Search

stage of the vegetation determines the radiative budget, energy balance partitioning, evapotranspiration and carbon dioxide flux. Here, we synthesize energy balance measurements from across the western boreal zone of North America as a function of stand age following fire. The data are from 22 sites in Alaska, Saskatchewan and Manitoba collected between 1998 and 2004 for a 150-year forest chronosequence. The summertime albedo immediately after a fire is about 0.05, increasing to about 0.12 for a period of about 30 years and then averaging about 0.08 for mature coniferous forests. A mature deciduous (aspen) forest has a higher summer albedo of about 0.16. Wintertime albedo decreases from a high of 0.7 for 5- to 30-year-old forests to about 0.2 for mature forests (deciduous and coniferous). Summer net radiation normalized to incoming solar radiation is lower in successional forests than in more mature forests by about 10%, except for the first 1–3 years after fire. This reduction in net radiative forcing is about 12–24 W m−2 as a daily average in summer (July). The summertime daily Bowen ratio exceeds 2 immediately after the fire, decreasing to about 0.5 for 15-year-old forests, with a wide range of 0.3–2 for mature forests depending on the forest type and soil water status. The magnitude of these changes is relatively large and may affect local, regional and perhaps global climates. Although fire has always determined stand renewal in these forests, increased future area burned could further alter the radiation balance and energy partitioning, causing a cooling feedback to counteract possible warming from carbon dioxide released by boreal fires.

The Brazilian Pampa biome has natural pastures that have been used for centuries for cattle grazing. This is considered a sustainable system because it combines the conservation of natural vegetation and high-quality meat production, protecting the biome from commercial agriculture's advances. However, whether it is a source or a sink of carbon dioxide (CO2) has yet to be evaluated. Hence, this study aimed to quantify the net ecosystem exchange (NEE) of the CO2 of a natural pasture of the Pampa biome used for livestock production. The experimental area is located in a subtropical region of southern Brazil, where eddy covariance (EC) measurements were conducted from 2015 to 2021 in a rotational cattle grazing system. The seven months of the warm season (September to March) were characterized as CO2 absorbers, while the five months of the cold season (April to August) were CO2 emitters. Throughout the six years and with complete data, the ecosystem was an absorber of atmospheric CO2, with an average value of −207.6 g C m−2 year−1. However, the significant interannual variability in NEE was observed, with cumulative values ranging from −82.0 to −385.3 g C m−2 year−1. The results suggest the coupling of climatic conditions to pasture management can be the factor that modulated the NEE interannual variability. The cattle raising system on the natural pastures of the Pampa absorbs CO2, which is further evidence of its sustainability and need for conservation. [ABSTRACT FROM AUTHOR]

Climate extremes and anomalies modify the CO2 ecosystem–atmosphere exchange of the boreal forests and consequently alter the terrestrial carbon stocks and the atmospheric greenhouse gas concentrations. The effects of the anomalous weather conditions on the CO2 net ecosystem exchange (NEE), total ecosystem respiration (TER), and gross primary production (GPP) of the typical southern taiga nemorose spruce forest were analyzed using continuous eddy covariance flux measurements in the 2015–2020 period. The forest was found to be a source of atmospheric CO2 in 2016, 2017, 2019, and 2020 (the mean annual GPP/TER ratio was between 0.87 and 0.97). In 2018, the forest was found to act as a CO2 sink (GPP/TER = 1.47) when a positive temperature anomaly in the growing season was accompanied by a negative precipitation anomaly and increased global radiation. The early start of the CO2 uptake in the anomalously warm winter of 2019/2020 did not result in an increase in the annual GPP/TER ratio (0.90). The comparison of the flux data obtained from the nemorose spruce forest on the well-drained soils with the data obtained from paludified spruce forest in the same landscape showed that the mean annual GPP/TER ratio of the sites alternatively responded to the mentioned anomalies. This study suggests that a variety of soil moisture regimes across the southern taiga spruce forests provide a non-uniformity in the response reactions of the CO2 ecosystem–atmosphere exchange on the climate anomalies. [ABSTRACT FROM AUTHOR]

Evapotranspiration is a key variable of the hydrological cycle but poorly studied in Alpine ecosystems. The current study aimed to characterise the impact of topography and temporal variability on actual evapotranspiration (ETa) and its environmental drivers at an Alpine abandoned grassland encroached by shrubs on a steep slope. Eddy covariance, meteorological, hydrological and soil data were analysed over four growing seasons, of which two had wet and two dry conditions. The topography caused a systematic morning inflexion of ETa in all growing seasons, reflecting the valley wind system. Inter-annual differences of ETa exceeded 100 mm, and ETa means and cumulative values were significantly different between wet and dry growing seasons in the four years. Besides, ETa had a larger temporal variability in wet growing seasons. A bimodality of ETa was found in all years, caused by the onset of plant activity in the morning hours. Energy- and water-limited ETa periods were identified by comparing ETa to potential evapotranspiration (ETo). Periods of fifteen days revealed the main intra- and inter-annual differences of the environmental variables (air temperature, vapour pressure deficit—VPD, precipitation and ETa). The fixed effects of a linear mixed model based on ETa drivers explained 56% of ETa variance. The most important ETa drivers were net radiation and VPD, followed by wind speed. In growing seasons characterised by dry conditions, air temperature and the ground heat flux at the surface (either both or one of them) influenced ETa as well. The current study contributed to the understanding of topographical and temporal effects on evapotranspiration and other micrometeorological variables in an Alpine ecosystem still rarely studied. [ABSTRACT FROM AUTHOR]

Approximating the complex nonlinear relationships that dominate the exchange of carbon dioxide fluxes between the biosphere and atmosphere is fundamentally important for addressing the issue of climate change. The progress of machine learning techniques has offered a number of useful tools for the scientific community aiming to gain new insights into the temporal and spatial variation of different carbon fluxes in terrestrial ecosystems. In this study, adaptive neuro-fuzzy inference system (ANFIS) and generalized regression neural network (GRNN) models were developed to predict the daily carbon fluxes in three boreal forest ecosystems based on eddy covariance (EC) measurements. Moreover, a comparison was made between the modeled values derived from these models and those of traditional artificial neural network (ANN) and support vector machine (SVM) models. These models were also compared with multiple linear regression (MLR). Several statistical indicators, including coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), bias error (Bias) and root mean square error (RMSE) were utilized to evaluate the performance of the applied models. The results showed that the developed machine learning models were able to account for the most variance in the carbon fluxes at both daily and hourly time scales in the three stands and they consistently and substantially outperformed the MLR model for both daily and hourly carbon flux estimates. It was demonstrated that the ANFIS and ANN models provided similar estimates in the testing period with an approximate value of R² = 0.93, NSE = 0.91, Bias = 0.11 g C m-2 day-1 and RMSE = 1.04 g C m-2 day-1 for daily gross primary productivity, 0.94, 0.82, 0.24 g C m-2 day-1 and 0.72 g C m-2 day-1 for daily ecosystem respiration, and 0.79, 0.75, 0.14 g C m-2 day-1 and 0.89 g C m-2 day-1 for daily net ecosystem exchange, and slightly outperformed the GRNN and SVM models. In practical terms, however, the newly developed models (ANFIS and GRNN) are more robust and flexible, and have less parameters needed for selection and optimization in comparison with traditional ANN and SVM models. Consequently, they can be used as valuable tools to estimate forest carbon fluxes and fill the missing carbon flux data during the long-term EC measurements. [ABSTRACT FROM AUTHOR]

Investigating the energy and water vapor exchange in oasis riparian forest ecosystems is of significant importance to improve scientific understanding of land surface processes in extreme arid regions. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) provided many observations of water vapor and heat fluxes from riparian forest ecosystem by using a network of eddy-covariance (EC) systems installed over representative surfaces in the Ejina Oasis, which is located in the downstream areas of the Heihe River Basin, northwestern China. Based on EC flux measurements and meteorological data performed at five stations and covering representative surface types of Populus euphratica tree with associated Tamarix chinensis shrub, Tamarix chinensis shrubland, cantaloupe cropland, and barren-land, this study explored the spatio-temporal patterns of heat and water vapor fluxes over the Ejina Oasis riparian forest ecosystem with five different surface types over the course of a growing season in 2014. Energy balance closure of the flux data was evaluated; footprint analysis for each EC site was also performed. Results showed that energy balance closure for the flux data was reasonably good, with average energy balance ratio (EBR) of 1.03. The seasonal variations in net radiation (Rn), latent (LE), and sensible heat flux (H) over the five contrasting surfaces were similar, and a reverse seasonal change was observed in energy partitioning into LE and H. Remarkable differences in Rn, LE, and H between the five surfaces were explored preliminarily, associated closely with the soil properties and foliage phenology. Over the growing season (May–October) in 2014, the total ET ranged 622–731 mm for mixed forest of P. euphratica trees with associated T. chinensis shrubs with average daily ET of 3.6–4.2 mm; ET from T. chinensis shrubland was about 541 mm, with average daily ET of 3.6 mm. ET for barren-land was 195 mm. The total ET in irrigated cantaloupe cropland with plastic mulch was 431 mm for its four-month growing period with a total average of 3.8 mm d−1. Determination of ET over riparian forest ecosystem helps to improve reasonable use of limited water resource in the Ejina Oasis. [ABSTRACT FROM AUTHOR]

Knowledge about the dynamics and biophysical controlling mechanism of nocturnal evapotranspiration (ETN) in desert-dwelling shrub ecosystem is still lacking. Using the eddy covariance measurements of latent heat flux in a dried shrubland in northwest China, we examined the dynamics of ETN and its biophysical controls at multiple timescales during growing-seasons from 2012 to 2014. The ETN was larger in the mid-growing season (usually in mid-summer) than in spring and autumn. The maximum daily ETN was 0.21, 0.17, and 0.14 mm night−1 in years 2012–2014, respectively. At the diel scale, ETN decreased from 21:00 to 5:00, then began to increase. ETN were mainly controlled by soil volumetric water content at 30 cm depth (VWC30), by vapor pressure deficit (VPD) and normalized difference vegetation index (NDVI) at leaf expanding and expanded stage, and by air temperature (Ta) and wind speed (Ws) at the leaf coloring stage. At the seasonal scale, variations of ETN were mainly driven by Ta, VPD, and VWC10. Averaged annual ETN was 4% of daytime ET. The summer drought in 2013 and the spring drought in 2014 caused the decline of daily evapotranspiration (ET). The present results demonstrated that ETN is a significant part of the water cycle and needs to be seriously considered in ET and related studies. The findings here can help with the sustainable management of water in desert ecosystems undergoing climate change. [ABSTRACT FROM AUTHOR]

Climate change impacts the characteristics of the vegetation carbon-uptake process in the northern Eurasian terrestrial ecosystem. However, the currently available direct CO2 flux measurement datasets, particularly for central Siberia, are insufficient for understanding the current condition in the northern Eurasian carbon cycle. Here, we report daily and seasonal interannual variations in CO2 fluxes and associated abiotic factors measured using eddy covariance in a coniferous forest and a bog near Zotino, Krasnoyarsk Krai, Russia, for April to early June, 2013–2017. Despite the snow not being completely melted, both ecosystems became weak net CO2 sinks if the air temperature was warm enough for photosynthesis. The forest became a net CO2 sink 7–16 days earlier than the bog. After the surface soil temperature exceeded ~1 °C, the ecosystems became persistent net CO2 sinks. Net ecosystem productivity was highest in 2015 for both ecosystems because of the anomalously high air temperature in May compared with other years. Our findings demonstrate that long-term monitoring of flux measurements at the site level, particularly during winter and its transition to spring, is essential for understanding the responses of the northern Eurasian ecosystem to spring warming. [ABSTRACT FROM AUTHOR]

Despite the critical role latent (LE) and sensible (H) heat play in turbulent processes and heat exchange in the water–air interface, there is a lack of studies of turbulent fluxes over the surface in semiarid regions. We collected continuous measurements of net radiation (Rn), LE, H, and micrometeorological data at a coastal lagoon in the Gulf of California during 2019 with an eddy covariance (EC) system. We analyzed the time series, considering the North American Monsoon System, the pre-monsoon, and post-monsoon season. Results show that Rn (276 ± 118 W m−2) and turbulent fluxes were higher during the monsoon season (July–September) LE (129 ± 18 W m−2), and H (29 ± 9 W m−2). The monthly average of Rn, LE, and H was highest in June (493.9 W m−2), August (142 W m−2), and May (50 W m−2), respectively. Furthermore, during the monsoon season, the (H + LE)/Rn ratio (0.74) suggests that more than half of the Rn reaching the coastal lagoon is used for the turbulent exchange of LE and H. During the pre-monsoon, LE (r2 = 0.36) increases with a higher vapor pressure deficit (VPD), while H (r2 = 0.66) increases with a higher friction velocity (u*) during the monsoon season. Quantitative observations are essential for further research. [ABSTRACT FROM AUTHOR]

A large area of Estonian hemiboreal forest is recovering from clear-cut harvesting and changing carbon (C) balance of the stands. However, there is a lack of information about C- source/sink relationships during recovery of such stands. The eddy covariance technique was used to estimate C-status through net ecosystem exchange (NEE) of CO2 in two stands of different development stages located in southeast Estonia in 2014. Measured summertime (June–September) mean CO2 concentration was 337.75 ppm with mean NEE −1.72 µmol m−2 s−1. June NEE was −4.60 µmol m−2 s−1; July, August, and September NEE was −1.17, −0.77, and −0.25 µmol m−2 s−1, respectively. The two stands had similar patterns of CO2 exchange; measurement period temperature drove NEE. Our results show that after clear-cutting a 6-year-old forest ecosystem was a light C-sink and 8-year-old young stand demonstrated a stronger C-sink status during the measurement period. [ABSTRACT FROM AUTHOR]

Global retrieval of solar-induced chlorophyll fluorescence (SIF) using remote sensing by means of satellites has been developed rapidly in recent years. Exploring how SIF could improve the characterization of photosynthesis and its role in the land surface carbon cycle has gradually become a very important and active area. However, compared with other gross primary production (GPP) models, the robustness of the parameterization of the SIF model under different circumstances has rarely been investigated. In this study, we examined and compared the effects of temporal aggregation and meteorological conditions on the stability of model parameters for the SIF model ( ε / S I F yield ), the one-leaf light-use efficiency (SL-LUE) model ( ε max ), and the two-leaf LUE (TL-LUE) model ( ε msu and ε msh ). The three models were parameterized based on a maize–wheat rotation eddy-covariance flux tower data in Yucheng, Shandong Province, China by using the Metropolis–Hasting algorithm. The results showed that the values of the ε / S I F yield and ε max were similarly robust and considerably more stable than ε msu and ε msh for all temporal aggregation levels. Under different meteorological conditions, all the parameters showed a certain degree of fluctuation and were most affected at the mid-day scale, followed by the monthly scale and finally at the daily scale. Nonetheless, the averaged coefficient of variation ( C V ) of ε / S I F yield was relatively small (15.0%) and was obviously lower than ε max ( C V = 27.0%), ε msu ( C V = 43.2%), and ε msh ( C V = 53.1%). Furthermore, the SIF model's performance for estimating GPP was better than that of the SL-LUE model and was comparable to that of the TL-LUE model. This study indicates that, compared with the LUE-based models, the SIF-based model without climate-dependence is a good predictor of GPP and its parameter is more likely to converge for different temporal aggregation levels and under varying environmental restrictions in croplands. We suggest that more flux tower data should be used for further validation of parameter convergence in other vegetation types. [ABSTRACT FROM AUTHOR]

Experimentally characterizing evapotranspiration (ET) in different biomes around the world is an issue of interest for different areas of science. ET in natural areas of the Brazilian Pampa biome has still not been assessed. In this study, the actual ET (ETact) obtained from eddy covariance measurements over two sites of the Pampa biome was analyzed. The objective was to evaluate the energy partition and seasonal variability of the actual ET of the Pampa biome. Results showed that the latent heat flux was the dominant component in available energy in both the autumn–winter (AW) and spring–summer (SS) periods. Evapotranspiration of the Pampa biome showed strong seasonality, with highest ET rates in the SS period. During the study period, approximately 65% of the net radiation was used for the evapotranspiration process in the Pampa biome. The annual mean ET rate was 2.45 mm d−1. ET did not show to vary significantly between sites, with daily values very similar in both sites. The water availability in the Pampa biome was not a limiting factor for ET, which resulted in a small difference between the reference ET and the actual ET. These results are helpful in achieving a better understanding of the temporal pattern of ET in relation to the landscape of the Pampa biome and its meteorological, soil, and vegetation characteristics. [ABSTRACT FROM AUTHOR]

Commercially available autonomous photochemical reflectance index (PRI) sensors are a new development in the remote sensing field that offer novel opportunities for a deeper exploration of vegetation physiology dynamics. In this study, we evaluated the reliability of autonomous PRI sensors (SRS-PRI) developed by METER Group Inc. as proxies of light use efficiency (LUE) in an aspen (Populus tremuloides) forest stand. Before comparisons between PRI and LUE measurements were made, the optical SRS-PRI sensor pairs required calibrations to resolve diurnal and seasonal patterns properly. An offline diurnal calibration procedure was shown to account for variable sky conditions and diurnal illumination changes affecting sensor response. Eddy covariance measurements provided seasonal gross primary productivity (GPP) measures as well as apparent canopy quantum yield dynamics (α). LUE was derived from the ratio of GPP to absorbed photosynthetically active radiation (APAR). Corrected PRI values were derived after diurnal and midday cross-calibration of the sensor's 532 nm and 570 nm fore-optics, and closely related to both LUE (R2 = 0.62, p < 0.05) and α (R2 = 0.72, p < 0.05). A LUE model derived from corrected PRI values showed good correlation to measured GPP (R2 = 0.77, p < 0.05), with an accuracy comparable to results obtained from an α driven LUE model (R2 = 0.79, p < 0.05). The automated PRI sensors proved to be suitable proxies of light use efficiency. The onset of continuous PRI sensors signifies new opportunities for explicitly examining the cause of changing PRI, LUE, and productivity over time and space. As such, this technology represents great value for the flux, remote sensing and modeling community. [ABSTRACT FROM AUTHOR]