Measuring and modeling evapotranspiration of a Populus euphratica forest in northwestern China

Vegetation is sparsely distributed in the arid regions of northwestern China,and accurately measuring and partitioning of evapotranspiration is of importance for ecosystems in such areas.In this study,we measured and analyzed diurnal and phenological variations in evapotranspiration using the eddy-covariance method based on the Penman-Monteith,Priestley-Taylor,Shuttleworth-Wallace models,a newly proposed improved dual source model and a clumped model in a forest reserve in the Ejin oasis of Populus euphratica in 2015 and 2016 growing seasons.A sensitivity analysis was performed for the models with higher accuracies and we examined the biotic and abiotic controls on evapotranspiration.The results show that the total amounts of evapotranspiration during the two growing seasons in 2015 and 2016 were 622 and 612 mm,respectively.Phenological variations in evapotranspiration produced single-peak curves,while diurnal variations reflected the influence of high temperatures on some afternoons.The Priestley-Taylor and the improved dual source models gave the most accurate evapotranspiration values at the daily scale and appeared to be most suitable for the estimation of evapotranspiration for the species in arid regions.In addition,both models were the most sensitive to net radiation(Rn).

Machine Learning and Pattern Analysis Identify Distinctive Influences from Long-term Weekly Net Ecosystem Exchange at Four Deciduous Woodland Locations

A methodology integrating correlation,regression(MLR),machine learning(ML),and pattern analysis of long-term weekly net ecosystem exchange(NEE)datasets are applied to four deciduous broadleaf forest(DBF)sites forming part of the AmeriFlux(FLUXNET2015)database.Such analysis effectively characterizes and distinguishes those DBF sites for which long-term NEE patterns can be accurately predicted using the recorded environmental variables,from those sites cannot be so delineated.Comparisons of twelve NEE prediction models(5 MLR;7 ML),using multi-fold cross-validation analysis,reveal that support vector regression generates the most accurate and reliable predictions for each site considered,based on fits involving between 16 and 24 available environmental variables.SVR can accurately predict NEE for datasets for DBF sites US-MMS and US-MOz,but fail to reliably do so for sites CA-Cbo and MX-Tes.For the latter two sites the predicted versus recorded NEE weekly data follow a Y≠X pattern and are characterized by rapid fluctuations between low and high NEE values across leaf-on seasonal periods.Variable influences on NEE,determined by their importance to MLR and ML model solutions,identify distinctive sets of the most and least influential variables for each site studied.Such information is valuable for monitoring and modelling the likely impacts of changing climate on the ability of these sites to serve as long-term carbon sinks.The periodically oscillating NEE weekly patterns distinguished for sites CA-Cbo and MX-Tes are not readily explained in terms of the currently recorded environmental variables.More detailed analysis of the biological processes at work in the forest understory and soil at these sites are recommended to determine additional suitable variables to measure that might better explain such fluctuations.

Seasonal and annual variation of CO_2 flux above a broad-leaved Korean pine mixed forest

Long-term measurement of carbon metabolism of old-growth forests is critical to predict their behaviors and to reduce the uncertainties of carbon accounting under changing climate. Eddy covariance technology was applied to investigate the long-term carbon exchange over a 200 year-old Chinese broad-leaved Korean pine mixed forest in the Changbai Mountains (128°28’E and 42°24’N, Jilin Province, P. R. China) since August 2002. On the data obtained with open-path eddy covariance system and CO2 profile measurement system from Jan. 2003 to Dec. 2004, this paper reports (i) annual and seasonal variation of FNEE, FGPP and Re; (ii) regulation of environmental factors on phase and amplitude of ecosystem CO2 uptake and release Corrections due to storage and friction velocity were applied to the eddy carbon flux. Lal and soil temperature determined the seasonal and annual dynamics of FGPP and RE separately. VPD and air temperature regulated ecosystem photosynthesis at finer scales in growing seasons. Water condition at the root zone exerted a significant influence on ecosystem maintenance carbon metabolism of this forest in winter. The forest was a net sink of atmospheric CO2 and sequestered -449 g C·m-2 during the study period; -278 and -171 gC·m-2 for 2003 and 2004 respectively. FGPP and FRE over 2003 and 2004 were -1332, -1294 g C·m-2. and 1054, 1124 g C·m-2 respectively. This study shows that old-growth forest can be a strong net carbon sink of atmospheric CO2. There was significant seasonal and annual variation in carbon metabolism. In winter, there was weak photosynthesis while the ecosystem emitted CO2. Carbon exchanges were active in spring and fall but contributed little to carbon sequestration on an annual scale. The summer is the most significant season as far as ecosystem carbon balance is concerned. The 90 days of summer contributed 66.9, 68.9% of FGPp, and 60.4, 62.1% of RE of the entire year.

Spatial variation of net radiation and its contribution to energy balance closures in grassland ecosystems

Introduction:Low energy balance closure(EBC)at a particular eddy-covariance flux site has increased the uncertainties of carbon,water,and energy measurements and has thus hampered the urgent research of scaling up and modeling analyses through site combinations in regional or global flux networks.Methods:A series of manipulative experiments were conducted in this study to explore the role of net radiation(Rn)in the EBC in relation to spatial variability of vegetation characteristics,source area,and sensor type in three sites of the Inner Mongolian grassland of northern China.Results:At all three sites,the residual fluxes of EBC peaked consistently at 110 W m^(-2).The spatial variability in net radiation was 19 W m^(-2)(5%of R_(n))during the day and 7 W m^(-2)(16%)at night,with an average of 13 W m^(-2)(11%)from eight plot measurements across the three sites.Large area measurements of Rn significantly increased by 9 W m^(-2)during the day and decreased by 4 W m^(-2)at night in the unclipped treatments.Net radiation decreased by 25 W m^(-2)(6%of Rn)at midday and 81 MJ m^(-2)(6%)during a growing season with heavier regular clipping than that in unclipped treatments.The Rn was lower by 11–21 W m^(-2)(~20–40%of Rn)measured by CNR1 than by Q7.1 at night,while there was only 6 W m^(-2)(~1–2%of Rn)difference during the daytime between these two types of commonly used net radiometers.Conclusions:Overall,the inclusion of the uncertainty in available energy accounted for 65%of the~110 W m^(-2)shortfalls in the lack of closure.Clearly,the unclosed energy balance at these three grassland sites remains significant,with unexplored mechanisms for future research.

Improved data gap-filling schemes for estimation of net ecosystem exchange in typical East-Asian croplands

The estimation of carbon exchange between ecosystems and the atmosphere suffers unavoidable data gaps in eddy-covariance technique, especially for short-living and fast-growing croplands. In this study we developed a modified gap-filling scheme introducing a leaf area index factor as the vegetation status information based on the conventional light response function for two East-Asian cropland sites (rice and potatoes). This scheme’s performance is comparable to the conventional time window scheme, but has the advantage when the gaps are large compared to the total length of the time series. To investigate how the time binning approach performs for fast-growing croplands, we tested different widths of the time window, showing that a four-day window for the potato field and an eight-day time window for the rice field perform the best. The insufficiency of the conventional temperature binning approach was explained as well as the influence of vapor pressure deficit. We found that vapor pressure deficit plays a minor role in both the potato and the rice fields under Asian monsoon weather conditions with the exception of the early pre-monsoon growing stage of the potatoes. Consequently, we recommend using the conventional time-window scheme together with our new leaf-light response function to fill data gaps of net ecosystem exchange in fast-growing croplands.