Mangrove forests play an important role in climate change adaptation and mitigation by maintaining coastline elevations relative to sea level rise, protecting coastal infrastructure from storm damage and storing substantial quantities of carbon (C) in live and detrital pools. Determining the efficacy of mangroves in achieving climate goals can be complicated by difficulty in quantifying C inputs (i.e., differentiating newer inputs from younger trees from older residual C pools), and mitigation assessments rarely consider potential offsets to CO2 storage by methane (CH4 ) production in mangrove sediments. The establishment of non-native Rhizophora mangle along Hawaiian coastlines over the last century offers an opportunity to examine the role mangroves play in climate mitigation and adaptation both globally and locally as novel ecosystems. We quantified total ecosystem C storage, sedimentation, accretion, sediment organic C burial and CH4 emissions from ~70 year old R. mangle stands and adjacent uninvaded mudflats. Ecosystem C stocks of mangrove stands exceeded mudflats by 434 ± 33 Mg C ha-1 , and mangrove establishment increased average coastal accretion by 460%. Sediment organic C burial increased 10-fold (to 4.5 Mg C ha-1 yr-1 ), double the global mean for old growth mangrove forests, suggesting that C accumulation from younger trees may occur faster than previously thought, with implications for mangrove restoration. Simulations indicate that increased CH4 emissions from sediments offset ecosystem CO2 storage by only 2-4%, equivalent to 30-60 Mg CO2 -eq ha-1 over mangrove lifetime (100-year sustained global warming potential). Results highlight the importance of mangroves as novel systems that can rapidly accumulate C, have a net positive atmospheric greenhouse gas removal effect, and support shoreline accretion rates that outpace current sea level rise. Sequestration potential of novel mangrove forests should be taken into account when considering their removal or management, especially in the context of climate mitigation goals.
While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.