Dynamics of carbon and water vapor fluxes in three typical ecosystems of Heihe River Basin, Northwestern China

Understanding the dynamics of carbon and water vapor fluxes in arid inland river basin ecosystems is essential for predicting and assessing the regional carbon-water budget amid climate change. However, studies aiming to unravel the mechanisms driving the variations and coupling process of regional carbon-water budget in a changing environment in arid regions are limited. Here, we used the eddy covariance technique to analyze the relationship between CO2 and H2O fluxes in three typical ecosystems across the upper, middle, and lower reaches of an arid inland river basin in Northwestern China. Our results showed that all ecosystems acted as carbon sinks, with the alpine swamp meadow, cropland, and desert shrubland sequestrating -300.2 ± 0.01, -644.8 ± 2.9, and - 203.7 ± 22.5 g C m-2 yr-1, respectively. Air temperature (Ta) primarily controlled daily gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE) in the irrigated cropland during the growing season, while soil temperature (Ts) and vapor pressure deficit (VPD) regulated these parameters in the alpine swamp meadow and desert shrubland. Additionally, Ta and net radiation (Rn) controlled daily evapotranspiration (ET) in cropland, while Ts and Rn regulated ET at other sites. Consequently, carbon and water vapor fluxes of all three ecosystems tended to be energy-limited during the growing season. The differential responses of carbon and water vapor fluxes in the upper, middle, and lower reaches of these ecosystems to biophysical factors determined their distinct coupling and variations in water use efficiency. Notably, the desert shrub ecosystem in the lower reach of the basin maintained a stable balance between carbon gain and water loss, indicating adaptation to aridity. This study provides valuable insights into the underlying mechanisms behind the changes in carbon and water vapor fluxes and water-use efficiency in arid river basin ecosystems.

Discriminating the impacts of vegetation greening and climate change on the changes in evapotranspiration and transpiration fraction over the Yellow River Basin

Evapotranspiration (ET) is a vital parameter in terrestrial water-energy cycles. The transpiration fraction (TF) is defined as the ratio of transpiration (T) to evapotranspiration (ET), representing the contribution rate of vegetation transpiration to ecosystem ET. Quantifying the relative contributions of vegetation and climate change on the ET and TF dynamic is of great significance to better understand the water budget between the land and atmosphere. Here, we chose Yellow River Basin (YRB) as the study area and analyzed the spatiotemporal changes of ET, T, and TF from 1982 to 2015 using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model. Meanwhile, the relative contributions of vegetation and climate change to ET, T and TF change were quantified. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During 1982-2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a over the YRB during 1982-2015, respectively. The regions with significant increases in ET, T and TF almost covered the whole study area except for the upper reaches of the YRB. Vegetation greening was the main factor for the increase of ET and TF in the YRB and enhanced ET and TF at a rate of 0.72 mm/a and 0.57/a, respectively, which mainly observed in the entire Loess Plateau region (over 50 % of the study area). Precipitation (PRE) was also the dominated factor contributing to the increase in ET and TF, and temperature (TEM) showed a positive correlation with the changes in ET and TF in the most areas of YRB, which jointly dominated ET changes in the upper reaches of the YRB and TF changes in the southern part of the basin. Except for the total effects, leaf area index (LAI) also indirectly promoted ET changes by affecting PRE, TEM and relative humidity (RH). While wind speed (WS) and radiation (RAD) had a relatively weak regulatory effect on the changes in ET and TF. These findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies for local government.

Satellite-based assessment of water use and leaf area efficiencies of dryland conifer forests along an aridity gradient

Dryland forests worldwide are increasingly threatened by drought stress due to climate change. Understanding the relationships between forest structure and function is essential for managing dryland forests to adapt to these changes. We investigated the structure-function relationships in four dryland conifer forests distributed along a semiarid to subhumid climatic aridity gradient. Forest structure was represented by leaf area index (LAI) and function by gross primary productivity (GPP), evapotranspiration (ET), and the derived efficiencies of water use (WUE = GPP/ET) and leaf area (LAE = GPP/LAI). Estimates of GPP and ET were based on the observed relationships between high-resolution vegetation indices from VENμS and Sentinel-2A satellites and flux data from three eddy covariance towers in the study regions between November 2015 to October 2018. The red-edge-based MERIS Terrestrial Chlorophyll Index (MTCI) from VENμS and Sentinel-2A showed strong correlations to flux tower GPP and ET measurements for the three sites (R2cal > 0.91, R2val > 0.84). Using our approach, we showed that as LAI decreased with decreasing aridity index (AI) (i.e., dryer conditions), estimated GPP and ET decreased (R2 > 0.8 to LAI), while WUE (R2 = 0.68 to LAI) and LAE increased. The observed global-scale patterns are associated with a variety of forest vegetation characteristics, at the local scale, such as tree species composition and density. However, our results point towards a canopy-level mechanism, where the ecosystem-LAI and resultant proportion of sun-exposed vs. shaded leaves are primary determinants of WUE and LAE along the studied climatic aridity gradient. This work demonstrates the importance of high-resolution (spatially and spectrally) remote sensing data conjugated with flux tower data for monitoring dryland forests and understanding the intricate structure-function interactions in their response to drying conditions.

Quantifying the policy-driven large scale vegetation restoration effects on evapotranspiration over drylands in China

Evapotranspiration (ET) is a key variable in the water cycle and reflects the ecosystem's feedback into the climate system. However, quantitative studies on the response of ET to large-scale vegetation restoration projects and climate change are still lacking, especially in drylands. To address this deficiency, this research examined the variation in ET since the implementation of restoration projects in the drylands of China in 2000-2018, and utilized quantitative analysis methods to investigate the effects of six environmental factors, including temperature (TEM), precipitation (PRE), solar radiation (RAD), vapour pressure deficit (VPD), soil moisture (SM), and leaf area index (LAI) on ET. Furthermore, a new method was proposed to detect the ET change caused by land use and land cover change (LUCC). The results indicated that ET showed a significant increasing trend (3.54 mm yr-1) during 2000-2018, and PRE was identified as a main influential factor with an ET contribution rate of more than 50%, especially in areas with insignificant vegetation greening. Additionally, the LAI had a major positive impact on ET in the areas of significant vegetation greening, and the contribution rate was nearly 40%. Furthermore, large-scale vegetation restoration expanded the area of high-transpiration vegetation types, and the ΔET (net variable quantity of ET caused by LUCC) increased obviously especially for the changes from cropland and grassland to forest, and barren land to grassland. These findings provide a new perspective for future assessments and further decision making regarding vegetation restoration projects in drylands.

Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset

Large sample datasets of in situ evapotranspiration (ET) measurements with well documented data provenance and quality assurance are critical for water management and many fields of earth science research. We present a post-processed ET oriented dataset at daily and monthly timesteps, from 161 stations, including 148 eddy covariance flux towers, that were chosen based on their data quality from nearly 350 stations across the contiguous United States. In addition to ET, the data includes energy and heat fluxes, meteorological measurements, and reference ET downloaded from gridMET for each flux station. Data processing techniques were conducted in a reproducible manner using open-source software. Most data initially came from the public AmeriFlux network, however, several different networks (e.g., the USDA-Agricultural Research Service) and university partners provided data that was not yet public. Initial half-hourly energy balance data were gap-filled and aggregated to daily frequency, and turbulent fluxes were corrected for energy balance closure error using the FLUXNET2015/ONEFlux energy balance ratio approach. Metadata, diagnostics of energy balance, and interactive graphs of time series data are included for each station. Although the dataset was developed primarily to benchmark satellite-based remote sensing ET models of the OpenET initiative, there are many other potential uses, such as validation for a range of regional hydrologic and atmospheric models.

Evaluating global ecosystem water use efficiency response to drought based on multi-model analysis

Drought has serious consequences on terrestrial ecosystems, particularly for their carbon and water processes. As an important indicator to examine the balance of ecosystem water and carbon cycles, ecosystem water use efficiency (WUE) has been widely used to investigate ecosystem responses to drought. However, the response of WUE to drought and the role of different ecosystem processes in controlling the response of WUE to drought are not well studied. In this paper, we used four WUE datasets from different remote sensing-driven (RS-driven) models and three drought indices (Standardized Precipitation Evapotranspiration Index, soil moisture anomaly index and water storage anomaly-based drought index) to comprehensively investigate the response of WUE to drought and its dominant ecosystem processes during the period of 2001-2018. The results showed the WUE datasets from four different RS-driven models had discrepancies in WUE temporal trends, particularly in tropical and subtropical forest and semi-arid regions. The Spearman correlation analysis revealed that the positive correlations between WUE and drought accounted for more than half of global vegetated lands, while negative relationship mainly occurred in the high latitude regions. We further explored the dominant ecosystem processes (represented by GPP and ET) in controlling WUE response to drought, and found ET controlled WUE-drought relationship in the high latitude areas and semi-arid/sub-humid regions, while GPP dominated it in tropical forest regions. Additionally, the effects of GPP and ET on controlling WUE response to drought were examined to change with different drought indices, especially in the semi-arid regions. Our study suggests multi-model analysis tend to reduce uncertainties in analyzing WUE response to drought caused by a single WUE data. Moreover, our results highlight the different role of ecosystem processes in controlling WUE response to drought and provide new information for the underlying mechanism of drought impacts on ecosystem water and carbon cycles.

The impact of shadows on partitioning of radiometric temperature to canopy and soil temperature based on the contextual two-source energy balance model (TSEB-2T)

Tests of the most recent version of the two-source energy balance model have demonstrated that canopy and soil temperatures can be retrieved from high-resolution thermal imagery captured by an unmanned aerial vehicle (UAV). This work has assumed a linear relationship between vegetation indices (VIs) and radiometric temperature in a square grid (i.e., 3.6 m × 3.6 m) that is coarser than the resolution of the imagery acquired by the UAV. In this method, with visible, near infrared (VNIR), and thermal bands available at the same high-resolution, a linear fit can be obtained over the pixels located in a grid, where the x-axis is a vegetation index (VI) and the y-axis is radiometric temperature. Next, with an accurate VI threshold that separates soil and vegetation pixels from one another, the corresponding soil and vegetation temperatures can be extracted from the linear equation. Although this method is simpler than other approaches, such as TSEB with Priestly-Taylor (TSEB-PT), it could be sensitive to VIs and the parameters that affect VIs, such as shadows. Recent studies have revealed that, on average, the values of VIs, such as normalized difference vegetation index (NDVI) and leaf area index (LAI), that are located in sunlit areas are greater than those in shaded areas. This means that involving or compensating for shadows will affect the linear relationship parameters (slope and bias) between radiometric temperature and VI, as well as thresholds that separate soil and vegetation pixels. This study evaluates the impact of shadows on the retrieval of canopy and soil temperature data from four UAV images before and after applying shadow compensation techniques. The retrieved temperatures, using the TSEB-2T approach, both before and after shadow correction, are compared to the average temperature values for both soil and canopy in each grid. The imagery was acquired by the Utah State University AggieAir UAV system over a commercial vineyard located in California as part of the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program during 2014 to 2016. The results of this study show when it is necessary to employ shadow compensation methods to retrieve vegetation and soil temperature directly.

Effects of extreme changes in precipitation on the physiology of C4 grasses

Climatic patterns are expected to become more extreme, with changes in precipitation characterized by heavier rainfall and prolonged dry periods. Yet, most studies focus on persistent moderate changes in precipitation, limiting our understanding of how ecosystems will function in the future. We examined the effects of extreme changes in precipitation on leaf-level and ecosystem CO₂ and H₂O exchange of three native C4 bunchgrasses (Andropogon gerardii, Panicum virgatum, and Sorghastrum nutans) over 3 years. Grasses were grown in three precipitation treatments: extreme dry, mean, and extreme wet based on historical rainfall records. After 3 years, plants were 45% smaller in the extreme dry treatment relative to the mean and extreme high treatment, which did not differ. We also found that an extreme decrease in precipitation caused reductions of 55, 40, and 40% in leaf-level photosynthesis (A_net), stomatal conductance (g_s), and water use efficiency (WUE), respectively. Extreme increases in precipitation inhibited leaf-level WUE, with a 44% reduction relative to the mean treatment. At the ecosystem level, both an extreme increase and decrease in precipitation reduced net CO₂ and water fluxes relative to plants grown with mean levels of precipitation. Net water fluxes (ET) were reduced by an average of 74% in the extreme dry and extreme wet treatment relative to mean treatment; net carbon fluxes followed a similar trend, with average reductions of 68% (NEE) and 100% (R_e). Unlike moderate climate change, extreme increases in precipitation may be just as detrimental as extreme decreases in precipitation in shifting grassland physiology.