Search

Atmospheric nitrogen (N) deposition is enriching soils with N across biomes. Soil N enrichment can increase plant productivity and affect microbial activity, thereby increasing soil organic carbon (SOC), but such responses vary across biomes. Drylands cover ~45% of Earth's land area and store ~33% of global SOC contained in the top 1 m of soil. Nitrogen fertilization could, therefore, disproportionately impact carbon (C) cycling, yet whether dryland SOC storage increases with N remains unclear. To understand how N enrichment may change SOC storage, we separated SOC into plant-derived, particulate organic C (POC), and largely microbially derived, mineral-associated organic C (MAOC) at four N deposition experimental sites in Southern California. Theory suggests that N enrichment increases the efficiency by which microbes build MAOC (C stabilization efficiency) if soil pH stays constant. But if soils acidify, a common response to N enrichment, then microbial biomass and enzymatic organic matter decay may decrease, increasing POC but not MAOC. We found that N enrichment had no effect on C fractions except for a decrease in MAOC at one site. Specifically, despite reported increases in plant biomass in three sites and decreases in microbial biomass and extracellular enzyme activities in two sites that acidified, POC did not increase. Furthermore, microbial C use and stabilization efficiency increased in a non-acidified site, but without increasing MAOC. Instead, MAOC decreased by 16% at one of the sites that acidified, likely because it lost 47% of the exchangeable calcium (Ca) relative to controls. Indeed, MAOC was strongly and positively affected by Ca, which directly and, through its positive effect on microbial biomass, explained 58% of variation in MAOC. Long-term effects of N fertilization on dryland SOC storage appear abiotic in nature, such that drylands where Ca-stabilization of SOC is prevalent and soils acidify, are most at risk for significant C loss.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

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.

Productivity and ecosystem carbon (C) storage are often positively associated with species and/or structural diversity; however, positive relationships in tropical forests and woodlands are not universal and the strength of this relationship may be affected by climate. Diversity-productivity relationships were evaluated in upland and seasonally flooded savanna (Cerrado) of the Cuiaba Basin and Northern Pantanal in southern Mato Grosso, Brazil. Data on wood C increment, tree species composition, and alpha diversity were measured over a 10-year period in nine communities located in the Cerrado-Pantanal transition zone. Communities were composed of a wide spectrum of tropical savanna physiognomies, including mixed grassland (campo sujo), typical wooded savanna (stricto sensu), dense wooded savanna (cerrado denso), seasonal forest (mata seca and mata ciliar), and riparian forest (mata de galeria). We hypothesized that tree species richness and diversity would increase from grassland to forest. We further hypothesized that there would be a positive relationship between woody C storage and diversity, but the strength of this relationship would be higher in wet years and wetter environments, such as the Pantanal, due to an increase in water availability. We found that tree species richness and diversity did not increase from mixed grasslands to forests, as mixed grasslands and riparian forests had similarly low levels of tree species richness and diversity compared to the other physiognomies. However, the rate of annual aboveground wood C increment was positively related to species richness and alpha diversity, and the positive relationship was primarily observed during wet years when the annual precipitation was at, or above, the long-term average for the region. Presumably, the impact of structural and species diversity on productivity declines during dry years when water availability becomes a more important control on stem C increment for tree species in the Cerrado-Pantanal transition. These data suggest that maintenance of diversity in these Cerrado woodlands and forests is important for maximizing aboveground C gain. However, climate change, which is causing warming and drying for the region, may limit the importance of diversity on wood C storage. [ABSTRACT FROM AUTHOR]

Author(s): Walter C. Oechel (corresponding author) [1]; George L. Vourlitis [2, 1]; Steven J. Hastings [1]; Rommel C. Zulueta [1]; Larry Hinzman [3]; Douglas Kane [3] Long-term sequestration of carbon [...]

1 Eddy covariance was used to measure landscape-scale fluxes of C[O.sub.2], [H.sub.2]O vapour and energy in moist-wet sedge tundra ecosystems of coastal arctic Alaska. 2 Net radiation ([R.sub.n]) was partitioned equally into sensible (H) and latent heat ([L.sub.e]), although a larger proportion of [R.sub.n] was partitioned into [L.sub.e] during and after the early season snow-melt period, while proportionally more [R.sub.n] was partitioned into H as the season progressed. Ground heat flux (G) comprised an average of 15% of [R.sub.n] throughout the growing season. 3 Interannual variation in evapotranspiration (ET) was negligible despite a 30% increase in total precipitation in 1995. On average, seasonal estimates of ET were 120 mm (1.3 mm [day.sup.-1]), which are similar to estimates found in the literature. 4 Net C[O.sub.2] influx generally peaked during the mid-day period when photosynthetic photon flux density (PPFD) was at a diurnal maximum, while peak net efflux occurred between 23.00 and 02.00 hours when PPFD was at a diurnal minimum. Most of the variation in diurnal net C[O.sub.2] exchange was explained by diurnal variations in PPFD, with the functional response best described as a rectangular hyperbola. 5 The coastal tundra landscapes were net sources of 0.02-0.05 mol [m.sup.-2] [day.sup.-1] during the early season snow-melt period. During the mid-season peak in productivity, which occurred as early as 10 July in 1994 and as late as 10 August in 1995, these landscapes were net sinks of on average 0.09 mol [m.sup.-2] [day.sup.-1]. Sink strength decreased considerably after the mid-season peak in productivity, presumably because of reductions in PPFD, an increase in water table depth, relatively high temperatures, and a decline in leaf area. 6 Over both growing seasons, the coastal tundra landscapes were sinks of 1.7 mol [m.sup.-2] This is comparable with the 'long-term' estimate of net C[O.sub.2] exchange calculated from the literature. Keywords: Arctic Alaska, ecophysiology, eddy covariance, net ecosystem exchange, wet-sedge tundra

Abstract. Regional estimates of arctic ecosystem [CO.sub.2] exchange are required because of the large soil carbon stocks located in arctic regions, the potentially large global-scale feedbacks associated with climate-change-induced alterations [...]

Although seasonal and temporal variations in evapotranspiration (ET) in Amazonia have been studied based upon flux-tower data and coarse resolution satellite-based models, ET dynamics over human-impacted landscapes are highly uncertain in this region. In this study, we estimate ET rates from critical land cover types over highly fragmented landscapes in the southern Amazon and characterize the ET dynamics during the dry season using the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC, a Landsat-based ET model, that generates spatially continuous ET estimates at a 30 m spatial resolution widely used for agricultural applications, was adapted to the southern Amazon by using the NDVI indexed reference ET fraction (ETrF) approach. Compared to flux tower-based ET rates, this approach showed an improved performance on the forest ET estimation over the standard METRIC approach, with R2 = 0.73 from R2 = 0.70 and RMSE reduced from 0.77 mm/day to 0.35 mm/day. We used this approach integrated into the METRIC procedure to estimate ET rates from primary, regenerated, and degraded forests and pasture in Acre, Rondônia, and Mato Grosso, all located in the southern Amazon, during the dry season in 2009. The lowest ET rates occurred in Mato Grosso, the driest region. Acre and Rondônia, both located in the southwestern Amazon, had similar ET rates for all land cover types. Dry season ET rates between primary forest and regenerated forest were similar (p > 0.05) in all sites, ranging between 2.5 and 3.4 mm/day for both forest cover types in the three sites. ET rates from degraded forest in Mato Grosso were significantly lower (p < 0.05) compared to the other forest cover types, with a value of 2.03 mm/day on average. Pasture showed the lowest ET rates during the dry season at all study sites, with the dry season average ET varying from 1.7 mm/day in Mato Grosso to 2.8 mm/day in Acre. [ABSTRACT FROM AUTHOR]