Wetlands are the largest source of methane (CH₄ ) globally, yet our understanding of how process-level controls scale to ecosystem fluxes remains limited. It is particularly uncertain how variable soil properties influence ecosystem CH₄ emissions on annual time scales. We measured ecosystem carbon dioxide (CO₂ ) and CH₄ fluxes by eddy covariance from two wetlands recently restored on peat and alluvium soils within the Sacramento-San Joaquin Delta of California. Annual CH₄ fluxes from the alluvium wetland were significantly lower than the peat site for multiple years following restoration, but these differences were not explained by variation in dominant climate drivers or productivity across wetlands. Soil iron (Fe) concentrations were significantly higher in alluvium soils, and alluvium CH₄ fluxes were decoupled from plant processes compared with the peat site, as expected when Fe reduction inhibits CH₄ production in the rhizosphere. Soil carbon content and CO₂ uptake rates did not vary across wetlands and, thus, could also be ruled out as drivers of initial CH₄ flux differences. Differences in wetland CH₄ fluxes across soil types were transient; alluvium wetland fluxes were similar to peat wetland fluxes 3 years after restoration. Changing alluvium CH₄ emissions with time could not be explained by an empirical model based on dominant CH₄ flux biophysical drivers, suggesting that other factors, not measured by our eddy covariance towers, were responsible for these changes. Recently accreted alluvium soils were less acidic and contained more reduced Fe compared with the pre-restoration parent soils, suggesting that CH₄ emissions increased as conditions became more favorable to methanogenesis within wetland sediments. This study suggests that alluvium soil properties, likely Fe content, are capable of inhibiting ecosystem-scale wetland CH₄ flux, but these effects appear to be transient without continued input of alluvium to wetland sediments.

Restoring degraded peat soils presents an attractive, but largely untested, climate change mitigation approach. Drained peat soils used for agriculture can be large greenhouse gas sources. By restoring subsided peat soils to managed, impounded wetlands, significant agricultural emissions are avoided, and soil carbon can be sequestered and protected. Here, we synthesize 36 site-years of continuous carbon dioxide and methane flux data from a mesonetwork of eddy covariance towers in the Sacramento-San Joaquin Delta in California, USA to compute carbon and greenhouse gas budgets for drained agricultural land uses and compare these to restored deltaic wetlands. We found that restored wetlands effectively sequestered carbon and halted soil carbon loss associated with drained agricultural land uses. Depending on the age and disturbance regime of the restored wetland, many land use conversions from agriculture to restored wetland resulted in emission reductions over a 100-year timescale. With a simple model of radiative forcing and atmospheric lifetimes, we showed that restored wetlands do not begin to accrue greenhouse gas benefits until nearly a half century, and become net sinks from the atmosphere after a century. Due to substantial interannual variability and uncertainty about the multi-decadal successional trajectory of managed, restored wetlands, ongoing ecosystem flux measurements are critical for understanding the long-term impacts of wetland restoration for climate change mitigation.

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems' responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.