH₄production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH₄dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH₄sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH₄fluxes in tidal wetlands. This research introduces a novel approach to examining CH₄fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems. 

Abstract Methane (CH₄) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH₄emissions, yet the magnitude and factors controlling CH₄fluxes in tidal wetlands remain uncertain. We synthesized CH₄flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH₄emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH₄m⁻² year⁻¹, with a median of 3.9 g CH₄m⁻² year⁻¹, and only 25% of sites exceeding 18 g CH₄m⁻² year⁻¹. The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH₄flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m⁻² s⁻¹at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH₄fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH₄flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH₄fluxes, with pulsed releases of stored CH₄at low to rising tide. This study provides data and methods to improve tidal marsh CH₄emission estimates, support blue carbon assessments, and refine national and global GHG inventories.