Search

Soil nitrous oxide (N2O) emissions and potato yield were evaluated under 0, 90, and 120 kg N ha−1 fertilizer rates and two planting dates, at productive and degraded fields in the Fraser Valley delta. During the growing season, N2O emissions were comparable among N fertilizer rates. Following November rainfall, N2O emissions increased by three times with 120 kg N ha−1. In the degraded field, yield did not respond to the increasing N fertilizer rates. These findings suggest that lower N fertilizer rates, especially in fields with degraded soils, can lower N2O emissions from British Columbia potato production.

10 pags.- 4 Figs. Under Licence CC BY 4.0, Global warming delays the autumn date of foliar senescence (DFS) in recent decades, with positive implications for growing season length and therefore global carbon storage. However, warming-associated drought, leading to water limitation, may conversely stimulate earlier DFS. Using ground observations since 1940s and 34 years of satellite greenness data (1982‒2015) over the Northern Hemisphere (>30° N), we show the increased impact of drought on DFS. Earlier DFS is linked to decreased precipitation under warming and weaker drought resistance associated with various plant functional traits. For example, isohydric plants with strict regulation of water status may drop leaves fast during droughts. We derive an improved set of phenology models based on this influence and project earlier DFS by the end of the century, particularly at high latitudes (>50° N). Our results limit uncertainties in the later end of plant growth with warming, aiding estimation of carbon uptake of terrestrial ecosystems., This work was funded by the Strategic Priority Research Programme of the Chinese Academy of Sciences (XDA19040103), the National Natural Science Foundation of China (42125101) and the CAS Interdisciplinary Innovation Team (JCTD-2020-05). J.P. and P.C. were funded by European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE-P. J.P. was also financially supported by the Fundación Ramon Areces grant ELEMENTAL-CLIMATE, the Spanish Government grant 2013-610028 and the Catalan Government grant SGR 2017-1005.

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (R

We used, and present, robust methodologies to measure the shortwave (S) and longwave (L) spectral radiative properties (reflectivity (ρ), transmissivity (τ) and absorptivity (α)) of nine plastic films and quantified their effect, when used as mulches, on soil heat flux density (G), net radiation (Rn, above the films) and soil temperature (Ts2cm, 2-cm depth; Ts10cm, 10-cm depth) in comparison to a control (bare soil). During the daytime, all treatments increased G when compared to the control to a maximum of ~45%, except for a plastic film that had a high shortwave ρ (ρs) value (0.45). The films with the highest αs and ρs values had the highest and lowest daytime Rn, respectively. As a general rule, films with high τs and αL values caused the greatest increases in G, Ts2cm and Ts10cm. In contrast, a comparison of three black plastic films with similarly high αs and different longwave properties showed that the film with the highest αL value achieved the lowest G and Ts2cm, which was unexpected. The daytime heat-sharing ratio (G/H, where H is sensible heat flux on the upward-facing side of the mulch) ranged in value from 0.80 ± 0.47 (mulch with τs = 0.79 αL = 0.39) to 0.26 ± 0.13 (mulch with αs = 0.96 αL = 0.94). The lowest total daily downwelling shortwave radiation (Sd) required for total daily G to become positive was 9.4 MJ m−2 compared to 17.6 MJ m−2 for the control, which shows the potential of plastic films for growing-season extension.

We studied the recovery of tree- and stand-level carbon (C) storage in a lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forest in northern British Columbia that experienced substantial (∼83%) mortality in 2006–2007 (total loss by 2013 = 86%) during a severe mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins, 1902) infestation. Earlier work suggested that this forest recovered positive annual C storage 3 years after attack based on eddy covariance measurements. We sought to confirm these results by examining C storage in surviving pine trees using tree core analysis. Average growth release of surviving lodgepole pine trees was 392% (range of –53% to 2326%) compared with mean decadal growth prior to MPB attack. Nearly 97% of trees underwent a growth release, considerably higher than the 15%–75% reported for lodgepole pine in previous studies. Mean annual stem C storage of the surviving trees in this study was highly correlated (r = 0.88) with 10 years of annual net ecosystem productivity estimates made using the eddy covariance technique, indicating that surviving lodgepole pine remain an important part of C recovery after MPB attack. Mean annual stem C storage was also highly correlated (r = 0.92) with the cumulative percentage of downed stems per hectare at the site, suggesting that increased availability of resources is likely assisting the growth release.

International audience; Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, towerbased CO 2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

Understanding the feedback of ecosystem carbon uptake on climate change at temporal and spatial scales is crucial for developing ecosystem models. Previous studies have focused on the role of spring and autumn phenology in regulating carbon sequestration in forest stands, but few on the impact of physiological status in summer. However, plant accumulated the most carbon in summer compared with spring and autumn, therefore, it is of great significance to explore the role of summer phenological metrics on the variability of carbon sequestration. Using 514 site-years of flux data obtained at 40 FLUXNET sites including three forest ecosystems (i.e. evergreen needleleaf forest (ENF), deciduous broadleaf forest (DBF) and mixed forest (MF)) in Europe and North America, we compared the potential of physiological and phenological metrics of Gross Primary Production (GPP) and Ecosystem Respiration (RECO) in explaining the interannual and spatial variability (IAV and SV) of forest net ecosystem production (NEP). In view of the better performance of physiological metrics, we developed the maximum carbon uptake index (MCUI), which integrated the physiology metrics of photosynthesis and respiration in summer, and further explored its ability in explaining the IAV and SV of NEP. The results suggest that the MCUI had a better ability than respiration-growth length ratio (RGR) in predicting NEP for all three forest types. The interpretation of MCUI based on meteorological variables illustrated that the controlling meteorological factors of MCUI differed substantially among ecosystems. The summer shortwave radiation had the greatest influence on MCUI at DBF sites, while the soil water content played an important but opposite role at ENF and DBF sites, and no significant meteorological driver was found at MF sites. The higher potential of MCUI in explaining IAV and SV of NEP highlights the importance of summer physiology in controlling the forest carbon sequestration, and further confirms the significant role of peak plant growth in regulating carbon cycle of forest ecosystems. Understanding the drivers of peak plant growth is therefore of a great significance for further improving the precious of ecosystem model in the future. ISSN:1470-160X ISSN:1872-7034

Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.

Extensive revegetation and conservation programs have been initiated in semiarid desert areas in northern China for over 10 years. However, our knowledge on how drought affects the desert ecosystem carbon (C) and water exchanges is limited. Based on eddy covariance measurements, we evaluated the effect of spring and summer droughts on ecosystem C and water exchanges over a semiarid Artemisia ordosica shrubland in Northwest China for 2014–2016. Over the 3 years, the ecosystem was a weak source of C (40 ± 32 g C m−2 y−1) (mean ± standard deviation) with evapotranspiration (ET) of 310 ± 65 mm y−1. Annual net ecosystem production was − 76, − 25 and − 18 g C m−2 y−1 and water use efficiency (WUE) [gross ecosystem production (GEP)/ET] was 0.92, 1.14 and 1.09 g C kg−1 H2O in 2014, 2015 and 2016, respectively, indicating greater C loss and suppressed WUE in 2014. We found that GEP, Re and ET were significantly suppressed in year 2014 when a severe spring drought occurred, as compared to the year 2016 with summer droughts. The differences in C and water fluxes between years 2014 and 2016 were greater than those between years 2015 and 2016, although the ecosystem suffered a severe summer drought in 2015. Interannual differences in GEP were likely due to differences in leaf area index and canopy conductance, both of which were decreased by drought. Our results indicated that spring drought appears to be more critical to the C balance than summer drought in this semiarid shrubland. This suggested that under future climate change with more variable precipitation and frequent droughts expected in northern China, the timing of drought may be critical to the C and water balances.

We used a hybrid-biometric modelling approach that combines tree-ring based stand reconstruction and the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate past magnitude and inter-annual variation of net primary production (NPP), net ecosystem production (NEP), and heterotrophic respiration (Rh) in plots located within the footprint of an eddy-covariance (EC) installation in a Douglas-fir stand of 1949 origin (DF49 or AmeriFlux CA-Ca1). Stand reconstruction estimated NEP showed excellent correspondence with EC-estimated NEP over the period 1998–2010 (r2 = 0.79, mean difference 24 gC m−2 year−1). Estimates of carbon use efficiency, aboveground NPP, and post-disturbance C dynamics following the harvest of DF49 in 2011 showed discrepancies between modelled estimates and independent data, which were attributed to underestimates of coarse litterfall in previous field studies and to uncertainty in the production, turnover, and post-mortality decay of non merchantable woody biomass in the CBM-CFS3. Despite these issues, the results provide further evidence of the potential use of tree-ring data to expand the availability of long-term estimates of annual ecosystem production and their ability to increase our understanding of forest C dynamics.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.The authors test for temperature dependency of ecosystem respiration rates across globally distributed eddy covariance sites, revealing consistent temperature thresholds where ecosystem metabolism changes.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (R S), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package., Here we describe the lightweight, open source COSORE (COntinuous SOil REspiration) database and software. COSORE focuses on automated, continuous and long‐term greenhouse gas flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation.

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

Land-cover change exerts more influence on soil respiration in boreal and temperate regions than climate change., Soil respiration (Rs) represents the largest flux of CO2 from terrestrial ecosystems to the atmosphere, but its spatial and temporal changes as well as the driving forces are not well understood. We derived a product of annual global Rs from 2000 to 2014 at 1 km by 1 km spatial resolution using remote sensing data and biome-specific statistical models. Different from the existing view that climate change dominated changes in Rs, we showed that land-cover change played a more important role in regulating Rs changes in temperate and boreal regions during 2000–2014. Significant changes in Rs occurred more frequently in areas with significant changes in short vegetation cover (i.e., all vegetation shorter than 5 m in height) than in areas with significant climate change. These results contribute to our understanding of global Rs patterns and highlight the importance of land-cover change in driving global and regional Rs changes.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., European Union (EU), United States Department of Energy (DOE)

Insect outbreaks can significantly influence carbon (C) and water balances of forests. Forest tent caterpillars (FTC) (Malacosoma disstria Hubner) are one of the most prominent insects found in aspen forests in Canada and have the potential to considerably influence regional C and water fluxes. In the summer of 2016, an FTC infestation occurred in a ca. 100 -year-old trembling aspen (Populus tremuloides) stand in the southern boreal forest where the longterm research site known as Old Aspen (OA) is located. The infestation led to nearly complete defoliation of the canopy during the leafing out period when photosynthesis, and thus C uptake, is progressing towards maximum levels. We used 21 years of eddy-covariance (EC) and climate measurements covering pre-infestation and infestation periods to estimate the impact of the FTC infestation on net ecosystem production (NEP), gross ecosystem production (GEP) and evapotranspiration (E). Defoliation in 2016 reduced annual NEP to −130 g C m−2 y−1 and GEP to 798 g C m−2 y−1, respectively, which were much less than their 20-year means (NEP = 118 ± 53 g C m−2 y−1, GEP = 1057 ± 74 g C m−2 y−1), and resulted in the most negative annual NEP value of the 21 years of measurements at the OA site. NEP for 2016 was even lower than values observed during three drought years (2001–2003). However, FTC infestation caused little effect on annual E. FTC infestation reduced the near-surface remotely-measured greenness index, green chromatic coordinate (GCC), to ∼0.32 on June 10 in comparison to ∼0.40 in other years. The defoliation, observable from space as reductions in normalized difference vegetation index (NDVI) values, also showed a negligible effect on E but a large effect on the C fluxes.

The most recent mountain pine beetle (MPB) (Dendroctonus ponderosae) outbreak in British Columbia (BC), which began in the late 1990s, killed ∼54% of the mature merchantable lodgepole pine and was expected to impact gross primary productivity (GPP), ecosystem respiration (R) and thus net ecosystem productivity (NEP) of infested stands. Eddy-covariance (EC) measurements of carbon dioxide and water vapor fluxes have been made in an almost single-species not-salvage-harvested lodgepole pine stand in northern interior BC during the decade following beetle attack in 2006 to determine the effects on the carbon (C) and water balances. We modified the 3-PG (Physiological Principles in Predicting Growth) model to simulate the effects of MPB attack on the stand. Modifications included a sub-model for heterotrophic respiration, which originates from the decomposition of two substrates, soil organic matter and coarse woody debris from the falling dead trees, thus permitting the determination of R and NEP. The modified model was used to simulate C balance components using model parameter values mostly taken from the literature with some estimated from in-situ measurements. Modelled monthly and annual stand-level GPP, R and NEP agreed well with respective EC-estimated values during the decade following attack. Modelled annual GPP, R and NEP decreased by about 52%, 35% and 126%, respectively, in the first year following attack compared to pre-attack values. Modelled GPP and R, as well as EC-estimated GPP, showed a relatively steady increase over the following decade, while R derived from the EC measurements changed little in the first eight years after attack and then increased in the last two years. EC-estimated GPP in 2016 exceeded the estimated pre-attack value by 9%, while modelled and EC-estimated R in 2016 exceeded 2005 values by 6% and 15%, respectively. Modelled NEP indicated that the recovering stand became a C sink a year later than indicated by the EC measurements, but both modelled and measured annual NEP increased significantly between 2007 and 2016. Our observations and modelling results show that the remaining trees and the growing understory enabled the not-salvage-harvested stand to recover from insect attack within a decade, with the stand functioning as a weak, yet distinct, C sink in the last two years of the study period. This suggests that the management strategy of not harvesting attacked stands can be beneficial for the C balance of attacked stands with similar characteristics and in similar climates.

Vegetation phenology and peak growth are important indicators reflecting the response of ecosystems to global changes, yet the trends in peak vegetation growth and its drivers have not been well analyzed across different ecosystems. Here, we used time series of satellite-derived Normalized Difference Vegetation Index (NDVI) (1985–2015) to track recent changes in maximum vegetation growth (the maximum of NDVI (NDVImax) and the peak of growing season (POS)) in the continental US, and explored their responses to both climatic drivers (i.e. temperature, precipitation and cloud cover) and atmospheric changes (i.e. nitrogen (N) deposition and atmospheric CO2 concentration [CO2]). We found that precipitation had the greatest impact on NDVImax, accounting for 31.7% of vegetated area, followed by cloud cover (17.1%), temperature (16.4%), [CO2] (13.7%), and N deposition (10.4%), respectively. However, temperature showed the largest contribution to POS change in about 41.9% of vegetated areas, followed by precipitation (18.6%), cloud cover (15.0%), N deposition (6.7%) and [CO2] (5.9%), respectively. Interestingly, the effects of cloud cover highly depended on moisture regime, that is, more cloud cover was associated with a delayed POS and a decreased NDVImax in wetter regions, but could advance POS and increase NDVImax in dry areas. In addition, we also found that an earlier POS was accompanied by a higher NDVImax in most ecosystems, but with lower NDVImax in arid ecosystems. These results reveal the control of both climatic and atmospheric drivers on peak growth, and consequently are of great significance for understanding of the responses and feedbacks of vegetation to global change and improve models of terrestrial ecosystem carbon cycle.

Hybrid-poplar (HP) plantations have received considerable attention in the Canadian aspen parkland due to their fast growth and carbon (C) sequestration potential, but their high transpiration rates raise concerns due to the low annual precipitation ( P ) in this region. We quantified water and C balances of two HP plantations planted on high-productivity soils in the northwest (HP09) and southeast (HP11) aspen parkland for five and four years, respectively, using eddy-covariance (EC) measurements. A two-source evapotranspiration model, which estimates canopy transpiration ( E cmod ) and soil evaporation ( E smod ) separately, allowed us to study the dynamics of E cmod and E smod as the HP plantations aged. Plantation surface conductance obtained using the model agreed well with that calculated using EC-measured evapotranspiration ( E EC ) in the inverted form of the Penman-Monteith equation. We found that E smod accounted for 96% of total modelled evapotranspiration ( E mod ) in the 1st year of growth but quickly declined with HP canopy closure, as E cmod increasingly dominated E mod , to a maximum of 85% at HP09 in the 5th year of growth. Measurements of net ecosystem production (NEP) showed both HP09 and HP11 shifted from annual C sources to annual C sinks of 87 ± 44 and 95 ± 97 g C m −2 yr −1 , respectively, in the 3rd year of growth, as gross primary production (GPP) increased and exceeded ecosystem respiration ( R e ). The rapid increase in GPP at HP09 coincided with large increases in E EC , causing E EC to exceed P in the 3rd to 6th years of growth, partly due to low P during the 5th and 6th years of growth. Water use efficiency (WUE) increased with plantation age from 0.13 to 2.5 g C kg −1 H 2 O in the 1st and 3rd year of growth at HP11, respectively, but at HP09, WUE plateaued during the 3rd to 5th years of growth (∼1.9 g C kg −1 H 2 O) and declined slightly in the 6th year due to disturbance (drought, hail damage, and fungal infection). We show that, although these HP plantations quickly shifted from being C sources to being C sinks, E EC can increase rapidly and exceed P , which highlights the impact that fast-growing HP plantations, when established over a large area, could have on the local water balance.

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

We propose a gap-filling model for carbon dioxide fluxes measured by eddy covariance (EC) that combines the flux variance similarity (FVS) partitioning approach with the artificial neural network (ANN) technique (FVS–ANN). 18 years of EC-measured net ecosystem production (NEP) of a Douglas-fir (Pseudotsuga menziesii) stand in British Columbia, Canada were used. FVS-partitioned fluxes were used as a training dataset for ANNs based on the environmental variables to model missing respiration and photosynthesis values. Results from the FVS–ANN model were compared with three established models using different partitioning and gap-filling approaches, namely the nighttime relationship, the daytime intercept, and an ANN-based model informed by the nighttime relationship (ANN–nighttime). In the gap-filled long-term NEP record, the 18-year mean NEP values were similar (between 225 and 239 gC m−2 year−1) and individual years showed small differences in annual NEP among the four models, demonstrating the reliability of estimated NEP when any of the models were used for gap-filling. However, the largest differences in annual gap-filled photosynthesis and respiration estimates among the four models in a given year were as large as 813 and 835 gC m−2 year−1, respectively. The FVS–ANN model consistently resulted in the smallest annual photosynthesis and respiration estimates, while the nighttime-based models resulted in the highest photosynthesis and respiration. The differences between the FVS–ANN and any of the other three models are explained by the different definitions of partitioned fluxes (i.e., values from the FVS–ANN are smaller than the other three models by leaf respiration). However, the differences may also be partly due to light inhibition of daytime respiration, which is known as the Kok effect that is believed to be adequately considered in the new FVS–ANN combination and partially in the daytime intercept model, but not in the other two models. The results suggest that previous EC-based estimates of global photosynthesis and respiration obtained by using nighttime relationships are potentially biased high.

The Pantanal is the largest tropical wetland on the planet and yet little information is available on the biome's carbon cycle. We used an automatic station to measure soil CO2 concentrations and oxidation-reduction potential over the 2014 and 2015 flood cycles of a tree island in the Pantanal that is immune to inundation during the wetland's annual flooding. The soil CO2 concentration profile was then used to estimate soil CO2 efflux over the two periods. In 2014, subsurface soil saturation at 0.30 m depth created conditions in that layer that led to CO2 buildup close to 200,000 ppm and soil oxidation-reduction potential below –300 mV, conditions that were not repeated in 2015 due to annual variability in soil saturation at the site. Mean CO2 efflux over the 2015 flood cycle was 0.023 ± 0.103 mg CO2-C m-2 s-1 representing a total annual efflux of 593 ± 2690 mg CO2-C m-2 y-1. Unlike a nearby tree island site that experiences full inundation during the wet season, here the soil dried quickly following repeated rain events throughout the year which led to the release of soil CO2 pulses from the soil. This study not only highlights the complexity and heterogeneity in the Pantanal's carbon balance based on differences in topography, flood cycles and vegetation, but also the challenges of applying the gradient-method in the Pantanal due to deviations from steady-state conditions.

The Quest Carbon Capture and Storage (CCS) project in Alberta, Canada, is a fully integrated project, as it involves the capture, transport, injection, storage of CO2, and a measurement, monitoring and verification (MMV) program. The MMV program has two key objectives: a) to ensure containment and b) to ensure conformance. Prior to the start of CO2 injection at the end of August 2015, a number of projects were undertaken to gather data from various domains, namely the atmosphere, biosphere, hydrosphere and geosphere, to provide input to the Quest MMV program. The focus of this paper is on monitoring activities undertaken in relation to the atmosphere and biosphere domains. Activities undertaken across the Quest sequestration lease area (SLA) included an eddy covariance system, soil gas probes, soil flux chambers, and walk-over surveys. In conclusion, understanding the spatial and temporal variability of CO2 levels prior to start of CO2 injection represents an important activity of a CCS MMV program. It provides technical input to the development of such a program, but also provides knowledge for communication to and awareness of project stakeholders (e.g. landowners) regarding CO2 levels within the atmosphere and biosphere across a SLA.

Tree mortality due to the recent mountain pine beetle (MPB) (Dendroctonus ponderosae) outbreak in British Columbia (BC) is expected to impact evapotranspiration (E), gross primary productivity (GPP), and snow accumulation and melt, thereby influencing ecosystem hydrology. To quantify the impact on E and GPP, we have made eddy-covariance (EC) measurements of water vapor and carbon dioxide fluxes for nine years above a lodgepole pine (Pinus contorta var. latifolia) stand in northern interior BC that was not salvage harvested following beetle attack in 2006. To understand the processes and determine long-term recovery of the water and carbon balances of this stand following attack, we modified the 3-PG (Physiological Principles in Predicting Growth) model to include the effects of insect attack on the stand, and modelled monthly E, GPP and water use efficiency (WUE) of the understory and overstory. The modified model was validated using the flux and climate measurements made during the nine-year period. It generally worked well with modelled annual E and GPP agreeing reasonably well with their measured values. Modelled values of annual E and GPP decreased by about 62% and 52%, respectively, between 2005 and 2007. Annual measured E remained remarkably stable for five years after the attack, and then increased by ∼13% year−1 in the last four years; however, the model indicated a relatively steady increase of ∼13% year−1 over the 9 years. On the other hand, EC-estimated GPP showed a steady recovery (∼9% year−1) almost returning to estimated pre-attack levels within nine years. Modelled annual GPP generally agreed with EC-estimated values as well as capturing much of the interannual variability observed in the last 4 years. Projections for the following decade, depending on expected climate change, suggested that E would slightly increase, GPP would remain relatively constant, and WUE would decrease slightly. With the decrease in E, modelled drainage (Dr) increased significantly in the first year after attack compared to pre-attack estimates, but gradually decreased again in the following years. Measured and modelled Dr decreased between 2007 and 2015 by about 28% and 49%, respectively. Projections show Dr staying relatively constant for the following decade (2016–2025). Our observations that the recovery of E and GPP was faster than expected suggest that not to salvage harvest MPB-attacked stands with considerable remaining live canopy trees or understory should be a beneficial management strategy from carbon sequestration and hydrologic perspectives.

Nitrogen (N) fertilization of forests for increasing carbon sequestration and wood volume is expected to influence soil greenhouse gas (GHG) emissions, especially to increase N2O emissions. As biochar application is known to affect soil GHG emissions, we investigated the effect of biochar application, with and without N fertilization, to a forest soil on GHG emissions in a controlled laboratory study. We found that biochar application at high (10%) application rates increased CO2 and N2O emissions when applied without urea-N fertilizer. At both low (1%) and high biochar (10%) application rates CH4 consumption was reduced when applied without urea-N fertilizer. Biochar application with urea-N fertilization did not increase CO2 emissions compared to biochar amended soil without fertilizer. In terms of CO2-eq, the net change in GHG emissions was mainly controlled by CO2 emissions, regardless of treatment, with CH4 and N2O together accounting for less than 1.5% of the total emissions.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks., A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.

Long-term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999-2017 from a 120-year-old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long-term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p

International audience; In the version of this Letter originally published, there were errors in Fig. 1a. The sites denoted purple were described in the legend as `Pday>0.05 & Pnight>0.05', but should have been labelled `Pdaynight>0.05'. The sites denoted green were described in the legend as `Pday>0.05 & Pnight>0.05', but should have been labelled `Pday>0.05 & Pnightday>0.05 & Pnight>0.05', but should have been labelled `Pdaynight

Agricultural fields can be significant sources of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4), with implications for climate change. This paper reports continuous half-hourly CO2, CH4 and N2O fluxes over a conventionally-managed highbush blueberry field on Westham Island in Delta, British Columbia (BC), Canada, measured using the eddy-covariance (EC) method for a 1-year period. Field management, including fertilization and mowing interrow grass, was associated with substantial changes in GHG exchange. With emissions of N2O and CH4 totaling 0.61 ± 0.03 g N2O m−2 year−1 and 0.81 ± 0.4 g CH4 m−2 year−1, corresponding to 182 ± 9 g and 30 ± 13 g CO2 equivalent (CO2e) m−2 year−1, respectively, based on their 100-year global warming potentials, the field was a net source of 840 ± 126 g CO2e m−2 year−1. The annual net ecosystem exchange of CO2 (NEEc) was the largest component of the GHG balance at 171 ± 28 g C m−2 year−1 (628 ± 104 g CO2 m−2 year−1), indicating the field was a net carbon (C) source. After accounting for inputs and outputs of C in sawdust and harvested fruit, respectively, the agroecosystem gained a net of 233 ± 88 g C m−2 year−1, primarily controlled by the application of sawdust mulch. Both soil temperature and soil moisture were important environmental factors controlling GHG emissions, which has implications for future feedback cycles and climate change. Our results suggest that agricultural management strategies can be targeted for GHG mitigation.

It is critical to have long-term carbon dioxide (CO2) flux observations in forest ecosystems to understand how changing climate can affect forest carbon (C) stocks and CO2 exchange between forests and the atmosphere. In this study, fifteen years (2002–2016) of continuous eddy-covariance flux and climate measurements in an intermediate-aged Douglas-fir stand on the east coast of Vancouver Island, Canada, were analyzed. First, the eddy covariance-measured CO2 fluxes were partitioned into gross primary production and ecosystem respiration using two artificial neural networks. Second, the responses of net ecosystem production, gross primary production and ecosystem respiration to interannual climate variability, including five El Nino-Southern Oscillation events, were determined. Three hyper-parameters (number of layers, hidden units, and batch size) of each artificial neural network were set by Bayesian optimization using sequential model-based optimization while the remaining hyper-parameters were taken from the literature. The first artificial neural network was fitted using only nighttime CO2 flux data and applied to estimate nighttime and daytime ecosystem respiration values, and the second one was used to gap-fill gross primary production values. In addition, a predictor analysis was done to investigate the most influential predictors (i.e., environmental variables) within seasons and years. When applied to half-hourly data, the ecosystem respiration model had an R2 of 0.43, whereas the gross primary production model had an R2 of 0.80. The stand was a moderate C sink (average net ecosystem production of 118 ± 404 g C m−2 year−1) during the entire study period, except for the years 2002–2006 when the stand was a moderate C source. The mean annual values of gross primary production and ecosystem respiration were 1649 ± 157 g C m−2 year−1 and 1531 ± 410 g C m−2 year−1, respectively. Our analysis showed that soil temperature was the most important predictor for the ecosystem respiration model, and photosynthetically active irradiance was the most important predictor for the gross primary production model. However, during dry periods in late summer, soil moisture became the most important predictor. Interannual variability of net ecosystem production was only slightly affected by annual total precipitation, mean soil temperature and mean air temperature. Instead, it depended on spring mean air temperature (start of the growing season), summer total precipitation (indicative of water deficiency) and mean summer air temperature. El Nino and La Nina events generally resulted in lower and higher annual net ecosystem production, respectively.

Partitioning measured net ecosystem exchange of CO2 (NEE) into ecosystem respiration (Re) and gross primary production (GPP) is essential for understanding the biophysical controls on forest ecosystem carbon (C) dynamics. Obtaining Re and GPP accurately from NEE remains a challenge. In this study, we measured stable CO2 isotopologue signatures at ecosystem scale simultaneously with eddy-covariance measurements of NEE above a Douglas-fir stand on Vancouver Island, Canada. This allowed us to analyze three partitioning methods (the traditional nighttime relationship, daytime intercept, and stable C isotope methods). In all three methods, nighttime Re values were obtained from nighttime EC-measured NEE values. Over a 29-day summertime period, daily (24-h) Re and GPP obtained using the daytime intercept method were 11±4% and 6 ± 5%, respectively, lower than those estimated using the nighttime relationship method. Stable-C-isotope-partitioned daily Re and GPP were 35±13% and 19±10%, respectively, lower than when using the nighttime relationship method to obtain daytime Re. That mean daytime Re obtained using the stable C isotope method was 56% less than that estimated using the nighttime relationship method suggests that light inhibition of foliage respiration (i.e., the Kok effect) had a major effect on daytime Re in this Douglas-fir stand. The mean daytime Re obtained using the stable C isotope method was 49% lower than the value estimated using the daytime intercept method, which indicates that the daytime intercept method accounted only for a small proportion of the light inhibition effect during the most active period of the growing season.

Planting hedgerows on farm field edges can help mitigate greenhouse gas (GHG) emissions from agricultural landscapes by sequestering carbon (C) in woody biomass and in soil. Sequestration rates however, must be assessed in terms of their overall global warming potential (GWP) which must also consider GHG emissions. The objectives of this study were to (1) compare carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions from two types of hedgerows and adjacent annual agricultural production fields, and 2) better understand how climate, soil properties and plant species configurations affect hedgerow GHG emissions. At eight study sites in the lower Fraser River delta of British Columbia, we measured emissions from soil in both planted (P-Hedgerow) and remnant hedgerows (R-Hedgerow), as well as in adjacent annual crop production fields over 1 year using a closed-static chamber method. CO2 emissions were 59 % higher in P-Hedgerow than R-Hedgerow, yet there were no significant differences of relative emissions of CH4 and N2O. The environmental variables that explained the variation in emissions differed for the three GHGs. CO2 emissions were significantly correlated with soil temperature. CH4 and N2O and emissions were marginally significantly correlated with soil organic carbon (SOC) and soil water-filled pore space (WFPS), respectively. Emissions were not significantly correlated with hedgerow plant species diversity. While hedgerows sequester carbon in their woody biomass, we demonstrated that it is critical to measure hedgerow emissions to accurately ascertain their overall GHG mitigation potential. Our results show that there are no CO2e emission differences between the management options that plant new diverse hedgerows or conserve existing hedgerows.

Plant phenology plays a significant role in regulating carbon sequestration period of terrestrial ecosystems. Remote sensing of land surface phenology (LSP), i.e., the start and the end of the growing season (SOS and EOS, respectively) in evergreen needleleaf forests is particularly challenging due to their limited seasonal variability in canopy greenness. Using 107 site-years of CO 2 flux data at 14 evergreen needleleaf forest sites in North America, we developed a new model to estimate SOS and EOS based entirely on the Moderate Resolution Imaging Spectroradiometer (MODIS) data. We found that the commonly used vegetation indices (VI), including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), were not able to detect SOS and EOS in these forests. The MODIS land surface temperature (LST) showed better performance in the estimation of SOS than did a single VI. Interestingly, the variability of LST (i.e., the coefficient of variation, CV_LST) was more useful than LST itself in detecting changes in forest LSP. Therefore, a new model using the product of VI and CV_LST was developed and it significantly improved the representation of LSP with mean errors of 11.7 and 5.6 days for SOS and EOS, respectively. Further validation at five sites in the Long Term Ecological Research network (LTER) using camera data also indicated the applicability of the new approach. These results suggest that temperature variability plays a previously overlooked role in phenological modeling, and a combination of canopy greenness and temperature could be a useful way to enhance the estimation of evergreen needleleaf forest phenology of future ecosystem models.

Establishment of hybrid poplar (HP) plantations has been advocated as an effective method for sequestering CO2 from the atmosphere. However, how carbon (C) cycling in HP plantations changes during stand development under different soil fertility and climatic conditions is poorly understood. We studied the dynamics of soil respiration (R-s) and its heterotrophic (R-h) and autotrophic (R-a) components and soil organic C (SOC) content in HP plantations of different stand ages established on soils with different productivity (Class 1 vs. Class 3 soils) in Alberta (AB) and Ontario (ON), Canada. The Rs was the highest for AB-Class 1 (high-productivity) soils, followed by AB-Class 3 and ON-Class 3 (low-productivity) soils. Annual Rs, Rh, and R-h/R-s decreased in the first 3 yr in AB-Class 1 and 6 yr in AB-Class 3 soils after plantation establishment and increased thereafter, but they increased with stand age after plantation establishment in ON-Class 3 soils. The SOC content in the AB-Class 1, AB-Class 3, and ON-Class 3 sites decreased in the first 3, 5, and 1.5 yr, respectively, after plantation establishment and then increased, reaching the pre-establishment level after 6, 10, and 3 yr, respectively. From this first attempt to understand C cycling across multiple sites with different soil fertility levels, we conclude that stand age and soil productivity play a significant role in affecting C cycling, and such effects should be considered in regional and global C cycling models, especially when assessing the C sequestration potential of HP plantations.

Douglas-fir (Pseudotsuga menziesii) forests in the Pacific Northwest are the most productive managed forests in North America. Nitrogen (N) fertilizers are generally applied in this region to increase the rate of tree growth and consequently carbon (C) sequestration. However, the long-term effects of N fertilization on C and water exchanges of Douglas-fir forests are not clear. This study presents 15 years of eddy-covariance (EC) measurements of C and water fluxes above a pole-sapling-stage Douglas-fir stand on Vancouver Island, British Columbia, Canada, and determines how N fertilization with 200 kg ha−1 of urea-N affected these fluxes over the 10-year period after fertilization. A process-based forest growth model, 3-PG, was calibrated using EC-measured C and water fluxes during the 5 pre-fertilization years, and then used to predict these fluxes for the next 10 years assuming the stand was not fertilized. The modelled C and water fluxes for the pre-fertilization years agreed well with the measurements (with R2 values of 0.90, 0.89, and 0.89 for gross primary production (GPP), ecosystem respiration (Re) and evapotranspiration (ET), respectively) and only slightly underestimated GPP, Re, and ET by 4%, 1%, and 3%, respectively. The effects of N fertilization on C sequestration and water use (ET) were then obtained as differences between EC-measured (fertilized stand) and modelled (unfertilized stand) fluxes. Application of N fertilizer to this stand led to a short-term (first two years) increase in GPP followed by little change over the long term. Re increased over the short-term (first year), while it was appreciably suppressed over the long term. N fertilization resulted in an average increase in net ecosystem productivity by 170 g m−2 year−1 of C during 2007–2016 with interannual variation depending on annual weather conditions. N fertilization led to an average increase in annual water use of 15% (or 53 mm year−1).

This study examined the response of carbon (C) sequestration and evapotranspiration (ET) to nitrogen (N) fertilization during the four post-fertilization years (2007–2010) in a Pacific Northwest chronosequence of three Douglas-fir stands 61, 22 and 10 yr old in 2010 (DF49, HDF11 and HDF00, respectively). An artificial neural network (ANN) for time series analysis was employed to identify and estimate the complex nonlinear relationships between C and water exchanges and environmental variables. To test the performance of the ANN model, it was trained against multi-year monthly climate variables and EC-measured C and water fluxes for 1998–2004 and the trained model was then verified using data obtained in 2005 and 2006. The optimized model which showed high reliability (linear regression analysis: for C and water fluxes, R2 > 0.93, slope = 0.96–0.99, p < 0.000) was then used to calculate the C and water fluxes for 2007–2010 assuming the three stands were not fertilized. The calculated C and water fluxes (for non-fertilized conditions) were compared with the measured fluxes (for fertilized conditions) to quantify the effects of fertilization during the post-fertilization four years. Results showed that N fertilization increased gross primary productivity of all three stands in all four years with the largest absolute increases in the 10 yr-old stand (HDF00) followed by the 22 yr-old stand (HDF11). Ecosystem respiration increased in all four years at HDF00, but decreased over the last three years at HDF88, and over all four years in the 61 yr-old stand (DF49). As a result, fertilization increased the net ecosystem productivity of all three stands with the average increase being the largest at HDF88 followed by DF49. In addition, fertilization caused a small increase in annual ET in all four years at DF49; a small increase in the first year and a decrease in the next three years at HDF88; and no consistent effect at HDF00. Consequently, fertilization exerted only a small impact on water use efficiency in the oldest stand (DF49) but a significant increase in the two younger stands (HDF00 and HDF88). Furthermore, N fertilization increased light use efficiency in all three stands, especially in the 10 yr-old stand.

Plant phenology is a sensitive indicator of climate change1–4 and plays an important role in regulating carbon uptake by plants5–7. Previous studies have focused on spring leaf-out by daytime temperature and the onset of snow-melt time8,9, but the drivers controlling leaf senescence date (LSD) in autumn remain largely unknown10–12. Using long-term ground phenological records (14,536 time series since the 1900s) and satellite greenness observations dating back to the 1980s, we show that rising pre-season maximum daytime (Tday) and minimum night-time (Tnight) temperatures had contrasting effects on the timing of autumn LSD in the Northern Hemisphere (> 20° N). If higher Tday leads to an earlier or later LSD, an increase in Tnight systematically drives LSD to occur oppositely. Contrasting impacts of daytime and night-time warming on drought stress may be the underlying mechanism. Our LSD model considering these opposite effects improved autumn phenology modelling and predicted an overall earlier autumn LSD by the end of this century compared with traditional projections. These results challenge the notion of prolonged growth under higher autumn temperatures, suggesting instead that leaf senescence in the Northern Hemisphere will begin earlier than currently expected, causing a positive climate feedback. Rising pre-season daytime and night-time temperatures have contrasting effects on the timing of autumn-leaf senescence date in the Northern Hemisphere. Diurnal differences in drought stress may be the underlying mechanism.

This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.