Methane fluxes in tidal marshes of the conterminous United States.

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 CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux 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 CH4 emissions. 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 CH4 m-2 year-1, with a median of 3.9 g CH4 m-2 year-1, and only 25% of sites exceeding 18 g CH4 m-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 CH4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m-2 s-1 at 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 CH4 fluxes, 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 CH4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH4 fluxes, with pulsed releases of stored CH4 at low to rising tide. This study provides data and methods to improve tidal marsh CH4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

Complex eco-evolutionary responses of a foundational coastal marsh plant to global change.

Predicting the fate of coastal marshes requires understanding how plants respond to rapid environmental change. Environmental change can elicit shifts in trait variation attributable to phenotypic plasticity and act as selective agents to shift trait means, resulting in rapid evolution. Comparably, less is known about the potential for responses to reflect the evolution of trait plasticity. Here, we assessed the relative magnitude of eco-evolutionary responses to interacting global change factors using a multifactorial experiment. We exposed replicates of 32 Schoenoplectus americanus genotypes 'resurrected' from century-long, soil-stored seed banks to ambient or elevated CO2 , varying levels of inundation, and the presence of a competing marsh grass, across two sites with different salinities. Comparisons of responses to global change factors among age cohorts and across provenances indicated that plasticity has evolved in five of the seven traits measured. Accounting for evolutionary factors (i.e. evolution and sources of heritable variation) in statistical models explained an additional 9-31% of trait variation. Our findings indicate that evolutionary factors mediate ecological responses to environmental change. The magnitude of evolutionary change in plant traits over the last century suggests that evolution could play a role in pacing future ecosystem response to environmental change.

Accounting for variability when resurrecting dormant propagules substantiates their use in eco-evolutionary studies.

There has been a steady rise in the use of dormant propagules to study biotic responses to environmental change over time. This is particularly important for organisms that strongly mediate ecosystem processes, as changes in their traits over time can provide a unique snapshot into the structure and function of ecosystems from decades to millennia in the past. Understanding sources of bias and variation is a challenge in the field of resurrection ecology, including those that arise because often-used measurements like seed germination success are imperfect indicators of propagule viability. Using a Bayesian statistical framework, we evaluated sources of variability and tested for zero-inflation and overdispersion in data from 13 germination trials of soil-stored seeds of Schoenoplectus americanus, an ecosystem engineer in coastal salt marshes in the Chesapeake Bay. We hypothesized that these two model structures align with an ecological understanding of dormancy and revival: zero-inflation could arise due to failed germinations resulting from inviability or failed attempts to break dormancy, and overdispersion could arise by failing to measure important seed traits. A model that accounted for overdispersion, but not zero-inflation, was the best fit to our data. Tetrazolium viability tests corroborated this result: most seeds that failed to germinate did so because they were inviable, not because experimental methods failed to break their dormancy. Seed viability declined exponentially with seed age and was mediated by seed provenance and experimental conditions. Our results provide a framework for accounting for and explaining variability when estimating propagule viability from soil-stored natural archives which is a key aspect of using dormant propagules in eco-evolutionary studies.