The Relevance of Maintaining Standing Forests for Global Climate Balance: A Case Study in Brazilian Forests

Estimate Net Ecosystem Exchange (NEE) is important to better understand carbon exchanges between terrestrial ecosystems and the atmosphere. Comprehend these dynamics is essential to better understand the responses of environments to ongoing climatic changes. This study aims to analyze, with AMERIFLUX and LBA network measurements, the variability of NEE and climate variables in four different tropical coverages: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, was estimate the Gross Primary Productivity (GPP). We found a distinct seasonality of meteorological variables and CO2 fluxes in each site. Despite acting mostly as a CO2 sink, some environments already show worrying source data in certain periods, pointed out as a direct effect of the reduction of photosynthesis caused by land use changes. The preserved forest plays an important role in maintaining rainfall at a regional and global level, and its maintenance makes it possible, by the way, an important tool in combating global warming via carbon sequestration by trees, which requires commitment and public policies of environmental preservation and recovery of degraded areas

Global carbon dioxide efflux from rivers enhanced by high nocturnal emissions

Carbon dioxide (CO2) emissions to the atmosphere from running waters are estimated to be four times greater than the total carbon (C) flux to the oceans. However, these fluxes remain poorly constrained because of substantial spatial and temporal variability in dissolved CO2 concentrations. Using a global compilation of high-frequency CO2 measurements, we demonstrate that nocturnal CO2 emissions are on average 27% (0.9 gC m−2 d−1) greater than those estimated from diurnal concentrations alone. Constraints on light availability due to canopy shading or water colour are the principal controls on observed diel (24 hour) variation, suggesting this nocturnal increase arises from daytime fixation of CO2 by photosynthesis. Because current global estimates of CO2 emissions to the atmosphere from running waters (0.65–1.8 PgC yr−1) rely primarily on discrete measurements of dissolved CO2 obtained during the day, they substantially underestimate the magnitude of this flux. Accounting for night-time CO2 emissions may elevate global estimates from running waters to the atmosphere by 0.20–0.55 PgC yr−1

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

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 similar to 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.Peer reviewe

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

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 halfhourly 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).Peer reviewe

Nitrogen and phosphorus pools and fluxes in upland and seasonally flooded forests and woodlands of the Cerrado-Pantanal transition of Brazil

Brazilian tropical savanna (referred to as Cerrado) has enormous structural variability ranging from tree- and shrub-free grasslands to tall, dense forests that are found in both well-drained upland and seasonally flooded (hyperseasonal) landforms. These structural and hydrological variations cause variations in aboveground carbon (C) storage, and presumably nitrogen (N) and phosphorus (P) storage and fluxes; however, the effects of these structural and hydrological variations on ecosystem N and P pools and fluxes are less well-known. Thus, our objective was to analyze N and P pools and fluxes for a spectrum of Cerrado physiognomies in both upland and hyperseasonal landforms. N and P pools and fluxes were compiled over an 8-10 year period in structurally different forms of Cerrado, including both upland and hyperseasonal grass dominated (campo sujo), typical wooded (sensu stricto) and dense wooded cerrado, and forested Cerrado stands located in the Cuiaba Basin and Northern Pantanal of southern Mato Grosso, Brazil. We found that aboveground N and P storage was generally higher in forested Cerrado than in non-forest landcover types, regardless of hydrology; however, these patterns were not consistent as wood N and P storage was just as high in typical- and dense-wooded savanna as in forested savannas. Wood typically made up the largest aboveground vegetation N and P reservoir, even for woody-grass savanna (campo sujo) which had a substantially lower tree density than wooded or forested savanna, followed by litter and roots, and then foliage. However, the vast majority of N and P was found in the upper 50 cm soil layer, accounting for 82-98% and 72-98% of the total ecosystem N and P, respectively, and even if only the 0-10 cm soil layer is considered, more than half of the ecosystem N and P was found in soil. Nutrient return via litter production was the largest flux followed by mineralization and root uptake, and nutrient cycling in litter production tended to be higher for forests than for wooded and woody-grass savannas. Savanna woodlands and forests in the Pantanal had higher N and P storage than comparable woodlands and forests in the Cuiaba Basin, presumably because of the shallower and stonier soils of the Cuiaba Basin. However, while the vegetation types studied here had large differences in structure (vegetation height, leaf area index, and density), the forested and wooded savannas had comparable belowground and wood N and P pools

Streams with Riparian Forest Buffers versus Impoundments Differ in Discharge and DOM Characteristics for Pasture Catchments in Southern Amazonia

Forest to pasture land use change following deforestation in Southern Amazonia can result in changes to stream water quality. However, some pasture streams have riparian forest buffers, while others are dammed for farm ponds. Stream corridor management can have differential effects on hydrology and dissolved organic matter (DOM) characteristics. We examined rainfall-runoff patterns and DOM characteristics in a pasture catchment with a forested riparian buffer, and an adjacent catchment with an impoundment. Total streamflow was 1.5 times higher with the riparian buffer, whereas stormflow represented 20% of total discharge for the dammed stream versus 13% with buffer. Stream corridor management was also the primary factor related to DOM characteristics. In the impounded catchment, DOM was found to be less structurally complex, with lower molecular weight compounds, a lesser degree of humification, and a larger proportion of protein-like DOM. In the catchment with a forested buffer, DOM was dominated by humic-like components, with fluorescence characteristics indicative of DOM derived from humified soil organic matter under native vegetation. Our results suggest that differences in stream corridor management can have important implications for carbon cycling in headwater pasture catchments, and that such changes may have the potential to influence water quality downstream in the Amazon basin.Science, Faculty ofNon UBCEarth, Ocean and Atmospheric Sciences, Department ofResources, Environment and Sustainability (IRES), Institute forReviewedFacult

WUE and CO₂ Estimations by Eddy Covariance and Remote Sensing in Different Tropical Biomes

The analysis of gross primary production (GPP) is crucial to better understand CO2 exchanges between terrestrial ecosystems and the atmosphere, while the quantification of water-use efficiency (WUE) allows for the estimation of the compensation between carbon gained and water lost by the ecosystem. Understanding these dynamics is essential to better comprehend the responses of environments to ongoing climatic changes. The objective of the present study was to analyze, through AMERIFLUX and LBA network measurements, the variability of GPP and WUE in four distinct tropical biomes in Brazil: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, data measured by eddy covariance systems were used to assess remotely sensed GPP products (MOD17). We found a distinct seasonality of meteorological variables and energy fluxes with different latent heat controls regarding available energy in each site. Remotely sensed GPP was satisfactorily related with observed data, despite weak correlations in interannual estimates and consistent overestimations and underestimations during certain months. WUE was strongly dependent on water availability, with values of 0.95 gC kg−1 H2O (5.79 gC kg−1 H2O) in the wetter (drier) sites. These values reveal new thresholds that had not been previously reported in the literature. Our findings have crucial implications for ecosystem management and the design of climate policies regarding the conservation of tropical biomes, since WUE is expected to change in the ongoing climate change scenario that indicates an increase in frequency and severity of dry periods

Transpiração pelo método da sonda de dissipação térmica em floresta de transição Amazônica-Cerrado

Com este trabalho objetivou-se analisar o comportamento do fluxo de seiva em espécies da floresta de transição Amazônia Cerrado e caracterizar a dependência do fluxo de seiva, em função do déficit de pressão de vapor da atmosfera (DPV). O fluxo de seiva foi medido utilizando-se sondas de dissipação térmica em 5 espécies diferentes. Os dados foram divididos em quatro estações. No período experimental as curvas de variação sazonal do fluxo de seiva evidenciam a ocorrência de picos no período úmido. Esta tendência sazonal do fluxo de seiva foi evidenciada pela relação entre valores diários de transpiração e do DPV. O valor limite do DPV nessas estações foi de 1 a 1,5 kPa. Com referência ao fluxo de seiva como representativo da taxa transpiratória das plantas, a redução do fluxo no período seco não confirma a hipótese da manutenção do processo de evapotranspiração. O fluxo de seiva nas espécies do estudo é influenciado mais pelas condições atmosféricas do que mesmo pela disponibilidade de água no solo, o que suscita um possível armazenamento da água no caule nos períodos mais secos quando a área foliar diminui mas a taxa transpiratória não é significativamente distinta daquela do período chuvoso