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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.

Deforestation and climate change have the capacity to alter rainfall regimes, water availability, and surface-atmosphere flux of water and energy of tropical forests, especially in ecotonal, semi-deciduous tropical forests of the southern Amazon Basin, which have experienced rapid regional warming and deforestation over the last three decades. To reduce uncertainty regarding current and future energy and water flux, micrometeorological measurements of latent ( Qe) and sensible heat flux ( Qh) and canopy conductance ( Gc) were combined with measurements of sap flux density ( Fd) and maximum leaf conductance ( gsmax) to characterize the seasonal controls on mass (H2O) and energy exchange of an ecotonal, semi-deciduous forest in northern Mato Grosso, Brazil over the 2005-2006 annual cycle. Average diel patterns and daily rates of energy flux and conductance declined during the dry season; however, the decline in Fd and Qe was smaller and/or more gradual than Gc and gsmax. Weekly averages of transpiration calculated from sap flow measurements during the dry-wet season transition period were positively correlated (r2 = 0.47; p < 0.05; n = 11) with estimates of leaf area index (LAI) derived from the Modis-Aqua satellite platform while estimates of evapotranspiration ET derived from eddy covariance were not, presumably because these estimates also include an evaporation component. Overall, our results suggest that access to deep water reserves can support high rates of Fd and Qe during the dry season, but because of high evaporative demand, declines in plant water potential lead to a corresponding decline in Gc. Furthermore, seasonal variations in LAI, that are likely to be controlled in part by plant water status and phenology, constrain tree and stand transpiration. Thus the consistency of Qe over the annual cycle appears to be the result of trade-offs between water availability (rainfall, soil moisture, water potential), canopy structural properties (LAI), and meteorological conditions including vapor pressure deficit and net radiation. [ABSTRACT FROM AUTHOR]

This research utilized tower-based eddy covariance to quantify the trends in net ecosystem mass (CO2 and H2O vapor) and energy exchange of important land-cover types of NW Mato Grosso during the March-December 2002 seasonal transition. Measurements were made in a mature transitional (ecotonal) tropical forest near Sinop, Mato Grosso, and a cattle pasture near Cotriguaçú Mato Grosso, located 500km WNW of Sinop. Pasture net ecosystem CO2 exchange (NEE) was considerably more variable than the forest NEE over the seasonal transition, and the pasture had significantly higher rates of maximum gross primary production in every season except the dry-wet season transition (September-October). The pasture also had significantly higher rates of whole-ecosystem dark respiration than the forest during the wetter times of the year. Average (±95% CI) rates of total daily NEE during the March-December 2002 measurement period were 26±15 mmol m-2day-1 for the forest (positive values indicate net CO2 loss by the ecosystem) and -38±26mmol m-2 day-1 for the pasture. While both ecosystems partitioned more net radiation ( Rn) into latent heat flux ( Le), the forest had significantly higher rates of Le and lower rates of sensible heat flux ( H) than the pasture; a trend that became more extreme during the onset of the dry season. Large differences in pasture and forest mass and energy exchange occurred even though seasonal variations in micrometeorology (air temperature, humidity, and radiation) were relatively similar for both ecosystems. While the short measurement period and lack of spatial replication limit the ability to generalize these results to pasture and forest regions of the Amazon Basin, these results suggest important differences in the magnitude and seasonal variation of NEE and energy partitioning for pasture and transitional tropical forest. [ABSTRACT FROM AUTHOR]

Abstract The spatial and temporal patterns in CO2 flux for the Kuparuk River Basin, a 9200-km2 watershed located in NE Alaska were estimated using the Regional Arctic CO2 Exchange Simulator (RACES) for the 1994–1995 growing seasons. RACES uses non-linear models and a Geographical Information System database (GIS) consisting of the normalized difference vegetation index (NDVI) and dynamic temperature and radiation maps. The spatial and temporal patterns in the NDVI during both growing seasons suggest that ecosystem development occurred 2–4 weeks earlier and was relatively more rapid in the southern portion of the Kuparuk River Basin. Rates of gross primary production (GPP) and whole-ecosystem respiration (R) were 2–4 fold higher in the southern basin than along the arctic coastal plain depending on time of year. The higher rate of GPP estimated for the southern basin was primarily due to higher NDVI values, while the higher R estimated for the southern basin was due in part to higher temperature and the NDVI. While GPP and R showed strong latitudinal trends, spatial and temporal trends in net ecosystem CO2 exchange (NEE) were much more variable. Thus, while spatial trends in carbon gain (GPP) and loss (R) were highly correlated, small spatial and temporal differences in these large fluxes (GPP and/or R) lead to corresponding large spatial variations in the NEE. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to physiological models for the measurement of carbon dioxide flux in arctic Tundra Landscape. Topics discussed include requirement of arctic ecosystem carbon dioxide in exchange soil carbon, impact of climatic changes on arctic ecosystem, and use of gross primary production (GPP), whole-ecosystem respiration (R) and air temperature for photosynthetic photon flux density.

• In-situ observation energy fluxes in a Pantanal scrub-forest using eddy covariance. • The largest portion of Rn was mainly consumed by LE even in the dry season. • The Ω suggests that the canopy is decoupled from the atmosphere. • ET exhibited a strong relationship with biotic factors such as EVI. Brazilian Pantanal is the largest seasonal wetland in the world and it plays an important role in regulating the local and global water cycle and energy balance. The Pantanal landscape consists of a mosaic of temporary and permanent aquatic habitats, floodable and non-floodable pastures, and forests; however, patterns of energy exchange are poorly understood, especially for seasonally flooded forests. Thus, the main objective of this research was to assess the variability of evapotranspiration (ET) and to evaluate biophysical controls on ET for a seasonally flooded scrub-forest. We used eddy covariance to measure latent (LE) and sensible (H) heat fluxes and linked both micrometeorological and remote sensing data to assess the connection between water dynamics and phenology. Our data suggest that 72% of the net radiation (Rn) was consumed by LE + H , even during the dry season, indicating that trees can access deep water when surface water is limiting. The decoupling factor (0.63 ± 0.08) suggests that the canopy is decoupled from the atmosphere and ET is essentially sensitive to Rn. The patterns of ET and vapor pressure deficit suggest that ET was more dependent on the Rn received and less dependent on stomatal control, but still exhibited a strong relationship with biotic factors such as enhanced vegetation index (EVI), which is sensitive to seasonal variations in leaf area index and canopy cover. Stomatal limitations of this seasonally flooded forest appear to be minimal, even in the dry season, presumably due to the relatively high-water table, the ability of trees to acquire subsurface water, and the predominance of secondary species with high rates of leaf gas exchange. These data indicate that seasonally flooded tropical forests of the Pantanal are consistent sources of water vapor to the atmosphere even during seasonal drought. [ABSTRACT FROM AUTHOR]

• 25 different ET o methods were evaluated for the Cerrado condition. • Radiation-based methods are applicable in the Cerrado region when Penman-Monteith model inputs are not available. • Our GA generated equation using solar radiation and temperature as inputs showed good overall results. The Brazilian savanna, locally known as Cerrado, native vegetation has been replaced by an agro-pastoral land cover over the last few decades, which has affected its hydrological cycle and the availability of its water resources. Reference evapotranspiration (ET o) estimates are an important tool for water resources managements because they estimate the potential for atmospheric water loss. The Penman-Monteith method (FAO-PM) is recommended by FAO due to its consistent results in different regions and climates, but it requires a high data demand. Several empirical ET o methods with less inputs have been tested around the world, and machine learning approaches have been studied in the recent years. Therefore, in the present paper, 21 empirical methods, classified as mass transfer-based, radiation-based, temperature-based, or combination methods, and 4 equations generated by genetic algorithm (GA) were evaluated against the FAO-PM method. Radiation-based methods were more accurate than the others, especially De Bruin-Keijman and Priestley-Taylor methods, which were the two models with best performance. Mass transfer-based and temperature-based models were deemed unsuitable due to their high errors and low correlation when compared to the other ET o methods. Among the combination methods, the Copais method showed the fifth best result from all the empirical equations tested. The GA equations were generated based on our results, considering the mass transfer-based and temperature-based models, however only one equation, using air temperature and solar radiation as inputs, presented a performance as good as the best methods found in our study. Therefore, alternatives empirical equations and GA approach could meet ET o estimates similar to the FAO-PM method using less inputs. [ABSTRACT FROM AUTHOR]