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Partitioning Eddy Covariance Water Flux Components Using Physiological and Micrometeorological Approaches
Journal of Geophysical Research: Biogeosciences
Abstract
Eddy covariance (EC) provides ecosystem-scale estimates of photosynthesis (Ph) and evapotranspiration (ET; the sum of plant transpiration [T] and evaporation [Es]). Separating ET into its components is becoming necessary for linking plant-water use strategies to environmental variability. Based on optimality principles, a data-model based approach for partitioning ET was proposed and independently tested. Short-term responses of canopy-scale internal leaf-to-ambient CO2 (χ) were predicted based on a big-leaf representation of the canopy accounting for the influence of boundary-layer conductance. This representation allowed investigating stomatal behavior in accordance with the Ph estimates. With the objective of minimizing the carbon cost of transpiration, a novel optimization approach was implemented to develop solutions for an optimal stomatal conductance model as the basis to derive T. The Es was then calculated as a residual between the observed ET and modeled T. The proposed method was applied to long-term EC measurements collected above a Mediterranean tree-grass ecosystem. Estimated Es agreed with independent lysimeter measurements (r = 0.69). They also agreed with other partitioning methods derived from similarity theory and conditional sampling applied to turbulence measurements. These similarity schemes appeared to be sensitive to different χ parameterization. Measured Es was underestimated by 30% when χ was assumed constant (= 0.8). Diel and seasonal χ patterns were characterized in response to soil dryness. A surprising result was a large Es/ET throughout the seasons. The robustness of the results provides a new perspective on EC ET partitioning, which can be utilized across a wide range of climates and biomes.
... T can be partitioned from ecosystem-scale evapotranspiration (ET) by several methods, including leaf gas exchange, plant-level sap flow, lysimeters, soil, photometers, soil heat pulse methods, and stable and radioisotopic techniques [14][15][16]. Among them, Nelson et al. [17] used three widely applicable methods, underlying water use efficiency (uWUE) [18], Perez-Priego [19], and the Transpiration Estimation Algorithm (TEA) [20], to partition the eddy covariance (EC)-based ET into evaporation (E) and T for 251 sites in FLUXNET [21]. All three methods are based on coupled water-carbon relationships, but their assumptions and parameterization methods differ. ...
... The uWUE method [22,23] assumes an ecosystem has an actual and potential underlying water use efficiency and uses optimality assumptions to calculate T/ET. The Perez-Priego method [19] circumvents the assumption that T/ET approaches unity at some periods by estimating ecosystem conductance directly. The TEA method from Nelson et al. [20] utilizes a nonparametric model and thereby limits assumptions on how the ecosystem functions [14]. ...
... GPP is gross primary productivity, and D a is vapor pressure deficit (kPa). Perez-Priego et al. used optimality theory for a more complex partitioning of ET using a big-leaf canopy model (big-leaf scheme) in which parameters were optimized using half-hourly data from a 5-day window so that the parameters for each 5-day window maximally satisfied the fit between the model and the observed GPP and also minimized water loss per carbon gain [19]. T was then calculated from the model using G s , and E was calculated as the residual (ET-T). ...
Plant stomata regulate transpiration (T) and CO2 assimilation, essential for the water–carbon cycle. Quantifying how environmental factors influence stomatal conductance will provide a scientific basis for understanding the vegetation–atmosphere water–carbon exchange process and water use strategies. Based on eddy covariance and hydro-metrological observations from FLUXNET sites with four plant functional types and using three widely applied methods to estimate ecosystem T from eddy covariance data, namely uWUE, Perez-Priego, and TEA, we quantified the regulation effect of environmental factors on canopy stomatal conductance (Gs). The environmental factors considered here include radiation (net radiation and solar radiation), water (soil moisture, relative air humidity, and vapor pressure deficit), temperature (air temperature), and atmospheric conditions (CO2 concentration and wind speed). Our findings reveal variation in the influence of these factors on Gs across biomes, with air temperature, relative humidity, soil water content, and net radiation being consistently significant. Wind speed had the least influence. Incorporating the leaf area index into a Random Forest model to account for vegetation phenology significantly improved model accuracy (R² increased from 0.663 to 0.799). These insights enhance our understanding of the primary factors influencing stomatal conductance, contributing to a broader knowledge of vegetation physiology and ecosystem functioning.
... In recent years, there have been notable advances in developing models that partition ET using flux tower data that can be applied to a broad range of ecosystem types (Eichelmann et al., 2022;Li et al., 2019;Nelson et al., 2018;Pérez-Priego et al., 2018;Scanlon et al., 2019;Scott & Biederman, 2017;Zahn et al., 2022;Zhou et al., 2016). However, previous ET partitioning models have various potential issues when applied to dryland ecosystems. ...
... However, previous ET partitioning models have various potential issues when applied to dryland ecosystems. For example, they estimate water-use efficiency (WUE) using only dry periods (Nelson et al., 2018;Zhou et al., 2016), assume plants maximize carbon gain per unit water lost (Pérez-Priego et al., 2018;Zhou et al., 2016), or do not produce daily estimates or E, T, or WUE (Scott & Biederman, 2017) (see Table 1). Due to these limitations, a flux tower-based ET partitioning approach is needed that can be confidently applied to dryland ecosystems. ...
... Constraining WUE has been the main focus of improving ET partitioning models (Niu et al., 2011). Some fluxbased ET partitioning models-such as the models introduced in Pérez- Priego et al. (2018) and Zhou et al. (2016) -use theories of stomatal behavior related to leaf-level (intrinsic) WUE to estimate WUE at the ecosystem scale. ...
Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.
... We do so using an approach developed to partition carbon and water fluxes from high frequency EC measurements called flux variance similarity (FVS) (Scanlon & Kustas, 2012;Scanlon & Sahu, 2008). FVS assumes that stomatal and non-stomatal fluxes independently conform to Monin-Obukhov similarity theory and has been successfully applied to study E and T across multiple global ecosystems Perez-Priego et al., 2018;Rana et al., 2018;Scanlon & Kustas, 2012;Sulman et al., 2018;Wagle et al., 2020) but less frequently in forests and wetlands (Klosterhalfen et al., 2019;Sulman et al., 2018), leaving opportunities to better understand the pathways by which different ecosystems use water. ...
... This finding is supported by Paul-Limoges et al. (2020) who also found quasi-constant daily E below the canopy throughout seasonal changes in a deciduous forest in Switzerland. E is strongly associated with changes in SM under water limited conditions (Or & Lehmann, 2019;Perez-Priego et al., 2018). When the moisture content of the soil surface is close to saturation, atmospheric conditions control E. Our observations typically fell between saturation and water limitation during the measurement period (e.g., Figure 4b) such that we found weak relationships between both edaphic variables and atmospheric drivers when considering seasonal sums. ...
Climate change is intensifying the hydrologic cycle and altering ecosystem function, including water flux to the atmosphere through evapotranspiration (ET). ET is made up of evaporation (E) via non‐stomatal surfaces, and transpiration (T) through plant stomata which are impacted by global changes in different ways. E and T are difficult to measure independently at the ecosystem scale, especially across multiple sites that represent different land use and land management strategies. To address this gap in understanding, we applied flux variance similarity (FVS) to quantify how E and T differ across 13 different ecosystems measured using eddy covariance in a 10 × 10 km area from the CHEESEHEAD19 experiment in northern Wisconsin, USA. The study sites included eight forests with a large deciduous broadleaf component, three evergreen needleleaf forests, and two wetlands. Average T/ET for the study period averaged nearly 52% in forested sites and 45% in wetlands, with larger values after excluding periods following rain events when evaporation from canopy interception may be expected. A dominance analysis revealed that environmental variables explained on average 69% of the variance of half‐hourly T, which decreased from summer to autumn. Deciduous and evergreen forests showed similar E trajectories over time despite differences in vegetation phenology, and vapor pressure deficit explained some 13% of the variance E in wetlands but only 5% or less in forests. Retrieval of E and T within a dense network of flux towers lends confidence that FVS is a promising approach for comparing ecosystem hydrology across multiple sites to improve our process‐based understanding of ecosystem water fluxes.
... As a result, correction methods have been developed over the years mostly based on the idea of LE underestimation (Twine et al., 2000). Moreover, methods for partitioning the total evapotranspiration into evaporation (E) and transpiration (T) have been developed, even though many limitations and uncertainties are still present (Nelson et al., 2020;Perez-Priego et al., 2018;Zhou et al., 2016;Scott and Biederman, 2017;Scanlon and Kustas, 2012). ...
... Besides providing an estimate of the total fluxes, the FEST-2X2-EWB scheme has been demonstrated to reproduce the soil and vegetation components of the energy fluxes in respect to eddy covariance Recently, the study of the evapotranspiration components has gained new attention due to the increasing importance of water uses in irrigated agriculture, while remaining still an open problem due to the complex interaction between the soil dynamic, crop and meteorological conditions. Thus, the T/ET ratio can vary from 30% to 90% Fisher et al., 2017;Nelson et al., 2020;Perez-Priego et al., 2018). ...
... The transpiration (T ) component accounts for water loss from the leaf stomata of the sparse tree component, seasonal grasses, and the minor forb component. The evaporation (E) component is large following rain events, as intercepted water and near-surface soil water evaporate; the latter may continue over periods longer than a week (Perez-Priego et al., 2018). The partitioning of ET between E and T may Published by Copernicus Publications on behalf of the European Geosciences Union. ...
... Therefore, the random error of the monthly means of the 30 min T /ET estimates in this study can be assumed to be small. For a Mediterranean tree-grass savanna, T /ET was shown to rarely exceed 0.8 (Perez-Priego et al., 2018). In contrast to the Mediterranean site, the Welgegund site has sandy soil, deep-rooted trees, and no clay horizon close to the soil surface. ...
The role of precipitation (P) variability with respect to evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E), from savannas continues to draw significant research interest given its relevance to a number of ecohydrological applications. Our study reports on 6 years of measured ET and estimated T and E from a grazed savanna grassland at Welgegund, South Africa. Annual P varied significantly with respect to amount (508 to 672 mm yr-1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy-covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T for the 4 wet years with frequent early wet-season rainfall was nearly constant, 326±19 mm yr-1 (T/ET=0.51), but was lower and more variable between the 2 dry years (255 and 154 mm yr-1, respectively). Annual T and T/ET were linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grasses as well as trees' ability to use water from deeper layers. During extreme drought, grasses respond to water availability with a dieback–regrowth pattern, reducing leaf area and transpiration and, thus, increasing the proportion of transpiration contributed by trees. The works suggest that the early-season P distribution explains the interannual variability in T, which should be considered when managing grazing and fodder production in these grasslands.
... This is in line withPerez-Priego et al. (2017, 2018 who show that the understory ET dominates in ES-LM1. In fact, E soil /ET inPerez-Priego et al. (2018) reached up to ~70% during the growing period, estimated through lysimeter measurements and a novel ET partitioning method, similar to that achieved with 3SEB (Fig. 9). Perez-Priego et al.(2018)observed considerable soil evaporation rates even when the shallow (i.e., sandy) soil was dry, indicating the evaporation rates may be upheld from moisture of the deeper soil (e.g., clay) layer.While past studies suggested T/ET to be independent from P (e.g.,Fatichi and Pappas, 2017;Schlesinger and Jasechko, 2014, Sun et al. 2019), mean annual T/ET correlated positively here with annual P (r = 0.58, p = 0.02;Fig. ...
... 10). In water-limited ecosystems, ET partitioning might be more strongly linked to P and water availability (e.g.,Perez-Priego et al., 2018).El-Madany et al. (2020) reported very strong linear correlations between annual P and GPP for ES-Abr and ES-LM1, which has mechanistic links to T. At the monthly scale, T un /ET and T ov /ET had opposing relations with seasonal P. This further demonstrated the contrasting survival strategies of both vegetation functional ...
It is well documented that energy balance and other remote sensing‐based evapotranspiration (ET) models face greater uncertainty over water‐limited tree‐grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass‐dominated understory and tree‐dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy‐limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal‐based three‐source energy balance (3SEB) model, accommodating an additional vegetation source within the well‐known two‐source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy‐covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m²; MSG: LE RMSD ~90 W/m²), improving over both TSEB and seasonally changing TSEB (TSEB‐2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.
... During the dry season, the herbaceous species are inactive until the return of rain 85 . The site is managed with low-intensity grazing by cows during the growing season (El-Madany et al., 2018). An exclusion cage was used to avoid cows stepping into the lysimeters. ...
... Fluxes of latent heat (λE, W m −2 ), wind speed (u, m s −1 ) and friction velocity (u * , m s −1 ) were measured by an eddy covariance (EC) system, consisting of a sonic anemometer (R3-50 Gill Instruments, Lymingon UK) and an infra-red gas analyzer (LI-7200, Licor Biosciences, Lincoln, USA) at 1.6 m sampling height and targeting the herbaceous layer . For further details on the EC data processing, see El-Madany et al. (2018). ...
The input of liquid water to terrestrial ecosystems is composed of rain and non-rainfall water input (NRWI). The latter comprises dew, fog, and adsorption of atmospheric vapor on soil particle surfaces. Although NRWIs can be relevant to support ecosystem functioning in seasonally dry ecosystems, they are understudied, being relatively small, and therefore hard to measure. In this study, we test a routine for analyzing lysimeter data specifically to determine NRWI. We apply it on one year of data from large high-precision weighing lysimeters at a semi-arid Mediterranean site and quantify that NRWIs occur for at least 3 h on 297 days (81 % of the year) with a mean diel duration of 6 hours. They reflect a pronounced seasonality as modulated by environmental conditions (i.e., temperature and net radiation). During the wet season, both dew and fog dominate NRWI, while during the dry season it is soil adsorption of atmospheric vapor. Although NRWI contributes only 7.4 % to the annual water input NRWI is the only water input to the ecosystem during 15 weeks, mainly in the dry season. Benefitting from the comprehensive set of measurements at the Majadas instrumental site, we show that our findings are in line with (i) independent model simulations forced with (near-) surface energy and moisture measurements and (ii) eddy covariance-derived latent heat flux estimates. This study shows that NRWI can be reliably quantified through high-resolution weighing lysimeters and a few additional measurements. Their main occurrence during night-time underlines the necessity to consider ecosystem water fluxes at high temporal resolution and with 24-hour coverage.
... Another optimality-based partitioning method is the P18 method, which is developed using a big-leaf canopy model (Perez-Priego et al., 2018). P18 method is the most physiologically based among these methods. ...
... This result is consistent with previous findings from Nelson et al. (2020), who reported that the N18 method yielded the highest T/ET value (0.77) across 251 FLUXNET sites followed by Z16 method (0.52) and P18 produced the lowest T/ET value of 0.45. The usage of P18 method is clearly limited by that there are no sufficient studies to prove the rationality of approximating C 4 plants via the big-leaf approach (Perez-Priego et al., 2018). But even for C 3 plants, the systematic uncertainty of partitioning results is likely to be associated with the parameter settings of the big leaf model. ...
Partitioning of evapotranspiration (ET) is important for understanding surface-atmosphere interactions, hydrological cycle, and plant water use strategy. Here, we applied seven widely used eddy covariance (EC)-based methods and 15-year EC measurements in a winter wheat-summer maize rotation cropland in North China Plain to partition ET into soil evaporation (E) and plant transpiration (T). Then the two-stage theory of bare soil evaporation was employed to evaluate these partitioning methods. This innovative evaluation approach is particularly suitable for this kind of ecosystem, requires no direct measurements of ET components, and avoids spatial mismatching between the source areas of reference values and EC-based ET. Combining the two-stage theory and the meta-analysis, we found that among seven partitioning methods, only the Transpiration Estimation Algorithm (TEA) (hereafter, N18 method) utilizing a machine learning approach not only simulated the dynamics of 14-day transpiration fraction of ET (T/ET) quite well, but also yielded reliable 14-day and mean growing season magnitudes of T/ET for both crops. Furthermore, we developed a new partitioning method based on the stomatal slope parameter in the optimality-based unified stomatal optimization (USO) model. The newly developed method showed similar performances with N18 method on partitioning ET of both crops at our site. By using the N18 method and the newly developed method, we revealed that the multi-year mean growing season T/ET (± standard deviation) was 0.72 ± 0.03 and 0.77 ± 0.04 for maize and wheat, respectively. For the interannual variability of ET and its components, only T of maize increased significantly during 2005-2019 at our site. Moreover, it was found that E had the highest interannual variability followed by T and then T/ET for both crops.
... The transpiration (T) component accounts for water loss from the leaf stomata of the sparse tree component, seasonal grasses, and the minor forb component. The evaporation (E) component is 5 large following rain events, as intercepted water and near-surface soil water evaporate; the latter may continue over periods longer than a week (Perez-Priego et al., 2018). The partition of ET between E and T may affect the net radiation (Rn) and surface temperature on short timescales (sub-daily). ...
... For a Mediterranean tree-grass savanna, T/ET was shown to rarely exceeded 0.8 (Perez-Priego et al., 2018). In contrast to the Mediterranean site, the Welgegund site has sandy soil, deep-rooted trees, and no clay horizon close to the soil surface. ...
The role of precipitation (P) variability on evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E) from savannas, continues to draw significant research interest given its relevance to a number of eco-hydrological applications. Our study reports on six years of measured ET and estimated T and E from a grazed savanna grassland in Welgegund, South Africa. Annual P varied significantly in amount (508 to 672 mm yr−1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T was nearly constant, 331 ± 11 mm yr−1 (T/ET = 0.52), for the four wet years with frequent early wet-season rainfall, whereas annual T was 268 and 175 mm yr−1 during the dry years. Annual T/ET was linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grass and constant annual tree transpiration covering 15 % of the landscape. However, grass transpiration declines during dry spells. Moreover, grasses respond to water availability with a dieback-regrowth pattern, reducing leaf area and transpiration during drought. These changes lead to an anomalous monthly T/ET relation to leaf-area index (LAI). The results highlight the role of the C4 grass layer in the hydrological balance and suggest that the grass response to dry spells and drought is reasonably described by precipitation timing.
... The discrepancies between these techniques are caused by lower magnitudes of ET (Figure 3a [61], which was also observed in this study despite the magnitude of these fluxes differing from EddyPro/REddyProc methods. Fluxpart is considerably dependent on leaf WUE estimates, which is frequently not available and therefore estimated by the program [52,53,[78][79][80] tested a few LWUE parameterization scenarios using FVS partitioning and found that component fluxes can be biased by up to 30% based on the accuracy of estimated internal leaf-to-ambient CO 2 , with the poorest performing model being the one that used a constant for internal leaf-toambient CO 2 concentration. In this study, internal leaf CO 2 was assigned a default constant, based on photosynthetic pathway [22], which may have been partly responsible for the inconsistencies between EWUES and EWUEF. ...
... In this study, internal leaf CO 2 was assigned a default constant, based on photosynthetic pathway [22], which may have been partly responsible for the inconsistencies between EWUES and EWUEF. not available and therefore estimated by the program [52,53,[78][79][80] tested a few LWUE parameterization scenarios using FVS partitioning and found that component fluxes can be biased by up to 30% based on the accuracy of estimated internal leaf-to-ambient CO2, with the poorest performing model being the one that used a constant for internal leaf-toambient CO2 concentration. In this study, internal leaf CO2 was assigned a default constant, based on photosynthetic pathway [22], which may have been partly responsible for the inconsistencies between EWUES and EWUEF. ...
Water use efficiency (WUE) can be calculated using a range of methods differing in carbon uptake and water use variable selection. Consequently, inconsistencies arise between WUE calculations due to complex physical and physiological interactions. The purpose of this study was to quantify and compare WUE estimates (harvest or flux-based) for alfalfa (C3 plant) and maize (C4 plant) and determine effects of input variables, plant physiology and farming practices on estimates. Four WUE calculations were investigated: two “harvest-based” methods, using above ground carbon content and either precipitation or evapotranspiration (ET), and two “flux-based” methods, using gross primary productivity (GPP) and either ET or transpiration. WUE estimates differed based on method used at both half-hourly and seasonal scales. Input variables used in calculations affected WUE estimates, and plant physiology led to different responses in carbon assimilation and water use variables. WUE estimates were also impacted by different plant physiological responses and processing methods, even when the same carbon assimilation and water use variables were considered. This study highlights a need to develop a metric of measuring cropland carbon-water coupling that accounts for all water use components, plant carbon responses, and biomass production.
... In the second part of the study, the focus shifted towards the partitioning of the evapotranspiration into its components, namely transpiration (T) and evaporation (E). Recent studies suggest that the T/ET ratio can vary from 30 to 90% (Anderson et al. 2017;Nelson et al. 2020;Perez-Priego et al. 2018;Sun et al. 2022), with large differences mainly due to localized irrigation, in complex agroecosystems, contributions from overstory crop and understory cover crop (Burchard-Levine 2022), or in semiarid natural ecosystems, shrub encroachment into grasslands (Wang et al. 2018). The relevance of this partitioning resides in the estimation of irrigation efficiency, as it allows estimation of the amount of water that is removed from the soil water reserve via a nonbiological process (i.e., soil evaporation) and thus does not contribute to biomass accumulation of the crop. ...
Accurate knowledge of evapotranspiration (ET) and its partitioned components, transpiration (T) and evaporation (E), is essential for improving irrigation water monitoring and management, especially in semi-arid areas. In this study, we conduct an intercomparison between the FEST-2-EWB and the TSEB models over a Californian vineyard. TSEB solves for ET using remotely sensed land surface temperature (LST) and leaf area index as key inputs, computing energy fluxes instantaneously at acquisition time and has been extensively tested over California vineyards. FEST-2-EWB employs an innovative time-continuous formulation that computes LST internally and uses it for model calibration, while simulating soil moisture and the surface energy fluxes. Thus, FEST-2-EWB does not require LST derived from satellite imagery at each timestep. Both models are compared to local eddy covariance (EC) measurements and to modeled soil and canopy temperatures and fluxes. The latent heat flux over the growing season is reproduced with mean biases of + 15 Wm⁻² (TSEB) and + 46 Wm⁻² (FEST-2-EWB). The estimated hourly T from both models is compared to partitioned ET fluxes from EC data obtained from three different methods (flux-variance similarity, FVS; modified relaxed eddy accumulation, MREA; conditional eddy covariance, CEC) that partition ET based on the correlation between CO2 and water vapor exchange at soil surface and plant canopy. Fairly similar RMSE values for T were found for FEST-2-EWB (68 Wm⁻²) and TSEB (56 Wm⁻²). Relative transpiration (T/ET) showed similar seasonal evolutions across both models with a modeled vine T that agreed with both the MREA and CEC estimates. However, the two models differed on the variation of T/ET within each day, with TSEB showing a morning peak and a gradual decline and FEST-2-EWB displaying a stable daytime trend, like those from the partitioning methods.
... In the P model, the LUE principle is analytically derived from the FvCB model via the assumption that key model parameters follow eco-evolutionary optimality principles 66 (Fig. 2b). Inclusion of evolutionary optimality hypotheses in the P model allows prediction of ecosystem-level values of carboxylation capacity at ambient temperature (V cmax ), electron-transport capacity at ambient temperature ( J max ) and the ratio of intercellular to ambient CO 2 (χ) from climate and CO 2 alone 66-69 , χ through the least-cost hypothesis 70,71 , V cmax through the coordination hypothesis (ref. 72) and the ratio of J max to V cmax through a cost-benefit calculation (ref. ...
Remote-sensing-based numerical models harness satellite-borne measurements of light absorption by vegetation to estimate global patterns and trends in gross primary production (GPP) — the basis of the terrestrial carbon cycle. In this Perspective, we discuss the challenges in estimating GPP using these models and explore ways to improve their reliability. Current models vary substantially in their structure and produce differing results, especially regarding temporal trends in GPP. Many models invoke the light use efficiency principle, which links light absorption to photosynthesis and plant biomass production, to estimate GPP. However, these models vary in their assumptions about the controls of light use efficiency and typically depend on many, poorly constrained parameters. Eco-evolutionary optimality principles can greatly reduce parameter requirements, improving the accuracy and consistency of GPP estimates and interpretations of their relationships with environmental drivers. Integrating data across different satellites and sensors, and utilizing auxiliary optical band retrievals, could enhance spatiotemporal resolution and improve model-based detection of vegetation physiology, including drought stress. Extending and harmonizing the eddy-covariance flux-tower network will support systematic evaluation of GPP models. Improved reliability of GPP and biomass production estimates will better characterize temporal variation and advance understanding of the response of the terrestrial carbon cycle to environmental change.
... Future studies can also expand this dataset by including additional partitioning models. As an example, Nelson et al. (2020) 405 compared three partitioning algorithms across FLUXNET sites (Perez-Priego et al., 2018;Zhou et al., 2016;Nelson et al., 2018). By comparing different algorithms, we can further explore their uncertainties and focus on model improvement. ...
Long-term time series of transpiration, evaporation, plant photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. To help address this open challenge, we generated a dataset of these four components by implementing five (conventional and novel) approaches to partition total ET and CO2 fluxes into plant and soil fluxes across 47 NEON sites. The final dataset (https://doi.org/10.5281/zenodo.12191876) spans a five-year period and covers various ecosystems, including forests, grasslands, and agricultural terrain. This is the first comprehensive dataset covering such a wide spatial and temporal distribution. Overall, we observed good agreement across most methods for ET components, increasing the reliability of these estimates. Partitioning of CO2 components was found to be less robust and more dependent on prior knowledge of water-use efficiency. This dataset has several potential future applications, such as addressing critical questions regarding the response of ecosystems to extreme weather events, which are expected to become more severe and frequent with climate change.
... Various approaches (physical and machine learning based) have also emerged to partition total measured ET into plant transpiration (T ) and soil evaporation (E) (Eichelmann et al., 2022;X. Li et al., 2019;Nelson et al., 2018;Perez-Priego et al., 2018;Rigden et al., 2018;Scott & Biederman, 2017;Wei et al., 2017;Zhou et al., 2016). However, challenges in model validation have prevented a clear assessment of their accuracy, as illustrated by divergent partitioning estimates in comparison studies (Nelson et al., 2020). ...
While yearly budgets of CO2 flux (Fc) and evapotranspiration (ET) above vegetation can be readily obtained from eddy‐covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely on analysis of conventional high frequency eddy‐covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large‐eddy simulations, which are used to replicate eddy‐covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO2 and water vapor. In addition, best performances for all partitioning methods were found when all four flux components are non‐negligible, and measurements are collected close to the canopy top. Methods relying on the water‐use efficiency (W) perform better when W is known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO2 and water vapor can be used to infer the reliability of different W parameterizations.
... Technically, it is based on the interpretation of the covariance between a turbulent wind (in the direction normal to the sur face) and the concentrations of a constituent (such as CO 2 ) as a flux to or from the surface of interest (i.e. Perez-Priego et al., 2018). Taken together, these technologies have contributed to a better understanding of fundamental processes in the biosphere, such as evapotranspiration (Ryu et al., 2012), and they are indeed understood as a main and very promising tool to enhance the capacity of plant systems to combat or adapt to climate change (Guevara-Escobar et al., 2021;Wiesner et al., 2022). ...
... Deeply, there are also some methods for estimating vegetation T from eddy covariance (EC) datasets: the underlying water use efficiency method (Zhou et al., 2016), the Pérez-Priego method (Perez-Priego et al., 2018) and the transpiration estimation algorithm method (Nelson et al., 2018(Nelson et al., , 2020. As a natural tracer of ecosystem processes, stable water isotope combined with traditional in-situ measurements has been widely used in ET partitioning across different ecosystems and proved to be effective at the plot scale (Han et al., 2022;Schlesinger & Jasechko, 2014;Scott & Biederman, 2017;Wei et al., 2018). ...
Evapotranspiration (ET) partitioning distinguishes the soil evaporation (E) and plant transpiration (T) components and is crucial for understanding the land‐atmosphere interactions and ecosystem water budget. However, the mechanism and controls of ET partitioning for subtropical forests in heterogeneous environments remain poorly understood. Here, we present δ¹⁸O and δ²H of about 1,527 isotope samples including atmospheric water, soil and plant water during different seasons in 2 years of 2020–2021 from a coniferous forest across Southeast China. We used the isotopic mass balance of ecosystem water pools, the Craig‐Gordon model and the Keeling‐Plot method to partition T from ET (T/ET) and quantify the controls on T/ET. Results indicated that the uncertainty in the T/ET was principally from the soil water evaporation (δE) value, about 20–30 cm was found to be a reasonable evaporating front depth for estimating δE in this coniferous forest. T/ET presented a “U” shape diurnal pattern and varied from 66.7% to 89.9%. Isotope‐based T/ET in autumn with high temperatures and little rain was higher than those in the summer and winter seasons. Relative humidity (or vapour pressure deficit) dominated the diurnal T/ET variations (relative contributions of > 40%) in summer and autumn, while air temperature and soil water content were the main controls in winter. Our study also showed that δ¹⁸O‐derived T/ET was consistent with that of δ²H, although δ²H was found to be more stable in ET partitioning, the dual stable isotope approach should be employed in future studies for the uncertainties brought by samplings or measurements. The agreement between the isotope‐based T/ET and ET partitioning approach that uses eddy covariance and sap flux data was stronger at midday. These isotope‐inferred ET partitioning can inform land surface models and provide more insights into water management in subtropical forests.
... Total forest ET at the ecosystem level, i.e. including soil, understory and overstory vegetation, can be directly measured above the canopy by the eddy covariance (EC) method, which quantifies turbulent biosphereatmosphere exchange using high-frequency measurements of vertical wind velocity and water vapor concentrations (Baldocchi et al., 1988). However, EC measurements above the forest canopy cannot separate ET contributions from the understory (including the soil), nor can they partition the component fluxes of T and E. Both of these objectives typically require additional measurements by, e.g., chambers (Kassuelke et al., 2022;Qubaja et al., 2020;Raz-Yaseef et al., 2012), weighing lysimeters (Hirschi et al., 2017;Liu et al., 2022;Perez-Priego et al., 2017;Sun et al., 2016), sap flow (Vandegehuchte and Steppe, 2013;, or alternatively require modelling approaches based on EC data and water use efficiency (Berkelhammer et al., 2016;Nelson et al., 2018;Perez-Priego et al., 2018;Scott and Biederman, 2017;Zhou et al., 2016), or high-frequency EC measurements for conditional sampling of turbulent eddies (Thomas et al., 2008) and for applying the flux-variance similarity approach (Scanlon and Kustas, 2012;Scanlon and Sahu, 2008;Skaggs et al., 2018;Stoy et al., 2019). These additional measurement methods, however, are typically limited to short campaigns, disturb plants and soil (e.g. ...
Evapotranspiration (ET) from the land surface to the atmosphere is a major component of Earth’s water cycle, and comprises both transpiration (T) of xylem water from plants and evaporation (E) of water from soils and vegetation surfaces. These two component fluxes respond differently to changes in temperature, water availability and atmospheric CO2 concentrations. Concurrent eddy covariance (EC) measurements above and below forest canopies provide a promising approach to partition ET into E and T. However, below-canopy EC measurements are rare, and questions remain regarding their spatial variability, canopy coupling, and temporal dynamics. To address these challenges, we measured and partitioned ET over more than three years, using concurrent above- and below-canopy EC towers in a montane forest at Sagehen Creek in California’s Sierra Nevada mountains. This is the establishing study for the AmeriFlux site US-SHC. The main environmental control for ET was available energy; other important controls were canopy & soil temperature, soil moisture, vapor pressure deficit, and wind speed. Below-canopy measurements at two locations within the above-canopy footprint were similar to one another, suggesting low spatial heterogeneity in understory ET near the creek at our Sagehen site. We observed a total forest ET of 606 ± 50 mm yr-1 with 275 ± 17 mm yr-1 measured in the understory (all mean ± SD) during the water years 2018–2020. Interannual variability in ET and T was small despite large variability in precipitation totals; thus the P–ET water balance was mainly driven by variations in water supply. Partitioning the components of total forest ET at Sagehen with concurrent EC measurements showed that on average, 67–74% of ET originated from T (47% from trees and 20–27% from understory vegetation), while 26–33% were from E (mostly from the understory). Our results demonstrate the potential of concurrent above- and below-canopy EC measurements for ET partitioning.
... ET measurements from eddy covariance can be partitioned into T and E using several methods (Nelson et al., 2018;Perez-Priego et al., 2018;Scanlon and Kustas, 2010;Scott and Biederman, 2017;Zhou et al., 2016). However, some of these methods require long-term (Scott and Biederman, 2017) or high frequency data (Skaggs et al., 2018) that were not available at all of our sites. ...
Land-use and land-cover change (LULCC) can dramatically affect the magnitude, seasonality and main drivers of evaporation (E) and transpiration (T), together as evapotranspiration (ET), with effects on overall ecosystem function, as well as both the hydrological cycle and climate system at multiple scales. Our understanding of tropical ecosystem responses to LULCC and global change processes is still limited, mainly due to a lack of ground-based observations that cover a variety of ecosystems, land-uses and land-covers. In this study, we used a network of nine eddy covariance flux towers installed in natural (forest, savanna, wetland) and managed systems (rainfed and irrigated cropland, pastureland) to explore how LULCC affects ET and its components in the Amazon, Cerrado and Pantanal biomes. At each site, tower-based ET measurements were partitioned into T and E to investigate how these fluxes varied between different land-uses and seasons. We found that ET, T and E decreased significantly during the dry season, except in Amazon forest ecosystems where T rates were maintained throughout the year. In contrast to Amazon forests, Cerrado and Pantanal ecosystems showed stronger stomatal control during the dry season. Cropland and pasture sites had lower ET and T compared to native vegetation in all biomes, but E was greater in Pantanal pasture when compared to Pantanal forest. The T fraction of ET was correlated with LAI and EVI, but relationships were weaker in Amazon forests. Our results highlight the importance of understanding the effects of LULCC on water fluxes in tropical ecosystems, and the implications for climate change mitigation policies and land management.
... ET has been widely assessed using the eddy covariance (EC) method over different landcover types, while the plant transpiration and soil evaporation can be derived via measurements from sap flow systems and lysimeters, respectively. These components (E, T) can also be partitioned from EC fluxes time series using isotope methodologies (Good et al., 2015;Wen et al., 2016), water-carbon coupling approaches such as the underlying water use efficiency (uWUE) (Zhou et al., 2016), Pérez-Priego method (Perez-Priego et al., 2018), Transpiration Estimation Algorithm (TEA) (Nelson et al., 2018) and the Flux Variance Similarity (FVS, (Skaggs et al., 2018)) method. Alternative approaches make use of various ET products derived from land surface models (Haddeland et al., 2011), remote sensing based models Miralles et al., 2011;Mu et al., 2011;Pascolini-Campbell et al., 2021;Song et al., 2018) and machine learning approaches in combination with flux tower measurements, remote sensing and meteorological data (Jung et al., 2019;Jung et al., 2010). ...
The two-source energy balance model coupled with soil moisture (TSEB-SM) was evaluated against observations from a global set of 57 eddy covariance (EC) sites, part of the FLUXNET2015 dataset. In addition, modeled soil
evaporation (E) and transpiration (T) were compared with the values obtained from the Transpiration Estimation Algorithm (TEA) and underlying water use efficiency (uWUE) approaches. The TSEB-SM model framework using near-surface soil moisture improved the agreement to EC-observed sensible and latent heat fluxes, reducing mean
absolute percentage error (MAPE) by about 30% and root mean square error (RMSE) by about 44 W/m2 across all sites. The results show that the advantage of the TSEB-SM model, with respect to the original TSEB, becomes
more evident as the ratio of actual to potential evapotranspiration (AET/PET) decreases. The E and T produced
by TSEB-SM has better correlation with the results of uWUE partitioning than TSEB, especially under low soil
water content condition. Likewise, TSEB-SM is superior to TSEB in simulating T when compared with sap flow
measurements derived from the SAPFLUXNET database. These results imply that the development and application
of TSEB-SM has made significant advances in modeling surface water fluxes, even though uncertainties remain. The approach used in TSEB-SM, driving the model with an extensive remotely sensed parameter set,
gives valuable information on water use and provides an alternative to Global Climate Models where complex interactions of ecosystems are parametrized. Thus, TSEB-SM provides a unique insight into the flow of energy
and the role of surface fluxes in the global water cycle.
... Indeed, this scarcity is a motivating factor behind the development of the SAPFLUXNET database and hence its utilization in this study. While various models have been developed to isolate T from EC-derived measurements of ecosystem E (Nelson et al., 2018;Perez-Priego et al., 2018;Zhou et al., 2016), use of such estimates in isolation as surrogate for a "true" T reference is fraught by the difficulties of dealing with both random and systematic errors (Eliasson et al., 2013;Gruber et al., 2020), to which the deployment of a second reference estimate and the triple collocation technique can serve to overcome (McColl et al., 2014;Miralles et al., 2010;Stoffelen, 1998). Nevertheless, for lack of other benchmarks and to provide additional perspective, a normalized RMSE of ∼20% across a diversity of forested sites (n = 21) may be considered low when compared to those reported in Nelson et al. (2020) for individual sites based on comparision of T SF and T derived from three different water flux partitioning methods (cf. ...
Plain Language Summary
Forests comprise the largest share of Earth's vegetated surface area and play an integral role in its hydrological cycle. Forests transfer moisture from below the surface to the atmosphere via transpiration, affecting surface moisture budgets and weather patterns at local‐to‐regional scales. Our ability to accurately predict transpiration in forests is thus critical to reliable weather prediction and more informed water resource management. The most accurate predictions stem from process‐oriented models with detailed representations of plant hydraulic architecture and leaf stomata regulation. These models, however, rely on inputs that are not widely available and thus are not well‐suited for predictions across broader spatial scales. Here, we sought to identify models that could be readily applied using conventional input data streams to predict daily transpiration across a wide diversity of forested ecosystems and over large spatial scales. This was carried out by evaluating predictions emanating from four models of varying complexity against two independent estimates of daily transpiration. We found the most parsimonious models to be those requiring few meterological variables and one forest structural variable as input, achieving an accuracy 33% higher and explaining 16% greater variance than the most complex models requiring additional meteorological and forest structural variables as input.
... Details on these various methods of partitioning and their challenges are well documented elsewhere (Kool et al., 2014;Stoy et al., 2019). Majority of the methods listed above provide T:ET estimates at the gauging sites (e.g., Black et al., 1969;Li et al., 2019;Nelson et al., 2020;Paul-Limoges et al., 2020;Perez-Priego et al., 2018;Scanlon & Sahu, 2008;Scott & Biederman, 2017;Zhou et al., 2016) or over its flow contribution area (e.g., Good et al., 2015;Jasechko et al., 2013). To obtain spatially explicit estimates of T:ET, numerous alternative indirect methods have been developed. ...
Plain Language Summary
Evapotranspiration (ET) plays a significant role in water and climate cycles by affecting the energy and water balance over the land surface which in turn mediates the land‐atmosphere interactions. ET is composed of two primary components that is, direct evaporation (E) and plant transpiration (T). Partitioning total ET into its individual components (E and T) is of significant importance for better assessment of both regional and global water budgets. One of the primary approaches to partition ET over large areas is by using vegetation indices (VI), which indirectly capture plants' biophysical state. This approach has been used to partition ET in different landscapes, but its efficacy has not been tested in disturbed ecosystems, which cover a large fraction of Earth's vegetated area. Here, we assess the effectiveness of this VI‐based ET partitioning approach in disturbed (i.e., grazed) ecosystems. We find that the VI‐based ET partitioning introduces large errors in disturbed systems. Further investigation identifies conditions that can be used to filter‐out regions where the VI‐based partition is likely to be more (or less) effective.
... Scott and Biederman (2017) developed a method to partition ET at arid sites only using multi-year EC estimates of ET and gross primary production (GPP). The method performed well at water-limited sites over time periods during which the linear regression between GPP and ET has a positive ET axis intercept, thus allowing to estimate E. Other new modeling approaches suggested to partition ET at EC sites based on a Shuttleworth-Wallace two-source model (Hu et al., 2009), or based on the Penman-Monteith model where ecosystem conductance is decomposed into soil and canopy conductances (Li et al., 2019), or based on optimality principles (Perez-Priego et al., 2018), or based on water use efficiency (WUE) derived from the coupling of GPP and T (Nelson et al., 2018). Other studies have also suggested to partition global ET using the relationship between T/ET and leaf area index (LAI) for different ecosystems Wei et al., 2017). ...
Reducing water losses in agriculture needs a solid understanding of when evaporation (E) losses occur and how much water is used through crop transpiration (T). Partitioning ecosystem T is however challenging, and even more so when it comes to short‐statured crops, where many standard methods lead to inaccurate measurements. In this study, we combined biometeorological measurements with a Soil‐Plant‐Atmosphere Crop (SPA‐Crop) model to estimate T and E at a Swiss cropland over two crop seasons with winter cereals. We compared our results with two data‐driven approaches: The Transpiration Estimation Algorithm (TEA) and the underlying Water Use Efficiency (uWUE). Despite large differences in the productivity of both years, the T to evapotranspiration (ET) ratio had relatively similar seasonal and diurnal dynamics, and averaged to 0.72 and 0.73. Our measurements combined with a SPA‐Crop model provided T estimates similar to the TEA method, while the uWUE method produced systematically lower T even when the soil and leaves were dry. T was strongly related to the leaf area index, but additionally varied due to climatic conditions. The most important climatic drivers controlling T were found to be the photosynthetic photon flux density (R² = 0.84 and 0.87), and vapor pressure deficit (R² = 0.86 and 0.70). Our results suggest that site‐specific studies can help establish T/ET ratios, as well as identify dominant climatic drivers, which could then be used to partition T from reliable ET measurements. Moreover, our results suggest that the TEA method is a suitable tool for ET partitioning in short‐statured croplands.
... Unlike other plant-based methods, such as sap flux methods, optical dendrometers are very simple and easy to install, insensitive to external temperature variation, and very responsive to rapid changes in Ψ stem (Fig. 1). Compared with microclimatological techniques (Bowen ratio and eddy covariance) which provide estimates of evapotranspiration, incorporating both plant and soil water loss (Williams et al., 2004;Tang et al., 2006;Schlesinger and Jasechko, 2014;Perez-Priego et al., 2018), the optical technique measures plant transpiration alone, thus making it suitable for studying spatial and temporal dynamics of species-specific water use and carbon assimilation in mixed stands, and the responses to changes in climate in both natural and agricultural systems. This method can also be used, if scaled up to stand or regional level, as an independent ground-based method to validate models partitioning evaporation and vegetation transpiration (Lawrence et al., 2007;Sutanto et al., 2012), and as a tool to quantify irrigation demands in agricultural systems. ...
Plant transpiration is an inevitable consequence of photosynthesis and has a huge impact on the terrestrial carbon and water cycle, yet accurate and continuous monitoring of its dynamics is still challenging. Under well-watered conditions, canopy transpiration (Ec) could potentially be continuously calculated from stem water potential (Ψstem), but only if the root to stem hydraulic conductance (Kr-s) remains constant and plant capacitance is relatively small. We tested whether such an approach is viable by investigating whether Kr-s remains constant under a wide range of daytime transpiration rates in non-water-stressed plants. Optical dendrometers were used to continuously monitor tissue shrinkage, an accurate proxy of Ψstem, while Ec was manipulated in three species with contrasting morphological, anatomical and phylogenetic identities: Tanacetum cinerariifolium, Zea mays and Callitris rhomboidea. In all species we found Kr-s to remain constant across a wide range of Ec, meaning that the dynamics of Ψstem could be used to monitor Ec. This was evidenced by the close agreement between measured Ec and that predicted from optically measured Ψstem. These results suggest that optical dendrometers enable both plant hydration and Ec to be monitored non-invasively and continuously in a range of woody and herbaceous species. This technique presents new opportunities to monitor transpiration under laboratory and field conditions in a diversity of woody, herbaceous and grassy species.
... Thus, the effect of soil surface evaporation (Ke) on the Kcb values is insignificant, especially when using subsurface drip irrigation when Ke is near to zero, while transpiration potentially occurs without any limitation, for more details see Campos et al. (2017). In fact, soil evaporation can hardly fall to zero, even for dry ecosystems Perez-Priego et al. (2018). ETo values were collected at the automated weather station near the study site. ...
The increasing pressure on water resources in agricultural areas requires the implementation of innovative tools and solutions to improve irrigation water management. Against that background, this research presents the application of a remote sensing-based methodology for estimating actual evapotranspiration (ETa) based on two-source energy balance model (TSEB) and remote sensing-water balance (RSWB) coupling for sugarcane crop in Brazil using the hybrid model Spatial EvapoTranspiration Modeling Interface (SETMI). Estimated results through SETMI and field data using the eddy covariance system (EC) considering two growing seasons were used to validate the energy balance components and ETa. In addition, the basal crop coefficient as a function of the spectral reflectance (Kcbrf) was developed through the soil-adjusted vegetation index (SAVI) and observed ET. Modeled energy balance components showed a strong correlation to the ground data from EC, with ET presenting R² equal to 0.94 and a Pearson correlation coefficient (ρ) equal to 0.88. Regarding Kcbrf, the Kcb-SAVI relationship for sugarcane presented a high correlation with an R² value of 0.85 and an "ρ" equal to 0.92. On average, considering the whole season, Kcb was equal to 0.75 and 0.73 for the 4th ratoon and 5th ratoon, respectively. Overall, the average Kc throughout the period was 0.73 and 0.70 for the 4th and 5th ratoons respectively, and the maximum Kc of about 1.23 for both growing seasons. On average, accumulated ETa presented 1025 mm resulting in ETa rates of 2.9 mm per day considering the two seasons. Crop water productivity (WP) obtained values similar between the seasons, averaging 12.6, 21.7, and 12.3 kg m⁻³ for WPp+i, WPi and WPET, respectively. The SETMI hybrid model produced suitable estimated daily ETa values over the two growing seasons through remote sensing based on the Kcb-SAVI relationship and good performance of TSEB model during the evaluated growing periods confirming the applicability of the model under tropical conditions in Brazil focusing on improving irrigation management in sugarcane crop.
... This is especially relevant within an agronomic point of view, where irrigation strategies may want to reduce water losses from E compared to T, since vegetation T is intrinsically linked to crop biomass production. However, despite growing research interest in ET partitioning (T/ET; Nelson et al. 2020;Stoy et al. 2019), separating T and E remains a challenge due to their similar signals and complex relation with soil moisture, meteorology, and plant physiology (Perez-Priego et al. 2018;Scott and Biederman 2017). Several in situ T/ET measurements techniques have been developed (Anderson et al. 2017;Kool et al. 2014); however, these often rely on tenuous assumptions and are not spatially distributed nor inferable to the larger landscape or regional scales. ...
Improved accuracy of evapotranspiration (ET) estimation, including its partitioning between transpiration (T) and surface evaporation (E), is key to monitor agricultural water use in vineyards, especially to enhance water use efficiency in semi-arid regions such as California, USA. Remote-sensing methods have shown great utility in retrieving ET from surface energy balance models based on thermal infrared data. Notably, the two-source energy balance (TSEB) has been widely and robustly applied in numerous landscapes, including vineyards. However, vineyards add an additional complexity where the landscape is essentially made up of two distinct zones: the grapevine and the interrow, which is often seasonally covered by an herbaceous cover crop. Therefore, it becomes more complex to disentangle the various contributions of the different vegetation elements to total ET, especially through TSEB, which assumes a single vegetation source over a soil layer. As such, a remote-sensing-based three-source energy balance (3SEB) model, which essentially adds a vegetation source to TSEB, was applied in an experimental vineyard located in California's Central Valley to investigate whether it improves the depiction of the grapevine-interrow system. The model was applied in four different blocks in 2019 and 2020, where each block had an eddy-covariance (EC) tower collecting continuous flux, radiometric, and meteorological measurements. 3SEB's latent and sensible heat flux retrievals were accurate with an overall RMSD ~ 50 W/m2 compared to EC measurements. 3SEB improved upon TSEB simulations, with the largest differences being concentrated in the spring season, when there is greater mixing between grapevine foliage and the cover crop. Additionally, 3SEB's modeled ET partitioning (T/ET) compared well against an EC T/ET retrieval method, being only slightly underestimated. Overall, these promising results indicate 3SEB can be of great utility to vineyard irrigation management, especially to improve T/ET estimations and to quantify the contribution of the cover crop to ET. Improved knowledge of T/ET can enhance grapevine water stress detection to support irrigation and water resource management.
Supplementary information:
The online version contains supplementary material available at 10.1007/s00271-022-00787-x.
... Because of the general similarity between sources and sinks of the different components of F c and ET, and given their simultaneous measurements by the same instruments in EC systems, previous studies developed partitioning methods of EC fluxes into their individual components. The level of complexity of recently proposed methods (Li et al., 2019;Nelson et al., 2018;Scanlon and Sahu, 2008;Scott and Biederman, 2017;Thomas et al., 2008;Wei et al., 2017;Zhou et al., 2016) ranges from machine learning approaches (Nelson et al., 2018) and optimization models (Perez-Priego et al., 2018) to regression models (Reichstein et al., 2005;Scott and Biederman, 2017;Zhou et al., 2016). Nonetheless, independent of the complexity of the model, some of these approaches may require knowledge of various environmental variables (e.g., soil temperature), as well as canopy and plant characteristics (e.g., leaf area index and plant conductance), or even variables that are difficult to measure at the scale of interest such as water-use efficiency (WUE). ...
The partitioning of evapotranspiration (ET) into surface evaporation (E) and stomatal-based transpiration (T) is essential for analyzing the water cycle and earth surface energy budget. Similarly, the partitioning of net ecosystem exchange (NEE) of carbon dioxide into respiration (R) and photosynthesis (P) is needed to quantify the controls on its sources and sinks. Promising approaches to obtain these components from field measurements include partitioning models based on analysis of conventional high frequency eddy-covariance data. Here, two such existing approaches, based on similarity between non-stomatal (R and E) and stomatal (P and T) components, are considered: the Modified Relaxed Eddy Accumulation (MREA) and Flux-Variance Similarity (FVS) models. Moreover, a simpler technique is proposed based on a Conditional Eddy-Covariance (CEC) scheme. All approaches were evaluated against independent estimates of transpiration and respiration. The CEC method agreed better with measurements of transpiration over a grass field, with a smaller root mean square error (5.9 W m−2) and higher correlation (0.96). At a forest site, better agreement with soil respiration was found for FVS above the canopy, while CEC and MREA performed better below the canopy. Further application of these methods over a vineyard and a pine forest across different seasons provided insight into the main strengths and weaknesses of each approach. FVS and MREA converge less often when ground flux components dominate, while CEC might result in noisy P and R for small NEE. Finally, in the CEC and MREA framework, the ratio T/ET is shown to be related to the correlation coefficient for carbon dioxide and water vapor concentrations, which can thus be used as a qualitative measure of the importance of stomatal and non-stomatal components. Overall, these results advance the understanding of the skill and agreement of all three methods, and inform future studies where the various approaches can be applied simultaneously and intercompared.
... However, on specific ecosystem scales, observational efforts have confirmed the dominant role of vegetation transpiration in soil moisture loss. Its ratio can be dominated only by soil evaporation in the case of sparse canopies (Perez-Priego et al. 2018;Williams et al. 2004). A data-driven estimate of evapotranspiration revealed that global annual evapotranspiration increased from 1982 to 1997, and then the increase ceased until 2008 due to increased soil moisture limitations (Jung et al. 2010). ...
Changing pathways of soil moisture loss, either directly from soil (evaporation) or indirectly through vegetation (transpiration), are an indicator of ecosystem and land hydrological cycle responses to the changing climate. Based on the ratio of transpiration to evaporation, this paper investigates soil moisture loss pathway changes across China using five reanalysis-type datasets for the past and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections for the future. The results show that across China, the ratio of vegetation transpiration to soil evaporation has generally increased across vegetated land areas, except in grasslands and croplands in north China. During 1981-2014, there was an increase by 51.4 percentage points (pps, p , 0.01) on average according to the reanalyses and by 42.7 pps according to 13 CMIP6 models. The CMIP6 projections suggest that the holistic increasing trend will continue into the twenty-first century at a rate of 40.8 pps for SSP585, 30.6 pps for SSP245, and 21.0 pps for SSP126 shared socioeconomic pathway scenarios for the period 2015-2100 relative to 1981-2014. Major contributions come from the increases in vegetation transpiration over the semiarid and subhumid grasslands, croplands, and forestlands under the influence of increasing temperatures and prolonged growing seasons (with twin peaks in May and October). The future increasing vegetation transpiration ratio in soil moisture loss implies the potential of regional greening across China under global warming and the risks of intensifying land surface dryness and altering the coupling between soil moisture and climate in regions with water-limited ecosystems.
... Because of the general similarity between sources and sinks of the different components of F c and ET, and given their simultaneous measurements by the same instruments in EC systems, previous studies developed partitioning methods of EC fluxes into their individual components. The level of complexity of recently proposed methods (Li et al., 2019;Nelson et al., 2018;Scanlon and Sahu, 2008;Scott and Biederman, 2017;Thomas et al., 2008;Wei et al., 2017;Zhou et al., 2016) ranges from machine learning approaches (Nelson et al., 2018) and optimization models (Perez-Priego et al., 2018) to regression models (Reichstein et al., 2005;Scott and Biederman, 2017;Zhou et al., 2016). Nonetheless, independent of the complexity of the model, some of these approaches may require knowledge of various environmental variables (e.g., soil temperature), as well as canopy and plant characteristics (e.g., leaf area index and plant conductance), or even variables that are difficult to measure at the scale of interest such as water-use efficiency (WUE). ...
The partitioning of evapotranspiration (ET) into surface evaporation (E) and stomatal-based transpiration (T) is essential for analyzing the water cycle and earth surface energy budget. Similarly, the partitioning of net ecosystem exchange (NEE) of carbon dioxide into respiration (R) and photosynthesis (P) is needed to quantify the controls on its sources and sinks. Promising approaches to obtain these components from field measurements include partitioning models based on analysis of conventional high frequency eddy-covariance data. Here, two such existing approaches, based on similarity between non-stomatal (R and E) and stomatal (P and T) components, are considered: the Modified Relaxed Eddy Accumulation (MREA) and Flux-Variance Similarity (FVS) models. Moreover, a simpler technique is proposed based on a Conditional Eddy-Covariance (CEC) scheme. All approaches were evaluated against independent estimates of transpiration and respiration. The CEC method agreed better with measurements of transpiration over a grass field, with a smaller root mean square error (5.9 W m⁻²) and higher correlation (0.96). At a forest site, better agreement with soil respiration was found for FVS above the canopy, while CEC and MREA performed better below the canopy. Further application of these methods over a vineyard and a pine forest across different seasons provided insight into the main strengths and weaknesses of each approach. FVS and MREA converge less often when ground flux components dominate, while CEC might result in noisy P and R for small NEE. Finally, in the CEC and MREA framework, the ratio T/ET is shown to be related to the correlation coefficient for carbon dioxide and water vapor concentrations, which can thus be used as a qualitative measure of the importance of stomatal and non-stomatal components. Overall, these results advance the understanding of the skill and agreement of all three methods, and inform future studies where the various approaches can be applied simultaneously and intercompared.
... Several new methods have recently been proposed to partition λE into T and (soil) evaporation from eddy-covariance observations. The most common formulations depart from the assumption, based on the optimality theory, that WUE scales with VPD (Perez-Priego et al., 2018;Stoy et al., 2019;Zhou and Wang, 2016). In this paper, we use two different methods; first, the one proposed by Lin et al. (2018) and Li and Xiao (2019) in which T is calculated as ...
... During this period the herbaceous layer was completely dry. Therefore, the fluxes measured were representative of only the tree functioning as shown previously Perez-Priego et al., 2018;El-Madany et al., 2020) in which EC-derived water fluxes were compared with independent water fluxes of the herbaceous layer obtained with the lysimeters and sap flow measurements of the trees. An EC system consisting of a three-dimensional sonic anemometer (R3-50; Gill LTD, Lymington, UK) and an infrared gas analyser (LI-7200; Li-Cor Bioscience, Lincoln, NE, USA) was used to measure dry mixing ratios of CO 2 and H 2 O at a height of 15.5 m aboveground. ...
Sun‐induced fluorescence in the far‐red region (SIF) is increasingly used as a remote and proximal‐sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves.
Here, we examined how the 2018 European heatwave (HW) affected the GPP–SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy‐scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence.
The HW caused an inversion of the photosynthesis–fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF.
Our results show the complex modulation of the NPQ–SIF–GPP relationship at an extreme level of heat stress, which is not completely represented in state‐of‐the‐art coupled radiative transfer and photosynthesis models.
... The other key parameter related to water availability for plants and ecosystems is soil water content (SWC), which is not explicitly included in Eq. (3) but still affects WUE through its effect on c i /c a (Perez-Priego et al., 2018). Plants extract water from soil and stomatal conductance responds to soil water availability , leading to changes in GPP and ET. ...
Ecosystem water use efficiency (WUE), defined as the ratio of gross primary production (GPP) over evapotranspiration (ET), is a crucial variable that describes the tradeoff between ecosystem carbon uptake and water loss. However, the effects of soil moisture on WUE remain unclear. Based on hourly observations from 36 forest eddy-covariance sites globally and two percentile-based statistical models, we investigate the effects of soil water supply (i.e., volumetric soil water content, SWC) and vapor pressure deficit (VPD) on carbon-water coupling at the hourly timescale. We further decompose WUE into two components, i.e., the ratio between GPP and plant transpiration (T), WUEt (GPP/T), and the ratio of plant transpiration to total evapotranspiration, T/ET. Results show that the sensitivities of WUE to SWC significantly increased with the increase of VPD. The sensitivities of WUE to SWC are high at high VPD, due to a rapid decrease of T/ET with SWC at high VPD. At low VPD, WUE is largely independent of SWC. The contribution linked to WUEt is much weaker and no significant relationships are observed between the sensitivities of WUEt to SWC and VPD. Our study suggests that the change of ecosystem WUE with SWC is largely due to changes in T/ET, while WUEt remains rather constant.
Long-term time series of transpiration, evaporation, plant net photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. To help address this open challenge, we generated a dataset of these four components by implementing five (conventional and novel) approaches to partition total evapotranspiration (ET) and CO2 fluxes into plant and soil fluxes across 47 National Ecological Observatory Network (NEON) sites. The final dataset (10.5281/zenodo.12191876; ) spans a 5-year period and covers various ecosystems, including forests, grasslands, and agricultural terrain. This is the first comprehensive dataset covering such a wide spatial and temporal distribution. Overall, we observed good agreement across most methods for ET components, increasing confidence in these estimates. Partitioning of CO2 components, on the other hand, was found to be less robust and more dependent on prior knowledge of water use efficiency. This highlights some limitations of these present methods that we discuss, emphasizing the broader challenge posed by the lack of an accurate reference method to validate against. Despite these limitations, this dataset has several potential applications, especially in addressing critical questions regarding the response of ecosystems to extreme weather events, which are expected to become more severe and frequent with climate change.
Terrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.
Changing climatic and environmental scenarios profoundly impact physiological processes, including plant sap flow and gas exchange. Therefore, comprehending how these factors affect sap flow and gas exchange and quantifying their responses is crucial for predicting climate change impacts on global vegetation and ecosystem services. This chapter synthesizes the multifaceted responses of plants to changing climatic and environmental conditions, focusing on the intricate interplay between sap flow and gas exchange within the historical context of forest ecosystems. Sap flow, the transportation of water and solutes through the plant’s vascular system, and gas exchange, primarily involving photosynthesis and respiration, are central to these adaptations. Sap flow is influenced by various factors such as solar radiation, vapor pressure deficit, temperature, and soil moisture. Conversely, gas exchange, mediated by stomatal conductance, determines the balance between photosynthetic CO2 uptake and transpirational water loss, adjusting under stressors like drought, elevated atmospheric CO2 levels, and temperature. This synthesis of current knowledge underscores the necessity for cross-disciplinary research on tree ecophysiology to strengthen predictions of climate impacts on forests. It emphasizes the importance of informing management strategies to promote adaptation and resilience.
Understanding the availability of irrigation water at various growth stages is crucial for guiding agricultural scheduling in arid areas with limited water sources. However, challenges persist in swiftly and synchronously tracking water utilization post-irrigation, especially in discriminating between evaporation and transpiration. By utilizing high-frequency water vapor and carbon dioxide flux data collected by the eddy-covariance system, we employed the evapotranspiration partitioning method based on flux-variance similarity (FVS) to continuously monitor evaporation and transpiration. Through evaluating the effectiveness of the FVS-based partitioning approach with in-situ micro-lysimeters measurements and analyzing the impact of environmental factors using principal component analysis, the partitioning results, incorporating soil moisture content and groundwater levels, were utilized to assess the availability of irrigated water in a wheat field. The findings demonstrated that the refined partitioning method successfully separated evapotranspiration into transpiration and evaporation. Transpiration, contributing to 54.8%, was the primary driver of evapotranspiration (454 mm) during the growth period, while evaporation (205 mm) played a significant role during the seeding and maturation stages. Overall, evapotranspiration consumed 75.5% of the irrigated water (605 mm), with the remaining 24.5% recharged to the groundwater throughout the wheat growth period. These results indicated that 58.4% (comprising evaporation and deep leakage, totaling 353 mm) of irrigation water was not absorbed by the crops. Environmental factors such as air temperature, relative humidity, vapor pressure deficit, and net radiation subtly and consistently influenced the ratio of evaporation and transpiration, with changes in the plant canopy having the most substantial impact on water-use efficiency. Notably, the effects of irrigation events on water vapor fluxes were significant but temporary.
Transpiration (T) is pivotal in the global water cycle, responding to soil moisture, atmospheric stress, climate changes, and human impacts. Therefore, establishing a reliable global transpiration dataset is essential. Collocation analysis methods have been proven effective for assessing the errors in these products, which can subsequently be used for multisource fusion. However, previous results did not consider error cross-correlation, rendering the results less reliable. In this study, we employ collocation analysis, taking error cross-correlation into account, to effectively analyze the errors in multiple transpiration products and merge them to obtain a more reliable dataset. The results demonstrate its superior reliability. The outcome is a long-term daily global transpiration dataset at 0.1°from 2000 to 2020. Using the transpiration after partitioning at FLUXNET sites as a reference, we compare the performance of the merged product with inputs. The merged dataset performs well across various vegetation types and is validated against in-situ observations. Incorporating non-zero ECC considerations represents a significant theoretical and proven enhancement over previous methodologies that neglected such conditions, highlighting its reliability in enhancing our understanding of transpiration dynamics in a changing world.
Understanding the availability of irrigation water at various growth stages is crucial for guiding agricultural scheduling in arid areas with limited water sources. However, challenges persist in swiftly and synchronously tracking water utilization post-irrigation. Depending on the high-frequency water vapor and CO 2 fluxes recorded by the eddy-covariance system, a modified evapotranspiration partitioning method was employed to continuously monitor the availability of irrigated water in a wheat field. Concurrently, in-situ reference measurements were taken using micro-lysimeters to evaluate the effectiveness of this partitioning approach. The findings demonstrated that the refined partitioning method effectively segregated evapotranspiration into transpiration and evaporation. Transpiration, accounting for 54.8%, provided the primary contribution to evapotranspiration (454 mm) during the growth period. Evaporation (205 mm) played a significant role during the seeding and maturation stages. The evapotranspiration consumed 75.5% of the irrigated water (605 mm), and the remaining 24.5% was recharged to the groundwater during the wheat growth period. These results suggest that 58.4% (353 mm) of irrigation water was not absorbed by the crops. Changes in the plant canopy had the most substantial impact on water-use efficiency. Environmental factors like air temperature, relative humidity, vapor pressure deficit, and net radiation subtly and consistently regulated the ratio of evaporation and transpiration. However, the effects of irrigation events on water vapor fluxes were significant, albeit temporary.
Purpose of Review
Harsher abiotic conditions are projected for many woodland areas, especially in already arid and semi-arid climates such as the Southwestern USA. Stomatal regulation of their aperture is one of the ways plants cope with drought. Interestingly, the dominant species in the Southwest USA, like in many other ecosystems, have different stomatal behaviors to regulate water loss ranging from isohydric (e.g., piñon pine) to anisohydric (e.g., juniper) conditions suggesting a possible niche separation or different but comparable strategies of coping with stress. The relatively isohydric piñon pine is usually presumed to be more sensitive to drought or less desiccation tolerant compared to the anisohydric juniper although both species close their stomata under drought to avoid hydraulic failure, and the mortality of one species (mostly piñon) over the other in the recent droughts can be attributed to insect outbreaks rather than drought sensitivity alone. Furthermore, no clear evidence exists demonstrating that iso- or anisohydric strategy increases water use efficiency over the other consistently. How these different stomatal regulatory tactics enable woody species to withstand harsh abiotic conditions remains a subject of inquiry to be covered in this review.
Recent Findings
This contribution reviews and explores the use of simplified stomatal optimization theories to assess how photosynthesis and transpiration respond to warming (H), drought (D), and combined warming and drought (H+D) for isohydric and anisohydric woody plants experiencing the same abiotic stressors. It sheds light on how simplified stomatal optimization theories can separate between photosynthetic and hydraulic acclimation due to abiotic stressors and how the interactive effects of H+D versus H or D alone can be incorporated into future climate models.
Summary
The work here demonstrates how field data can be bridged to simplified optimality principles so as to explore the effect of future changes in temperature and in soil water content on the acclimation of tree species with distinct water use strategies. The results show that the deviations between measurements and predictions from the simplified optimality principle can explain different species’ acclimation behaviors.
Natural resource management requires knowledge of terrestrial evapotranspiration (ET). Most existing numeric models for ET include multiple plant-or ecosystem-type specific parameters that require calibration. This is a significant source of uncertainty under changing environmental conditions. A novel ET model with no type-− specific parameters was developed recently. Based on the coupling the diffusion (via stomata) of water and carbon dioxide (CO 2), this model predicts canopy conductance based on environmental conditions using eco-evolutionary optimality principles that apply to all plant types. Transpiration (T) and ET are calculated from canopy conductance using the Penman-Monteith equation for T and a universal empirical function for the T:ET ratio. Here, the model is systematically evaluated at globally distributed eddy-covariance sites and river basins. Site-scale modelled ET agrees well with flux data (r = 0.81, root mean square error = 0.73 mm day-1 in 23,623 records) and modelled ET in 39 river basins agrees well with the ET estimated by monthly water budget using two runoff datasets (r = 0.62 and 0.66, respectively). Modelled global patterns of ET are consistent with existing global ET products. The model's universality, parsimony and accuracy combine to indicate a broad potential field of application in resource management and global change science.
The input of liquid water to terrestrial ecosystems is composed of rain and non-rainfall water (NRW). The latter comprises dew, fog, and the adsorption of atmospheric vapor on soil particle surfaces. Although NRW inputs can be relevant to support ecosystem functioning in seasonally dry ecosystems, they are understudied, being relatively small, and therefore hard to measure. In this study, we apply a partitioning routine focusing on NRW inputs over 1 year of data from large, high-precision weighing lysimeters at a semi-arid Mediterranean site. NRW inputs occur for at least 3 h on 297 d (81 % of the year), with a mean diel duration of 6 h. They reflect a pronounced seasonality as modulated by environmental conditions (i.e., temperature and net radiation). During the wet season, both dew and fog dominate NRW, while during the dry season it is mostly the soil adsorption of atmospheric water vapor. Although NRW contributes only 7.4 % to the annual water input, NRW is the only water input to the ecosystem during 15 weeks, mainly in the dry season. Benefitting from the comprehensive set of measurements at our experimental site, we show that our findings are in line with (i) independent measurements and (ii) independent model simulations forced with (near-) surface energy and moisture measurements. Furthermore, we discuss the simultaneous occurrence of soil vapor adsorption and negative eddy-covariance-derived latent heat fluxes. This study shows that NRW inputs can be reliably detected through high-resolution weighing lysimeters and a few additional measurements. Their main occurrence during nighttime underlines the necessity to consider ecosystem water fluxes at a high temporal resolution and with 24 h coverage.
Partition of land surface evapotranspiration (ET) into soil evaporation (ET soil) and vegetation transpiration (ET veg) is of great significance for scheduling agricultural irrigation, improving water-use efficiency of crop, and managing water resources. This study made a comprehensive evaluation of one-phase and two-phase surface temperature versus fractional vegetation cover trapezoids in the separation of soil evaporation from vegetation transpiration through analytical deductions and model applications, with surface temperatures at four end-members determined from the layered approach and the patch approach. The two trapezoids were tested on the MODIS data during June to September in 2012 at Daman superstation in Northwest China. The trapezoid-estimated ratios of transpiration to total ET (ET veg /ET) were intercompared with the ET veg /ET from five typical partitioning methods, namely, the stable isotope-method, the underlying water-use efficiency (uWUE) method, the transpiration estimation algorithm (TEA), the Pérez-Priego method, and the Wei method. Results showed that: 1) The two-phase trapezoid integrated with the layered approach and the one-phase trapezoid integrated with the layered approach performed the best and worst with root-mean-square errors of 52.6 W/m 2 and 78.6 W/m 2 , respectively, when the estimated total ET was validated against the Bowen Ratio corrected eddy covariance measurements. 2) The five partitioning methods produced largely different ET veg /ET, with the highest values from the TEA method and the lowest values from the Pérez-Priego method. 3) The estimated vegetation transpiration and ET veg /ET by the two-phase trapezoid were generally higher than those by the one-phase trapezoid. 4) In the intercomparison of ET veg /ET, the layered approach agreed better with the five partitioning methods than the patch approach. 5) The two-phase trapezoid integrated with the layered approach overall produced the most consistent estimates of ET veg /ET with those from the five partitioning methods, with the lowest bias varying between-30.9% and 8.7% and root-mean-square differences varying between 16.8% and 36.8%. In summary, the two-phase trapezoid is theoretically more rational and appears to outperform the one-phase trapezoid. This study is beneficial for a better understanding of the differences, similarities, advantages and weaknesses of the one-phase and two-phase trapezoids in the partition of total ET to its soil and vegetation components.
Partitioning evapotranspiration (ET) into evaporation (E) and transpiration (T) is essential for understanding the global hydrological cycle and improving water resource management. However, ecosystem‐level ET partitioning remains challenging. Here we proposed a novel ET partitioning method that uses the unified stomatal conductance model to estimate T:ET by calculating the ratio of the ecosystem water use efficiency (WUEeco) to leaf WUE (WUEleaf) using half‐hourly flux data. The WUEleaf values estimated by the unified stomatal conductance model agree with an independently measured ratio of hourly photosynthetic rate to T rate (R² = 0.69). The sensitivity of T:ET to the key parameter g1 varied among different plant functional types (PFTs), but the T:ET variations for each PFT were all controlled within 20% when g1 altered within its 95% confidence interval. The mean annual T:ET was highest for evergreen broadleaf forests (0.63), followed by deciduous broad forests (0.62), grasslands (0.52), evergreen needleleaf forests (0.43) and woody savannas (0.40). C3 croplands had higher T:ET (0.65) than C4 croplands (0.48). Seasonal variations in T:ET varied across PFTs and the leaf area index explained about 50% of the variation in seasonal T:ET. Our method is not only consistent with other three EC‐based methods: Z16, N18, and L19 (R = 0.92, 0.94, and 0.68), but also shows high correlations to sap flow‐based T (R = 0.70) at three different forest sites. The method developed in this study provides a feasible and universal approach for ET partitioning of global EC sites, improving the understanding of ecosystem T characteristics across climates and PFTs.
Remote sensing capabilities to monitor evergreen broadleaved vegetation are limited by the low temporal variability in the greenness signal. With canopy greenness computed from digital repeat photography (PhenoCam), we investigated how canopy greenness related to seasonal changes in leaf age and traits as well as variation of trees’ water fluxes (characterized by sap flow and canopy conductance). The results showed that sprouting leaves are mainly responsible for the rapid increase in canopy green chromatic coordinate (GCC) in spring. We found statistically significantly differences in leaf traits and spectral properties among leaves of different leaf ages. Specifically, mean GCC of young leaves was 0.385 ± 0.010 (mean ± SD), while for mature and old leaves was 0.369 ± 0.003, and 0.376 ± 0.004, respectively. Thus, the temporal dynamics of canopy GCC can be explained by changes in leaf spectral properties and leaf age. Sap flow and canopy conductance are both well explained by a combination of environmental drivers and greenness (96% and 87% of the variance explained, respectively). In particular, air temperature and vapor pressure deficit (VPD) explained most of sap flow and canopy conductance variance, respectively. Besides, GCC is an important explanatory variable for variation of canopy conductance may because GCC can represent the leaf ontogeny information. We conclude that PhenoCam GCC can be used to identify the leaf flushing for evergreen broadleaved trees, which carries important information about leaf ontogeny and traits. Thus, it can be helpful for better estimating canopy conductance which constraints water fluxes.
Accurate simulation of plant water use across agricultural ecosystems is essential for various applications, including precision agriculture, quantifying groundwater recharge, and optimizing irrigation rates. Previous approaches to integrating plant water use data into hydrologic models have relied on evapotranspiration (ET) observations. Recently, the flux variance similarity approach has been developed to partition ET to transpiration (T) and evaporation, providing an opportunity to use T data to parameterize models. To explore the value of T/ET data in improving hydrologic model performance, we examined multiple approaches to incorporate these observations for vegetation parameterization. We used ET observations from 5 eddy covariance towers located in the irrigated San Joaquin Valley, California, to parameterize orchard crops in an integrated land surface – groundwater model. By using ET, or both ET and T data, we examined the impact of multiple model parameterization approaches ranging from simple performance metrics to the generalized likelihood uncertainty estimation method. We find that a simple approach of selecting the parameter sets based on ET and T performance metrics works best at these study sites. Selecting parameters based on performance relative to observed ET creates an uncertainty of 27% relative to the observed value. When parameters are selected using both T and ET data, this uncertainty drops to 24%. Similarly, the uncertainty in potential groundwater recharge drops from 63% to 58% when parameters are selected with ET or T and ET data, respectively. While these improvements are minor in an irrigated setting, the value of partitioning ET data may be more useful in non‐irrigated settings. Additionally, using crop type parameters results in similar levels of simulated ET as using site‐specific parameters. Different irrigation schemes create high amounts of uncertainty and highlight the need for accurate estimates of irrigation when performing water budget studies. This article is protected by copyright. All rights reserved.
Partitioning evapotranspiration (ET) into evaporation (E) and plant transpiration (T) is key to understanding ecosystem responses to rainfall variability resulting from climate change. The goal of this study was to quantify T and E using eddy covariance (EC) flux measurements in a tallgrass prairie in consecutive growing seasons with contrasting rainfall regimes. The field measurements were conducted at the National Ecological Observatory Network (NEON) KONZ site, in Kansas, U.S., during the growing seasons of 2017, 2018 and 2019. The ET partitioning was performed using an approach based on the concept of the underlying water use efficiency (uWUE). To evaluate the uWUE approach, we compared daily E estimates obtained from the uWUE with E observations provided by microlysimeters (ML). Green chromatic coordinate (GCC) was used to monitor the vegetation dynamic. In the 2017 growing season, the total rainfall was 23.1% below the site’s long-term average cumulative precipitation. On the other hand, in 2018 and 2019 the accumulated growing season precipitations were 7.2% and 40.2%, respectively, above the long-term precipitation average. The relationship between uWUE approach and ML E measurements showed a Pearson correlation coefficient (r) of 0.42 and a root mean square error (RMSE) of 0.58 mm d⁻¹. The lowest T/ET average value (0.50) was observed in the 2017 growing season, while the largest T/ET average (0.65) was observed in 2018. The correlations between the green chromatic coordinate (GCC) and T/ET were reduced during the growing seasons that experienced drought periods. Air temperature was the main environmental driver of T/ET during the wet growing seasons (r = 0.49 and 0.72). The subsurface soil moisture was the main environmental driver of T/ET during a dry growing season (r = 0.41). These results demonstrate that the precipitation variability not only has a direct impact on the ET components but also modulates the response of those components to other environmental drivers. Since ET partitioning studies at the ecosystem scale are still scarce, our results can improve T/ET and water use efficiency estimates in long-term modelling studies. This will help to better understand how ET in ecosystems will respond to global warming and increased CO2 concentration during wet and dry growing seasons.
Evapotranspiration (ET) links the water and carbon cycles in the atmosphere, hydrosphere, and biosphere. In this study, we develop an ET modelling framework based on the idea that the transpiration and carbon uptake are closely coupled, as predicted by the ‘least-cost hypothesis’ that canopy conductance acclimates to environmental variations. According to eco-evolutionary optimality theory, which has been previously applied in monitoring and modelling land-surface processes, the total costs (per unit carbon fixed) for maintaining transpiration and carboxylation capacities should be minimized. We calculate gross primary production (GPP) assuming that the light- and Rubisco-limited rates of photosynthesis, described by the classical biochemical model of photosynthesis, are coordinated on an approximately weekly time scale. Transpiration (T) is then calculated via acclimated canopy conductance, with no need for plant type- or biome-specific parameters. ET is finally calculated from T using an empirical function of light, temperature, soil water content and foliage cover to predict the T/ET ratio at each site. The GPP estimates were well supported by (weekly) GPP data at 20 widely distributed eddy-covariance flux sites (228 site-years), with correlation coefficients (r) = 0.81 and root-mean-square error (RMSE) = 18.7 gC week⁻¹ and Nash-Sutcliffe efficiency (NSE) = 0.61. Predicted ET was also well supported, with r =0.85, RMSE = 5.5 mm week–1 and NSE = 0.66. Estimated T/ET ratios (0.43–0.74) showed significant positive relationships to radiation, precipitation and green vegetation cover and negative relationships to temperature and modelled T (r = 0.84). Aspects of this framework could be improved, notably the estimation of T/ET. Nonetheless, we see the application of eco-evolutionary principles as a promising direction for water resources research, eliminating the uncertainty introduced by the need to specify multiple parameters, and leveraging the power of remotely sensed vegetation cover data as a key indicator of ecosystem function.
Understanding the annual variation in the transpiration to evapotranspiration ratio (T/ET) remains a challenge and is essential for a thorough understanding of plant responses to the changing environment. We obtained the annual dynamics of T/ET in a semi-arid area of the southwestern United States based on the medians of monthly T/ET derived from two ET partitioning methods. The variation in monthly T/ET was analysed, and plant water use strategies were discussed based on the water use efficiency evaluated by the transpiration (WUE_T). The results show that physiological changes in plants are vital in the annual dynamics of T/ET. Switches in plant physiological status (growth and dormancy) at the start and end of growing seasons induce two dramatic changes in T/ET. Consequently, there is an annual bimodal dynamic of monthly T/ET, with a maximum of 0.84 in October and a minimum of 0.14 in December. Physiological/biochemical variations of plants indicated by solar-induced chlorophyll fluorescence (SIF) are linearly related to T/ET in growing seasons at a monthly scale (T/ET = 3.40×SIF+0.36, R²=0.987). Generally, a stable high monthly T/ET occurs under sufficient energy and water conditions and a highly variable monthly T/ET occurs under energy and water deficient conditions. In semi-arid regions, plants can flexibly adjust WUE_T following different water use strategies to survive or gain as much gross primary productivity (GPP) to compete. Saving water by greatly elevating WUE_T is the main strategy by which plants survive the non-growing season when WUE_T is linearly related to SIF (WUE_T = -114.93×SIF + 3.25, R²=0.970). However, GPP and not WUE_T, becomes the goal of plants in growing seasons when they employ a stable and moderate WUE_T (around 2.1 gC kg⁻¹ H2O) despite the abundant energy and precipitation. There are obvious reductions in WUE_T during the transition periods of the plants’ ‘growth-dormancy’ cycle. Our study highlights the importance of studying annual T/ET variations and water-use efficiency dynamics to better understand water use strategies in plants.
To understand what is driving spatial flux variability within a savanna type ecosystem in central Spain, data of three co-located eddy covariance (EC) towers in combination with hyperspectral airborne measurements and footprint analysis were used. The three EC systems show consistent, and unbiased mass and energy fluxes. Nevertheless, instantaneous between-tower flux differences i.e. paired half hourly fluxes, showed large variability. A period of 13 days around an airborne hyperspectral campaign was analyzed and proved that between-tower differences can be associated to biophysical properties of the sampled footprint areas. At high photo-synthetically active radiation (PAR) net ecosystem exchange (NEE) was mainly controlled by chlorophyll content of the vegetation (estimated through MERIS Terrestrial Chlorophyll Index (MTCI)), while sensible heat flux (H) was driven by surface temperature. The spatial variability of biophysical properties translates into flux variability depending on the location and size of footprints. For H, negative correlations were found with surface temperature for between-tower differences, and for individual towers in time, meaning that higher H was observed at lower surface temperatures. High aerodynamic conductance of tree canopies reduces the canopy surface temperature and the excess energy is relieved as H. Therefore, higher tree canopy fractions yielded to lower surface temperatures and at the same time to higher H. For NEE, flux differences between towers were correlated to differences in MTCI of the respective footprints, showing that higher chlorophyll content of the vegetation translates into more photosynthetic CO 2 uptake, which controls NEE variability. Between-tower differences of latent heat fluxes (LE) showed no consistent correlation to any vegetation index (VI), or structural parameter e.g. tree-grass-fraction. This missing correlation is most likely caused by the large contribution of soil evaporation to ecosystem LE, which is not captured by any of the biophysical and structural properties. To analyze if spatial heterogeneity influences the uncertainty of measured fluxes three different measures of uncertainty were compared: the standard deviation of the marginal distribution sampling (MDS), the two-tower-approach (TTA), and the variance of the covariance (RE). All three uncertainty estimates had similar means and distributions at the individual towers while the methods were significantly different to each other. The uncertainty estimates increased from RE over TTA to MDS, indicating that different components like space, time, meteorology, and phenology are factors, which affect the uncertainty estimates. Differences between uncertainty estimates from the RE and TTA indicate that spatial heterogeneity contributes significantly to the ecosystem-flux uncertainty.
With the eddy-covariance (EC) technique, net fluxes of carbon dioxide (CO2) and other greenhouse gases as well as water and energy fluxes can be measured at the ecosystem level. These flux measurements are a main source for understanding biosphere-atmosphere interactions and feedbacks by cross-site analysis, model-data integration, and up-scaling. The raw fluxes measured with the EC technique require an extensive and laborious data processing. While there are standard tools available in open source environment for processing high-frequency (10 or 20 Hz) data into half-hourly quality checked fluxes, there is a need for more usable and extensible tools for the subsequent post-processing steps. We tackled this need by developing the REddyProc package in the cross-platform language R that provides standard CO2-focused post-processing routines for reading (half-)hourly data from different formats, estimating the uStar threshold, gap-filling, flux-partitioning, and visualizing the results. In addition to basic processing, the functions are extensible and allow easier integration in extended analysis than current tools. New features include cross year processing and a better treatment of uncertainties. A comparison of REddyProc routines with other state-of the art tools resulted in no significant differences in monthly and annual fluxes across sites. Lower uncertainty estimates of both uStar and resulting gap-filled fluxes with the presented tool was achieved by an improved treatment of seasons during the bootstrap analysis. Higher estimates of uncertainty in day-time partitioning resulted from a better accounting of the uncertainty in estimates of temperature sensitivity of respiration. The provided routines can be easily installed, configured, used, and integrated with further analysis. Hence the eddy covariance community will benefit from using the provided package, allowing easier integration of standard post-processing with extended analysis.
Core Ideas
Partitioned evaporation and transpiration is important for validating vadose zone models.
New partitioning approaches overcome spatiotemporal limitations of previous methods.
Some techniques can be applied to existing data to increase E and T observations.
Intercomparisons of approaches at a variety of field sites are needed to better assess each approach.
Partitioning evapotranspiration (ET) into its constituent components, evaporation ( E ) and transpiration ( T ), is important for numerous hydrological purposes including assessing impacts of management practices on water use efficiency and improved validation of vadose zone models that parameterize E and T separately. However, most long‐established observational techniques have short observational timescales and spatial footprints, raising questions about the representativeness of these measurements. In the past 15 yr, new approaches have allowed ET partitioning at spatial scales ranging from the pedon to the globe and at long timescales. In this update, we review some recent methodological developments for partitioning ET. These include micrometeorological approaches involving the flux variance partitioning of high‐frequency eddy covariance observations and proxies for photosynthesis and transpiration such as measurements of isotopic fractionation and carbonyl sulfide uptake. We discuss advances in partitioning the energy balance between canopy and soil using remote sensing. We conclude that the flux variance partitioning with raw eddy covariance data and the two‐source energy balance approaches with remote sensing platforms may have the greatest potential for partitioning ET, in part because large public repositories of eddy covariance and satellite data could be readily reprocessed to partition ET.
The ratio of intercellular to ambient CO2 concentrations (c i/c a) plays a key role in ecophysiology, micrometeorology, and global climatic change. However, systematic investigation on c i/c a variation and its determinants are rare. Here, the c i/c a was derived from measuring ecosystem fluxes in an even-aged monoculture of rubber trees (Hevea brasiliensis). We tested whether c i/c a is constant across environmental gradients and if not, which dominant factors control c i/c a variations. Evidence indicates that c i/c a is not a constant. The c i/c a exhibits a clear "V"-shaped diurnal pattern and varies across the environmental gradient. Water vapor pressure deficit (D) is the dominant factor controls over the c i/c a variations. c i/c a consistently decreases with increasing D. c i/c a decreases with square root of D as predicted by the optimal stomatal model. The D-driving single-variable model could simulate c i/c a as well as that of sophisticated model. Many variables function on longer timescales than a daily cycle, such as soil water content, could improve c i/c a model prediction ability. Ecosystem flux can be effectively used to calculate c i/c a and use it to better understand various natural cycles.
Even though knowing the contributions of transpiration (T), soil and open water evaporation (E), and interception (I) to terrestrial evapotranspiration (ET = T + E + I) is crucial for understanding the hydrological cycle and its connection to ecological processes, the fraction of T is unattainable by traditional measurement techniques over large scales. Previously reported global mean T/(E + T + I) from multiple independent sources, including satellite-based estimations, reanalysis, land surface models, and isotopic measurements, varies substantially from 24% to 90%. Here we develop a new ET partitioning algorithm, which combines global evapotranspiration estimates and relationships between leaf area index (LAI) and T/(E + T) for different vegetation types, to upscale a wide range of published site-scale measurements. We show that transpiration accounts for about 57.2% (with standard deviation ± 6.8%) of global terrestrial ET. Our approach bridges the scale gap between site measurements and global model simulations, and can be simply implemented into current global climate models to improve biological CO2 flux simulations.
The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in
climate. This is especially acute for impacts associated with changes in drought frequency and
intensity on the distribution and timing of water availability. The development of effective
adaptation strategies for these emerging threats to food and water security are compromised by
limitations in our understanding of how natural and managed ecosystems are responding to
changing hydrological and climatological regimes. This information gap is exacerbated by
insufficient monitoring capabilities from local to global scales. Here, we describe how
evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and
climate feedbacks, agricultural management, and water resources, and highlight both the
outstanding science and applications questions and the actions, especially from a space-based
perspective, necessary to advance them.
Sun‐induced fluorescence ( SIF ) in the far‐red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light‐use efficiency and gross primary production ( GPP ). However, the mechanistic link between GPP and SIF is not completely understood.
We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F 760 ) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen–phosphorous ( NP ). Using the soil–canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient‐induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF ) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration ( C ab) and maximum carboxylation capacity ( V cmax )) affected the observed linear relationship between F 760 and GPP .
We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F 760 . Changes in canopy structure mainly control the GPP –F 760 relationship, with a secondary effect of C ab and V cmax .
In order to exploit F 760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered.
Stomatal conductance influences both photosynthesis and transpiration, thereby coupling the carbon and water cycles and affecting surface–atmosphere energy exchange. The environmental response of stomatal conductance has been measured mainly on the leaf scale, and theoretical canopy models are relied on to upscale stomatal conductance for application in terrestrial ecosystem models and climate prediction. Here we estimate stomatal conductance and associated transpiration in a temperate deciduous forest directly on the canopy scale via two independent approaches: (i) from heat and water vapor exchange and (ii) from carbonyl sulfide (OCS) uptake. We use the eddy covariance method to measure the net ecosystem–atmosphere exchange of OCS, and we use a flux-gradient approach to separate canopy OCS uptake from soil OCS uptake. We find that the seasonal and diurnal patterns of canopy stomatal conductance obtained by the two approaches agree (to within ±6 % diurnally), validating both methods. Canopy stomatal conductance increases linearly with above-canopy light intensity (in contrast to the leaf scale, where stomatal conductance shows declining marginal increases) and otherwise depends only on the diffuse light fraction, the canopy-average leaf-to-air water vapor gradient, and the total leaf area. Based on stomatal conductance, we partition evapotranspiration (ET) and find that evaporation increases from 0 to 40 % of ET as the growing season progresses, driven primarily by rising soil temperature and secondarily by rainfall. Counterintuitively, evaporation peaks at the time of year when the soil is dry and the air is moist. Our method of ET partitioning avoids concerns about mismatched scales or measurement types because both ET and transpiration are derived from eddy covariance data. Neither of the two ecosystem models tested predicts the observed dynamics of evaporation or transpiration, indicating that ET partitioning such as that provided here is needed to further model development and improve our understanding of carbon and water cycling.
We evaluated the underlying causes of differences between latent heat (LE) fluxes measured with two enclosed-path eddy covariance systems (EC) at two measurement levels and independent estimates in an open oak-tree grass savannah over almost one year. Estimates of LE of the well-stablished underlying grass by replicated weighable tension-controlled lysimiters (LELys) provided a robust baseline against which to compare EC LE measured at 1.6 m above ground (LE_1.6). Similarly and at the ecosystem level, LE up-scaled using independent measurements (LEupscaled = sap flow + lysimeter) was benchmarked with 3 EC-derived LE estimates: 1) LE measured by a EC tower at 15 m above ground (LE_15), 2) LE_15 adjusted to close the energy balance by using the Bowen ratio method (LEBowen = (Rn − G)/(1 + β)), and 3) LE derived from the energy budget residual (LEresidual = Rn − G − H_15). The sensitivity of EC LE to the correction method applied (i.e. corrections for low-pass filtering effects on water vapor fluctuations and the so-called angle-of-attack correction) and its impact on the energy balance closure (EBC) were also evaluated.
The partitioning of evapotranspiration (ET) between plant transpiration (Et) and direct evaporation (Ed) presents one of the most important and challenging problems for characterizing ecohydrological processes. The exchange of water vapor (q) and CO2 (c) are closely coupled in ecosystem processes and knowledge of their controls can be gained through joint investigation of q and c. In this study we examine the correlation of water vapor and CO2 (Rqc) through analyses of high frequency time series derived from eddy covariance measurements collected over a suburban grass field in Princeton, NJ during a two-year period (2011-2013). Rqc at the study site exhibits pronounced seasonal and diurnal cycles, with maximum anticorrelation in June and maximum decorrelation in January. The diurnal cycle of Rqc varies seasonally and is characterized by a near-symmetric shape with peak anticorrelation around local noon. Wavelet and spectral analyses suggest that q and c are jointly transported for most eddy scales (1-200 m), which is important for flux-variance ET partitioning methods (e.g. Scanlon and Sahu [2008]). The diurnal cycle of the transpiration fraction (ratio of Et to total ET) exhibits an asymmetric diurnal cycle, especially during the warm season, with peak values occurring in the afternoon. These ET partitioning results give similar diurnal and seasonal patterns compared with numerical simulations from the Noah Land Surface Model using the Jarvis canopy resistance formulation. This article is protected by copyright. All rights reserved.
The transpiration (T) fraction of total terrestrial evapotranspiration (ET), T/ET, can vary across ecosystems between 20-95% with a global average of ∼60%. The wide range may either reflect true heterogeneity between ecosystems and/or uncertainties in the techniques used to derive this property. Here we compared independent approaches to estimate T/ET at two needle-leaf forested sites with a factor of three difference in leaf area index (LAI). The first method utilized water vapor isotope profiles and the second derived transpiration through its functional relationship with gross primary production (GPP). We found strong agreement between T/ET values from these two independent approaches although we noted a discrepancy at low vapor pressure deficits (VPD). We hypothesize that this divergence arises because stomatal conductance is independent of humidity at low VPD. Overall, we document significant synoptic-scale T/ET variability but minimal growing season-scale variability. This result indicates a high sensitivity of T/ET to passing weather but convergence towards a stable mean state, which is set by LAI. While changes in T/ET could emerge from a myriad of processes, including above- (LAI) or below- (rooting depth) ground changes, there was only minimal interannual variability and no secular trend in our analysis of T/ET from the 15-year eddy covariance timeseries at Niwot Ridge. If the lack of trend observed here is apparent elsewhere, it suggests that the processes controlling the T and E fluxes are coupled in a way to maintain a stable ratio.
Evapotranspiration (ET) is dominated by transpiration (T) in the terrestrial water cycle. However, continuous measurement of transpiration is still difficult, and the effect of vegetation on ET partitioning is unclear. The concept of underlying water use efficiency (uWUE) was used to develop a new method for ET partitioning by assuming that the maximum, or the potential uWUE is related to T while the averaged or apparent uWUE is related to ET. T/ET was thus estimated as the ratio of the apparent over the potential uWUE using half-hourly flux data from 17 AmeriFlux sites. The estimated potential uWUE was shown to be essentially constant for the 14 sites with a single vegetation type, and was broadly consistent with the uWUE evaluated at the leaf scale. The annual T/ET was the highest for croplands, i.e., 0.69 for corn and 0.62 for soybean, followed by grasslands (0.60) and evergreen needle leaf forests (0.56), and was the lowest for deciduous broadleaf forests (0.52). The enhanced vegetation index (EVI) was shown to be significantly correlated with T/ET and could explain about 75% of the variation in T/ET among the 71 site-years. The coefficients of determination between EVI and T/ET were 0.84 and 0.82 for corn and soybean, respectively, and 0.77 for deciduous broadleaf forests and grasslands, but only 0.37 for evergreen needle leaf forests. This ET partitioning method is sound in principle and simple to apply in practice, and would enhance the value and role of global FLUXNET in estimating T/ET variations and monitoring ecosystem dynamics. This article is protected by copyright. All rights reserved.
This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different nitrogen (N) and phosphorous (P) availability. Sun-induced chlorophyll fluorescence yield computed at 760 nm (Fy760), scaled photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy chambers on the same locations sampled by the spectrometers. We tested whether light-use efficiency (LUE) models driven by remote-sensing quantities (RSMs) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations – relying on the use of Fy760 or sPRI as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (fAPAR) – with those of classical MM. Results showed higher GPP in the N-fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was closely related to the mean of plant N content across treatments (r2 = 0.86, p
Evapotranspiration is a major component of the water cycle, yet only daytime transpiration is currently considered in Earth system and agricultural sciences. This contrasts with physiological studies where 25% or more of water losses have been reported to occur occurring overnight at leaf and plant scales. This gap probably arose from limitations in techniques to measure nocturnal water fluxes at ecosystem scales, a gap we bridge here by using lysimeters under controlled environmental conditions. The magnitude of the nocturnal water losses (12-23% of daytime water losses) in row-crop monocultures of bean (annual herb) and cotton (woody shrub) would be globally an order of magnitude higher than documented responses of global evapotranspiration to climate change (51-98 vs. 7-8 mm yr(-1)). Contrary to daytime responses and to conventional wisdom, nocturnal transpiration was not affected by previous radiation loads or carbon uptake, and showed a temporal pattern independent of vapour pressure deficit or temperature, because of endogenous controls on stomatal conductance via circadian regulation. Our results have important implications from large-scale ecosystem modelling to crop production: homeostatic water losses justify simple empirical predictive functions, and circadian controls show a fine-tune control that minimizes water loss while potentially increasing posterior carbon uptake.
Aims
Gas exchange measurements on individual plants depend largely on chamber systems, and uncertainties and corrections in current flux calculation procedures require further assessment.
Methods
We present a practical study with novel methods for analyses of flux uncertainties in an original chamber design excluding soil fluxes and allowing simultaneous measurements of whole-plant photosynthesis and transpiration.
Results
Results indicate that random errors caused by IRGA noise and the lack of criteria to optimize the time window (TW) of chamber enclosure lead to significant flux uncertainties (12 %). Although enclosure should be rapid to minimize plant disturbances, longer TWs (3 min) increase confidence in flux estimates. Indeterminate stabilization periods in existing calculation protocols cause significant systematic errors. Stabilization times were identified via the change-point detection method, and flux uncertainties were reduced. Photosynthesis was overestimated by up to 28 % when not correcting the evolving CO2 molar fraction for water vapour dilution. Leakage can compromise flux estimates, but was negligible (ca. 2 %) here due to the large chamber-headspace and relatively small values of both collar contact length and closure time.
Conclusions
A bootstrapping, resampling-based flux calculation method is presented and recommended to better assess random errors and improve flux precision. We present practical recommendations for the use of whole-plant chambers.
Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
Scanlon and Sahu (Water Resour Res 44(10):W10418, 2008) proposed an interesting method to estimate assimilation, respiration, evaporation and transpiration directly using high-frequency eddy-covariance measurements. In this note we critically revise this method and, in particular, using the Descartes’ rule of sign, we show that one branch of solutions can be directly neglected reducing the analytical complexity of the procedure. We also discuss the stability of the results of the method with respect to the input parameters, especially to the water-use efficiency.
Semi-arid ecosystems contribute about 40% to global net primary production (GPP) even though water is a major factor limiting carbon uptake. Evapotranspiration (ET) accounts for up to 95% of the water loss and in addition, vegetation can also mitigate drought effects by altering soil water distribution. Hence, partitioning of carbon and water fluxes between the soil and vegetation components is crucial to gain mechanistic understanding of vegetation effects on carbon and water cycling. However, the possible impact of herbaceous vegetation in savanna type ecosystems is often overlooked. Therefore, we aimed at quantifying understory vegetation effects on the water balance and productivity of a Mediterranean oak savanna. ET and net ecosystem CO2 exchange (NEE) were partitioned based on flux and stable oxygen isotope measurements and also rain infiltration was estimated. The understory vegetation contributed importantly to total ecosystem ET and GPP with a maximum of 43 and 51%, respectively. It reached water-use efficiencies (WUE; ratio of carbon gain by water loss) similar to cork-oak trees. The understory vegetation inhibited soil evaporation (E) and, although E was large during wet periods, it did not diminish WUE during water-limited times. The understory strongly increased soil water infiltration, specifically following major rain events. At the same time, the understory itself was vulnerable to drought, which led to an earlier senescence of the understory growing under trees as compared to open areas, due to competition for water. Thus, beneficial understory effects are dominant and contribute to the resilience of this ecosystem. At the same time the vulnerability of the understory to drought suggests that future climate change scenarios for the Mediterranean basin threaten understory development. This in turn will very likely diminish beneficial understory effects like infiltration and ground water recharge and therefore ecosystem resilience to drought.
A comparison of two popular eddy-covariance software packages is presented, namely EddyPro and TK3. Two about one-month long test datasets were processed, representing typical instrumental setups, i.e. CSAT3/LI-7500 above grassland and Solent R3/LI-6262 above a forest. The resulting fluxes and quality flags were compared. Achieving a satisfying agreement and understanding residual discrepancies required several iterations and interventions of different nature, spanning from simple software reconfiguration to actual code manipulations. In this paper, we document our comparison exercise and show that the two software packages can provide utterly satisfying agreement when properly configured. Our main aim, however, is to stress the complexity of performing a rigorous comparison of eddy-covariance software. We show that discriminating actual discrepancies in the results from inconsistencies in the software configuration requires deep knowledge of both software packages and of the eddy-covariance method. In some instances, it may be even beyond the possibility of the investigator who does not have access to and full knowledge of the source code. Being the developers of EddyPro and TK3, we could discuss the comparison at all levels of details and this proved necessary to achieve a full understanding. As a result, we suggest that researchers are more likely to get comparable results when using EddyPro (v5.1.1) and TK3 (v3.11) – at least with the setting presented in this paper - than they are when using any other pair of EC software which did not undergo a similar cross-validation.
As a further consequence, we also suggest that, to the aim of assuring consistency and comparability of centralized flux databases, and for a confident use of eddy fluxes in synthesis studies on the regional, continental and global scale, researchers only rely on software that have been extensively validated in documented intercomparisons.
Stomatal conductances, CO2 assimilation, transpiration and intercellular CO2 mol fractions of Eucalyptus grandis leaves were measured in the field using a portable, controlled environment cuvette. Test leaves were subjected to a range of temperatures, humidities, photon irradiances and external CO2 mol fractions. An empiral function, gsw = g0 + g1 Ahs/(cs-I'), was able to account for steady- state stomatal conductances g*sw, over a wide range of environmental conditions and leaf photosynthetic capacities. In this equation, termed the stomatal constraint function, A is CO2 assimilation rate, hs and cs are relative humidity and CO2 mol fraction at the leaf surface respectively, I' is the CO2 compensation point, g0 is conductance at A = 0 and gl is an empirical coefficient. Equations describing the supply of CO2 through stomata and demand for CO2 in photosynthesis were solved simultaneously with the constraint function to give a combined model of stomatal conductance, CO2 assimilation and intercellular CO2 mol fraction in terms of external environmental factors and several parameters describing C3 photosynthesis. The model provided a good description of experimental observations.
Persistent divergences among the predictions of complex carbon-cycle models
include differences in the sign as well as the magnitude of the response of
global terrestrial primary production to climate change. Such problems with
current models indicate an urgent need to reassess the principles underlying
the environmental controls of primary production. The global patterns of
annual and maximum monthly terrestrial gross primary production (GPP) by
C3 plants are explored here using a simple first-principles model based
on the light-use efficiency formalism and the Farquhar model for C3
photosynthesis. The model is driven by incident photosynthetically active
radiation (PAR) and remotely sensed green-vegetation cover, with additional
constraints imposed by low-temperature inhibition and CO2 limitation.
The ratio of leaf-internal to ambient CO2 concentration in the model
responds to growing-season mean temperature, atmospheric dryness (indexed by
the cumulative water deficit, Δ E) and elevation, based on an optimality
theory. The greatest annual GPP is predicted for tropical moist forests, but
the maximum (summer) monthly GPP can be as high, or higher, in boreal or
temperate forests. These findings are supported by a new analysis of CO2
flux measurements. The explanation is simply based on the seasonal and
latitudinal distribution of PAR combined with the physiology of
photosynthesis. By successively imposing biophysical constraints, it is shown
that partial vegetation cover – driven primarily by water shortage –
represents the largest constraint on global GPP.
We present a two-criteria inverse modeling approach to analyze the effects of seasonal drought on ecosystem gas exchange at three Mediterranean sites. The three sites include two nearly monospecific Quercus ilex L. forests, one on karstic limestone (Puéchabon), the other on fluvial sand with access to groundwater (Castelporziano), and a typical multispecies shrubland on limestone (Arca di Noè). A canopy gas exchange model Process Pixel Net Ecosystem Exchange (PROXELNEE), which contains the Farquhar photosynthesis model coupled to stomatal conductance via the Ball-Berry model, was inverted in order to estimate the seasonal time course of canopy parameters from hourly values of ecosystem gross carbon uptake and transpiration. It was shown that an inverse estimation of leaf-level parameters was impossible when optimizing against ecosystem H2O or CO2 fluxes alone (unidentifiable parameters). In contrast, a criterion that constrained the optimization against both H2O and CO2 fluxes yielded stable estimates of leaf-level parameters. Two separate model inversions were implemented to test two alternative hypotheses about the response to drought: a reduction in active leaf area as a result of patchy stomatal closure or a change in photosynthetic capacities. In contrast to a previously tested hypothesis of classical (uniform) stomatal control, both hypotheses were equally able to describe the seasonality of carbon uptake and transpiration on all three sites, with a decline during the drought and recovery after autumn rainfall. Large reductions of up to 80%, in either active leaf area or photosynthetic capacities, were necessary to describe the observed carbon and water fluxes at the end of the drought period. With a threshold-type relationship, soil water content was an excellent predictor of these changes. With the drought-dependent parameter changes included, the canopy model explains 80–90% of the variance of hourly gross CO2 uptake (root mean squared error (RMSE): 1.1–2.6 μmol m−2 s−1) and 70–80% of the variance of hourly transpiration (RMSE: 0.02–0.03 mm h−1) at all sites. In addition to drought effects, changes in leaf photosynthetic activity not related to water availability, i.e., high spring activity, were detected through the inverse modeling approach. Moreover, our study exemplifies a kind of multiconstraint inverse modeling that can be profitably used for calibrating ecosystem models that are meant for global applications with ecosystem flux data.
1] Future carbon and water fluxes within terrestrial ecosystems will be determined by how stomatal conductance (gs) responds to rising atmospheric CO2 and air temperatures. While both short-and long-term CO2 effects on gs have been repeatedly studied, there are few studies on how gs acclimates to higher air temperatures. Six gs models were parameterized using leaf gas exchange data from black spruce (Picea mariana) seedlings grown from seed at ambient (22/16°C day/night) or elevated (30/24°C) air temperatures. Model performance was independently assessed by how well carbon gain from each model reproduced estimated carbon costs to close the seedlings' seasonal carbon budgets, a 'long-term' indicator of success. A model holding a constant intercellular to ambient CO2 ratio and the Ball-Berry model (based on stomatal responses to relative humidity) could not close the carbon balance for either treatment, while the Jarvis-Oren model (based on stomatal responses to vapor pressure deficit, D) and a model assuming a constant gs each closed the carbon balance for one treatment. Two models, both based on gs responses to D, performed best overall, estimating carbon uptake within 10% of carbon costs for both treatments: the Leuning model and a linear optimization model that maximizes carbon gain per unit water loss. Since gs responses in the optimization model are not a priori assumed, this approach can be used in modeling land-atmosphere exchange of CO2 and water in future climates.
The stomata occupy a central position in the pathways for both the loss of water from plants and the exchange of CO2. It is commonly assumed that they therefore provide the main short-term control of both transpiration and photosynthesis,
though the detailed control criteria on which their movements are based are not well understood and are likely to depend on
the particular ecological situation. This paper first reviews the main methods available for quantifying the control exerted
by stomata over transpiration and photosynthesis in the absence of feedbacks between gasexchange and stomatal function. The
discussion is then extended by using very simple models to investigate the role of stomata in the control of gas exchange
in the presence of hydraulic feedbacks and to clarify the nature of causality in such systems. Comparison of a limited number
of different mechanistic models of stomatal function is used to investigate likely mechanisms underlying stomatal responses
to environment.
Optimization models of stomatal conductance ( g s ) attempt to explain observed stomatal behaviour in terms of cost‐‐benefit tradeoffs. While the benefit of stomatal opening through increased CO 2 uptake is clear, currently the nature of the associated cost(s) remains unclear. We explored the hypothesis that g s maximizes leaf photosynthesis, where the cost of stomatal opening arises from nonstomatal reductions in photosynthesis induced by leaf water stress.
We analytically solved two cases, CAP and MES, in which reduced leaf water potential leads to reductions in carboxylation cap acity ( CAP ) and mes ophyll conductance ( g m ) (MES).
Both CAP and MES predict the same one‐parameter relationship between the intercellular : atmospheric CO 2 concentration ratio ( c i / c a ) and vapour pressure deficit (VPD, D ), viz. c i / c a ≈ ξ /( ξ + √ D ), as that obtained from previous optimization models, with the novel feature that the parameter ξ is determined unambiguously as a function of a small number of photosynthetic and hydraulic variables. These include soil‐to‐leaf hydraulic conductance, implying a stomatal closure response to drought. MES also predicts that g s / g m is closely related to c i / c a and is similarly conservative.
These results are consistent with observations, give rise to new testable predictions, and offer new insights into the covariation of stomatal, mesophyll and hydraulic conductances.
Gross primary production (GPP) - the uptake of carbon dioxide (CO2) by leaves, and its conversion to sugars by photosynthesis - is the basis for life on land. Earth System Models (ESMs) incorporating the interactions of land ecosystems and climate are used to predict the future of the terrestrial sink for anthropogenic CO2¹ . ESMs require accurate representation of GPP. However, current ESMs disagree on how GPP responds to environmental variations 1,2, suggesting a need for a more robust theoretical framework for modelling 3,4 . Here, we focus on a key quantity for GPP, the ratio of leaf internal to external CO2 (χ). χ is tightly regulated and depends on environmental conditions, but is represented empirically and incompletely in today's models. We show that a simple evolutionary optimality hypothesis 5,6 predicts specific quantitative dependencies of χ on temperature, vapour pressure deficit and elevation; and that these same dependencies emerge from an independent analysis of empirical χ values, derived from a worldwide dataset of >3,500 leaf stable carbon isotope measurements. A single global equation embodying these relationships then unifies the empirical light-use efficiency model ⁷ with the standard model of C3 photosynthesis ⁸, and successfully predicts GPP measured at eddy-covariance flux sites. This success is notable given the equation's simplicity and broad applicability across biomes and plant functional types. It provides a theoretical underpinning for the analysis of plant functional coordination across species and emergent properties of ecosystems, and a potential basis for the reformulation of the controls of GPP in next-generation ESMs.
The separate components of evapotranspiration (ET) elucidate the pathways and time scales over which water is returned to the atmosphere, but ecosystem-scale measurements of transpiration (T) and evaporation (E) remain elusive. We propose a novel determination of E and T using multiyear eddy covariance estimates of ET and gross ecosystem photosynthesis (GEP). The method is applicable at water-limited sites over time periods during which a linear regression between GEP (abscissa) and ET (ordinate) yields a positive ET axis intercept, an estimate of E. At four summer-rainfall semiarid sites, T/ET increases to a peak coincident with maximum GEP and remains elevated as the growing season progresses, consistent with previous, direct measurements. The seasonal course of T/ET is related to increasing leaf area index and declining frequency of rainy days—an index of the wet surface conditions that promote E—suggesting both surface and climatic controls on ET partitioning.
In microeconomics, a standard framework is used for determining the optimal input mix for a two‐input production process. Here we adapt this framework for understanding the way plants use water and nitrogen (N) in photosynthesis. The least‐cost input mixture for generating a given output depends on the relative cost of procuring and using nitrogen versus water. This way of considering the issue integrates concepts such as water‐use efficiency and photosynthetic nitrogen‐use efficiency into the more inclusive objective of optimizing the input mix for a given situation. We explore the implications of deploying alternative combinations of leaf nitrogen concentration and stomatal conductance to water, focusing on comparing hypothetical species occurring in low‐ versus high‐humidity habitats. We then present data from sites in both the United States and Australia and show that low‐rainfall species operate with substantially higher leaf N concentration per unit leaf area. The extra protein reflected in higher leaf N concentration is associated with a greater drawdown of internal CO2, such that low‐rainfall species achieve higher photosynthetic rates at a given stomatal conductance. This restraint of transpirational water use apparently counterbalances the multiple costs of deploying high‐nitrogen leaves.
The eddy covariance (EC) method is routinely used to measure net ecosystem fluxes of carbon dioxide (CO2) and evapotranspiration (ET) in terrestrial ecosystems. It is often desirable to partition CO2 flux into gross primary production (GPP) and ecosystem respiration (RE), and to partition ET into evaporation and transpiration. We applied multiple partitioning methods, including the recently-developed flux variance similarity (FVS) partitioning method, to a ten-year record of ET and CO2 fluxes measured using EC at Morgan Monroe State Forest, a temperate, deciduous forest located in south-central Indiana, USA. While the FVS method has previously been demonstrated in croplands and grasslands, this is the first evaluation of the method in a forest. CO2 fluxes were partitioned using nonlinear regressions, FVS, and sub-canopy EC measurements. ET was partitioned using FVS and sub-canopy EC measurements, and sub-canopy potential evapotranspiration was calculated as an additional constraint on forest floor evaporation. Leaf gas exchange measurements were used to parameterize a model of water use efficiency (WUE) necessary for the FVS method. Scaled leaf gas exchange measurements also provided additional independent estimates of GPP and transpiration. There was good agreement among partitioning methods for transpiration and GPP, which also agreed well with scaled leaf gas exchange measurements. There was higher variability among methods for RE and evaporation. The sub-canopy flux method yielded lower estimates of evaporation and RE than FVS and lower estimates of RE than the nonlinear regression method, likely due to the exclusion of flux sources within the canopy but above the top of the sub-canopy tower for the sub-canopy flux method. Based on a sensitivity test, FVS flux partitioning was moderately sensitive to errors in WUE values, and underestimates of WUE significantly reduced the rate at which the algorithm was able to produce a physically valid solution. FVS partitioning has unique potential for retroactive ET partitioning at EC sites, because it relies on the same continuous measurements as EC and does not require additional specialized equipment. FVS also has advantages for partitioning CO2 fluxes, since it does not rely on the mechanistic assumptions necessary for the commonly used nonlinear regression technique.
It was shown over 40 years ago that plants maximize carbon gain for a given rate of water loss if stomatal conductance, gs , varies in response to external and internal conditions such that the marginal carbon revenue of water, ∂A/∂E, remains constant over time. This theory has long held promise for understanding the physiological ecology of water use and for informing models of plant-atmosphere interactions. Full realisation of this potential hinges on three questions: (i) Are analytical approximations adequate for applying the theory at diurnal time scales? (ii) At what time scale is it realistic and appropriate to apply the theory? (iii) How should gs vary to maximize growth over long time scales? We review the current state of understanding for each of these questions and describe future research frontiers. In particular, we show that analytical solutions represent the theory quite poorly, especially when boundary layer or mesophyll resistances are significant; that diurnal variations in hydraulic conductance may help or hinder maintenance of ∂A/∂E, and the matter requires further study; and that optimal diurnal responses are distinct from optimal long-term variations in gs , which emerge from optimal shifts in carbon partitioning at the whole-plant scale.
Convergence of Markov chain simulations can be monitored by measuring the diffusion and mixing of multiple independently-simulated chains, but different levels of convergence are appropriate for different goals. When considering inference from stochastic simulation, we need to separate two tasks: (1) inference about parameters and functions of parameters based on broad characteristics of their distribution, and (2) more precise computation of expectations and other functions of probability distributions. For the first task, there is a natural limit to precision beyond which additional simulations add essentially nothing; for the second task, the appropriate precision must be decided from external considerations. We illustrate with an example from our current research, a hierarchical model of trends in opinions on the death penalty in U.S. states.
Publisher Summary The study of leaf anatomy and of the mechanisms of the opening and closing of stomatal guard cells leads one to suppose that the stomata constitute the main or even the sole regulating system in leaf transpiration. Meteorologists have developed a wide variety of formulae for estimating evaporation from vegetation that are based entirely on weather variables and take no account at all of the species composition or stomatal properties of the transpiring vegetation. These “potential evaporation” formulae are widely and, to a large degree, successfully used for estimating evaporation from vegetation that is not water-stressed. Transpiration depends on stomatal conductance, net radiation receipt and upon air saturation deficit, temperature, and wind speed. Saturation deficit and wind speed vary through leaf boundary layers, through canopies, and through the atmosphere above the canopies. The sensitivity of saturation deficit to changes in stomatal conductance depends on where the saturation deficit is measured. If all of the stomata on a single leaf change aperture in unison, there may be a substantial change in saturation deficit measured at the leaf surface but a negligible change in saturation deficit measured a centimetre or two away, outside the leaf boundary layer.
With supporting experimental evidence from three separate field studies of daily mean evaporation from bare soil with vastly different physical characteristics, it is shown that the process can be described as isothermal linear diffusion in a finite depth domain. The resulting solution leads directly to similarity variables and thus a universal parameterization, which should in principle be applicable to most field soils. In addition, a closed form expression is presented to estimate the weighted mean diffusivity for exponential type soil water diffusivities. In this solution the widely used square root of inverse time proportionality of this phenomenon is its short time version, whereas the exponential decay proportionality, proposed however by several authors for vegetated surfaces, is its long time version. It appears that in many situations the soil layer contributing to evaporation is fairly shallow and only a few tens of centimeters thick.
A compilation of 81 studies that have partitioned evapotranspiration (ET) into its components—transpiration (T) and evaporation (E)—at the ecosystem scale indicates that T accounts for 61% (±15% s.d.) of ET and returns approximately 39 ± 10% of incident precipitation (P) to the atmosphere, creating a dominant force in the global water cycle. T as a proportion of ET is highest in tropical rainforests (70 ± 14%) and lowest in steppes, shrublands and deserts (51 ± 15%), but there is no relationship of T/ET versus P across all available data (R2 = 0.01). Changes to transpiration due to increasing CO2 concentrations, land use changes, shifting ecozones and climate warming are expected to have significant impacts upon runoff and groundwater recharge.
Optimization theories explain a variety of forms and functions in plants. At the leaf scale, it is often hypothesized that carbon gain is maximized, thus providing a quantifiable objective for a mathematical definition of optimality conditions. Eco-physiological trade-offs and limited resource availability introduce natural bounds to this optimization process. In particular, carbon uptake from the atmosphere is inherently linked to water losses from the soil as water is taken up by roots and evaporated. Hence, water availability in soils constrains the amount of carbon that can be taken up and assimilated into new biomass. The problem of maximizing photosynthesis at a given water availability by modifying stomatal conductance, the plant-controlled variable to be optimized, has been traditionally formulated for short time intervals over which soil moisture changes can be neglected. This simplification led to a mathematically open solution, where the undefined Lagrange multiplier of the optimization (equivalent to the marginal water use efficiency, λλ) is then heuristically determined via data fitting. Here, a set of models based on different assumptions that account for soil moisture dynamics over an individual dry-down are proposed so as to provide closed analytical expressions for the carbon gain maximization problem. These novel solutions link the observed variability in λλ over time, across soil moisture changes, and at different atmospheric CO2 concentrations to water use strategies ranging from intensive, in which all soil water is consumed by the end of the dry-down period, to more conservative, in which water stress is avoided by reducing transpiration.
A novel framework is presented for the analysis of ecophysiological field measurements and modelling. The hypothesis 'leaves minimise the summed unit costs of transpiration and carboxylation' predicts leaf-internal/ambient CO2 ratios (ci /ca ) and slopes of maximum carboxylation rate (Vcmax ) or leaf nitrogen (Narea ) vs. stomatal conductance. Analysis of data on woody species from contrasting climates (cold-hot, dry-wet) yielded steeper slopes and lower mean ci /ca ratios at the dry or cold sites than at the wet or hot sites. High atmospheric vapour pressure deficit implies low ci /ca in dry climates. High water viscosity (more costly transport) and low photorespiration (less costly photosynthesis) imply low ci /ca in cold climates. Observed site-mean ci /ca shifts are predicted quantitatively for temperature contrasts (by photorespiration plus viscosity effects) and approximately for aridity contrasts. The theory explains the dependency of ci /ca ratios on temperature and vapour pressure deficit, and observed relationships of leaf δ(13) C and Narea to aridity.
A variety of methods are currently available to partition water vapor
fluxes (into components of transpiration and direct evaporation) and
carbon dioxide fluxes (into components of photosynthesis and
respiration), using chambers, isotopes, and regression modeling
approaches. Here, a methodology is presented that accounts for
correlations between high-frequency measurements of water vapor (q) and
carbon dioxide (c) concentrations being influenced by their
non-identical source-sink distributions and the relative magnitude of
their constituent fluxes. Flux-variance similarity assumptions are
applied separately to the stomatal and the non-stomatal exchange, and
the flux components are identified by considering the q-c correlation.
Water use efficiency for the vegetation, and how it varies with respect
to vapor pressure deficit, is the only input needed for this approach
that uses standard eddy covariance measurements. The method is
demonstrated using data collected over a corn field throughout a growing
season. In particular, the research focuses on the partitioning of the
water flux with the aim of improving how direct evaporation is handled
in soil-vegetation- atmosphere transfer models over the course of
wetting and dry-down cycles.
Numerical solutions of the flow equation for the drying of porous media have been obtained assuming an exponential relationship between diffusivity and water content. Solutions are presented for both semi‐infinite and finite media for isothermal conditions, when gravity is absent or negligible. The rate of drying of laboratory soil columns is in good agreement with the numerical solutions. The rate of drying is controlled largely by the boundary conditions and physical characteristics of the soil that determine the rate of movement of water in the soil in the liquid phase.
ABSTRACTA spectrum of models that estimate assimilation rate A from intercellular carbon dioxide concentration (Ci) and measured stomatal conductance to CO2 (gc) were investigated using leaf-level gas exchange measurements. The gas exchange measurements were performed in a uniform loblolly pine stand (Pinus taeda L.) using the Free Air CO2 Enrichment (FACE) facility under ambient and elevated atmospheric CO2 for 3 years. These measurements were also used to test a newly proposed framework that combines basic properties of the A–Ci curve with a Fickian diffusion transport model to predict the relationship between Ci/Ca and gc, where Ca is atmospheric carbon dioxide concentration. The widely used Ball–Berry model and five other models as well as the biochemical model proposed by Farquhar et al. (1980) were also reformulated to express variations in Ci/Ca as a function of their corresponding driving mechanisms. To assess the predictive capabilities of these approaches, their respective parameters were estimated from independent measurements of long-term stable carbon isotope determinations (δ13C), meteorological variables, and ensemble A–Ci curves. All eight approaches reproduced the measured A reasonably well, in an ensemble sense, from measured water vapour conductance and modeled Ci/Ca. However, the scatter in the instantaneous A estimates was sufficiently large for both ambient and elevated Ca to suggest that other transient processes were not explicitly resolved by all eight parameterizations. An important finding from our analysis is that added physiological complexity in modeling Ci/Ca (when gc is known) need not always translate to increased accuracy in predicting A. Finally, the broader utility of these approaches to estimate assimilation and net ecosystem exchange is discussed in relation to elevated atmospheric CO2.
The measured net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere
reflects the balance between gross CO2 assimilation [gross primary production (GPP)]
and ecosystem respiration (Reco). For understanding the mechanistic responses of ecosystem
processes to environmental change it is important to separate these two flux components. Two
approaches are conventionally used: (1) respiration measurements made at night are extrapolated
to the daytime or (2) light–response curves are fit to daytime NEE measurements and
respiration is estimated from the intercept of the ordinate, which avoids the use of potentially
problematic nighttime data.We demonstrate that this approach is subject to biases if the effect
of vapor pressure deficit (VPD) modifying the light response is not included.We introduce an
algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE,
modified to account for the temperature sensitivity of respiration and the VPD limitation of
photosynthesis. Including the VPD dependency strongly improved the model’s ability to
reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the
reliability of Reco estimates given that the reduction of GPP by VPD may be otherwise
incorrectly attributed to higher Reco. Results from this improved algorithm are compared
against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 gCm�2 yr�1), while errors arising from the random error (median absolute deviation: � 2gCm�2 yr�1) are negligible. Despite sitespecific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and Reco is not spurious but holds true when quasi-independent, i.e. daytime and nighttime based estimates are compared.
Our previous reformulation of Cowan and Farquhar’s optimality hypothesis
of stomatal reg-ulation has resulted in models for photosynthesis and
transpiration which have been readily testable against field data. When
analysing the water use efficiency implied by our previous reformulation of
the optimality hypothesis of stomatal regulation, we discovered an unexpected
property: when stomatal reg-ulation is active, a linear relationship could be
found between transpiration and a term involving water vapour deficit and
photosynthesis. This prediction gives rise to a novel test which requires no
parameter estimation. We conducted such a test in Scots pine, utilising
ca 10 000 measurements of CO2
exchange, transpiration, temperature, PAR, and water vapour concentration,
taken at the SMEAR I measuring station in Finnish Lapland. As predicted, on
clear and sunny days the correlation coefficient of the linear relationship
was as high as 0.99, corroborating our formulation of the optimality
hypothesis.
Gas-exchange measurements on Eucalyptus grandis leaves and data extracted from the literature were used to test a semi-empirical model of stomatal conductance for CO2
gSc=go+a1A/(cs-I) (1+Ds/Do)]
where A is the assimilation rate; Ds and cs are the humidity deficit and the CO2 concentration at the leaf surface, respectively; g0 is the conductance as A → 0 when leaf irradiance → 0; and D0 and a1 are empirical coefficients. This model is a modified version of gsc=a1A hs/cs first proposed by Ball, Woodrow & Berry (1987, in Progress in Photosynthesis Research, Martinus Mijhoff, Publ., pp. 221–224), in which hs is relative humidity. Inclusion of the CO2 compensation point, τ, improved the behaviour of the model at low values of cs, while a hyperbolic function of Ds for humidity response correctly accounted for the observed hyperbolic and linear variation of gsc and ci/cs as a function of Ds, where Ci is the intercellular CO2 concentration. In contrast, use of relative humidity as the humidity variable led to predictions of a linear decrease in gsc and a hyperbolic variation in ci/cs as a function of Ds, contrary to data from E. grandis leaves. The revised model also successfully described the response of stomata to variations in A, Ds and cs for published responses of the leaves of several other species. Coupling of the revised stomatal model with a biochemical model for photosynthesis of C3 plants synthesizes many of the observed responses of leaves to light, humidity deficit, leaf temperature and CO2 concentration. Best results are obtained for well-watered plants.
Keywords:in situ;undisturbed sampling;soil structure;lysimeter vessel;soil processes;soil monolith
Responses of CO2 and water vapor exchange to absolute humidity deficit (AHD) were measured for seedlings of Pinustaeda L. at high and low irradiance in the laboratory. Diurnal patterns of CO2 and water vapor exchange of P. taeda seedlings and trees were monitored in the field. Stomatal behavior was evaluated in relation to a recent hypothesis of "optimal" stomatal behavior, in which changes in stomatal conductance in response to environmental variation are such that water loss is minimized for a given amount of carbon gain. That is, when stomatal behavior is "optimal," the ratio (gain ratio) of the sensitivities of transpiration and net photosynthesis to changes in stomatal conductance is constant.Laboratory and field stomatal behavior generally did not conform with this hypothesis. Under controlled conditions, at high irradiance, the gain ratio increased with AHD. In the field, the gain ratio increased diurnally on most days. Increasing gain ratios were associated with increasing values but relatively uniform values. Uniform gain ratios in the field were observed on some days, associated with uniform environment, constant , or varying values.