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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.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Global modeling efforts indicate semiarid regions dominate the increasing trend and interannual variation of net CO2 exchange with the atmosphere, mainly driven by water availability. Many semiarid regions are expected to undergo climatic drying, but the impacts on net CO2 exchange are poorly understood due to limited semiarid flux observations. Here we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (photosynthesis and respiration), precipitation, and evapotranspiration (ET) in 21 semiarid North American ecosystems with an observed range of 100 - 1000 mm in annual precipitation and records of 4-9 years each. In addition to evaluating spatial relationships among CO2 and water fluxes across sites, we separately quantified site-level temporal relationships, representing sensitivity to interannual variation. Across the climatic and ecological gradient, photosynthesis showed a saturating spatial relationship to precipitation, whereas the photosynthesis-ET relationship was linear, suggesting ET was a better proxy for water available to drive CO2 exchanges after hydrologic losses. Both photosynthesis and respiration showed similar site-level sensitivity to interannual changes in ET among the 21 ecosystems. Furthermore, these temporal relationships were not different from the spatial relationships of long-term mean CO2 exchanges with climatic ET. Consequently, a hypothetical 100-mm change in ET, whether short term or long term, was predicted to alter net ecosystem production (NEP) by 64 gCm(-2) yr(-1). Most of the unexplained NEP variability was related to persistent, site-specific function, suggesting prioritization of research on slow-changing controls. Common temporal and spatial sensitivity to water availability increases our confidence that site-level responses to interannual weather can be extrapolated for prediction of CO2 exchanges over decadal and longer timescales relevant to societal response to climate change.

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The exchange of multiple greenhouse gases (i.e., CO2 and CH4) between tree stems and the atmosphere represents a knowledge gap in the global carbon cycle. Stem CO2 and CH4 fluxes vary across time and space and are unclear, which are their individual or shared drivers. Here we measured CO2 and CH4 fluxes at different stem heights combining manual (biweekly; n = 678) and automated (hourly; n > 38,000) measurements in a temperate upland forest. All trees showed CO2 and CH4 emissions despite 20% of measurements showing net CH4 uptake. Stem CO2 fluxes presented clear seasonal trends from manual and automated measurements. Only automated measurements captured the high temporal variability of stem CH4 fluxes revealing clear seasonal trends. Despite that temporal integration, the limited number of automated chambers made stand‐level mean CH4 fluxes sensitive to "hot spots," resulting in mean fluxes with high uncertainty. Manual measurements provided better integration of spatial variability, but their lack of temporal variability integration hindered the detection of temporal trends and stand‐level mean fluxes. These results highlight the potential bias of previous studies of stem CH4 fluxes solely based on manual or automated measurements. Stem height, temperature, and soil moisture only explained 7% and 11% of the stem CH4 flux variability compared to 42% and 81% for CO2 (manual and automated measurements, respectively). This large unexplained variability, in combination with high CH4 concentrations in the trees' heartwood, suggests that stem CH4 fluxes might be more influenced by gas transport and diffusivity through the wood than by drivers of respiratory CO2 flux, which has crucial implications for developing process‐based ecosystem models. We postulate that CH4 is likely originated within tree stems because of lack of a consistent vertical pattern in CH4 fluxes, evidence of CH4 production in wood incubations, and low CH4 concentration in the soil profile but high concentrations within the trees' heartwood. [ABSTRACT FROM AUTHOR]

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such analyses are poorly constrained by measured CO2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production ( NEP) varying from -350 to +330 gCm−2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production ( GEP), and ecosystem respiration (Reco) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration ( ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and Reco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO2 exchange may be up to 3-5 times larger than current estimates. [ABSTRACT FROM AUTHOR]

Climate models suggest that extreme rainfall events will become more common with increased atmospheric warming. Consequently, changes in the size and frequency of rainfall will influence biophysical drivers that regulate the strength and timing of soil CO2 efflux - a major source of terrestrial carbon flux. We used a rainfall manipulation experiment during the summer monsoon season ( July- September) to vary both the size and frequency of precipitation in an arid grassland 2 years before and 2 years after a lightning-caused wildfire. Soil CO2 efflux rates were always higher under increased rainfall event size than under increased rainfall event frequency, or ambient precipitation. Although fire reduced soil CO2 efflux rates by nearly 70%, the overall responses to rainfall variability were consistent before and after the fire. The overall sensitivity of soil CO2 efflux to temperature ( Q10) converged to 1.4, but this value differed somewhat among treatments especially before the fire. Changes in rainfall patterns resulted in differences in the periodicity of soil CO2 efflux with strong signals at 1, 8, and 30 days. Increased rainfall event size enhanced the synchrony between photosynthetically active radiation and soil CO2 efflux over the growing season before and after fire, suggesting a change in the temporal availability of substrate pools that regulate the temporal dynamics and magnitude of soil CO2 efflux. We conclude that arid grasslands are capable of rapidly increasing and maintaining high soil CO2 efflux rates in response to increased rainfall event size more than increased rainfall event frequency both before and after a fire. Therefore, the amount and pattern of multiple rain pulses over the growing season are crucial for understanding CO2 dynamics in burned and unburned water-limited ecosystems. [ABSTRACT FROM AUTHOR]

Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water-limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20 mm rain event each month, and (3) ambient rain plus four 5 mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content ( θ), soil respiration ( R), along with leaf-level photosynthesis ( A), predawn leaf water potential (Ψ), and seasonal aboveground net primary productivity (ANPP) of the dominant C grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil θ which corresponded with a significant increase in R and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle. [ABSTRACT FROM AUTHOR]

Ecosystem processes are influenced by weather and climatic perturbations at multiple temporal scales with a large range of amplitudes and phases. Technological advances of automated biometeorological measurements provide the opportunity to apply spectral methods on continuous time series to identify differences in amplitudes and phases and relationships with weather variation. Here we used wavelet coherence analysis to study the temporal covariance between soil CO2 production and soil temperature, soil moisture, and photosynthetically active radiation (PAR). Continuous (hourly average) data were acquired over 2 years among three vegetation types in a semiarid mixed temperate forest. We showed that soil temperature and soil moisture influence soil CO2 production differently at multiple periods (e.g. hours, days, weeks, months, years), especially after rain pulse events. Our results provide information about the periodicity of soil CO2 production among vegetation types, and provide insights about processes controlling CO2 production through the study of phase relationships between two time series (e.g. soil CO2 production and PAR). We tested the performance of empirical models of soil CO2 production using the continuous wavelet transform. These models, built around soil temperature and moisture, failed at multiple periods across the measured dates, suggesting that empirical models should include other factors that regulate soil CO2 production at different temporal scales. Our results add a new dimension for the analysis of continuous time series of biometeorological measurements and model testing, which will prove useful for analysis of increasing sensor data obtained by environmental networks. [ABSTRACT FROM AUTHOR]

Seasonally dry tropical forests (SDTF) are a widely distributed vegetation type in the tropics, characterized by seasonal rainfall with several months of drought when they are subject to fire. This study is one of the first attempts to quantify above- and belowground biomass (AGB and BGB) and above- and belowground carbon (AGC and BGC) pools to calculate their recovery after fire, using a chronosequence approach (six forests that ranged form 1 to 29 years after fire and mature forest). We quantified AGB and AGC pools of trees, lianas, palms, and seedlings, and BGB and BGC pools (Oi, Oe, Oa soil horizons, and fine roots). Total AGC ranged from 0.05 to nearly 72 Mg C ha−1, BGC from 21.6 to nearly 85 Mg C ha−1, and total ecosystem carbon from 21.7 to 153.5 Mg C ha−1; all these pools increased with forest age. Nearly 50% of the total ecosystem carbon was stored in the Oa horizon of mature forests, and up to 90% was stored in the Oa-horizon of early successional SDTF stands. The soils were shallow with a depth of <20 cm at the study site. To recover values similar to mature forests, BGC and BGB required <19 years with accumulation rates greater than 20 Mg C ha−1 yr−1, while AGB required 80 years with accumulation rates nearly 2.5 Mg C ha−1 yr−1. Total ecosystem biomass and carbon required 70 and 50 years, respectively, to recover values similar to mature forests. When belowground pools are not included in the calculation of total ecosystem biomass or carbon recovery, we estimated an overestimation of 10 and 30 years, respectively. [ABSTRACT FROM AUTHOR]