\n Mobile surface waters and soil waters are relatively disconnected on a global scale. Water on land is eventually lost by surface runoff into the oceans or is ultimately sent back to the atmosphere through evapotranspiration processes. Good\n et al.\n determined that 65% of continental water evaporation is from soils, which includes water taken up and transpired by plants (see the Perspective by Brooks). Although just a small fraction of global surface waters pass through soils, individual stream ecosystems may be affected by water quality changes in nearby soils.\n

Evapotranspiration is a key variable and key process in global water cycle, and it is crucial for understanding how anthropogenic and climate changes have impacts on terrestrial water cycle. In the last decade, global vegetation changes are dramatic, reflected by land use and land cover changes and increase in leaf area index. It remains unclear how these changes influence terrestrial evapotranspiration processes. This study uses a coupled evapotranspiration and gross primary product model (PML-V2) that is run at 500 m and 8-day resolutions across the globe to investigate the impacts of vegetation changes on spatial pattern and dynamics of evapotranspiration in the period of 2003-2017. We found that evapotranspiration across the globe has increased noticeably because of vegetation changes, which is characterized by clear regional and non-regional patterns. Transpiration has strongly increased in the central and northern parts of North America, Europe, eastern China, southern Africa, and eastern and northern Australia. Under different land cover types, shrubs and cropland have been influenced strongly, and their impact is stronger in the post-2012 period than that in the pre-2012 period. The recent total increase from these two land cover types amounts to about 0.41 ×103 km3 a-1, which is about 8 times of natural annual runoff from the Yellow River Basin. The results from this study can help improve the understanding of how vegetation changes caused by recent land use and land cover changes influence terrestrial water cycle and the potential local and regional climate change.

蒸散发是陆面水循环的关键环节和过程,是研究水循环对人类活动和气候变化响应的关键要素。过去十几年,全球下垫面的植被变化剧烈,但如何影响全球陆面蒸散发仍未得到清晰的揭示。本文采用500 m分辨率MODIS数据驱动PML-V2模型,定量解析了2003—2017年植被变化对全球陆面蒸散发的影响。结果显示：在全球尺度上,植被变绿使得全球蒸散发呈现显著的增加趋势,使陆地水循环加快;区域尺度上,植被变化对蒸散发的影响则存在明显的地带性和非地带性特征,如在北美洲中北部、欧洲、中国东部、非洲南部和澳大利亚东北部等地区,蒸散发总量的增加主要是由植被蒸腾增加而引起的。分析不同植被功能类型区的贡献显示,下垫面变化对灌木和耕地影响尤为明显,并在2012年以后呈现增强趋势;这2个植被类型区的全球年总蒸散发累积增加量为0.41×10³ km³ a^-1,约为黄河流域多年平均径流量的8倍。该研究结果有助于进一步加强关于下垫面变化对陆地水循环的影响及其可能带来的局部气候变化的认识。

Amazon forests are a key but poorly understood component of the global carbon cycle. If, as anticipated, they dry this century, they might accelerate climate change through carbon losses and changed surface energy balances. We used records from multiple long-term monitoring plots across Amazonia to assess forest responses to the intense 2005 drought, a possible analog of future events. Affected forest lost biomass, reversing a large long-term carbon sink, with the greatest impacts observed where the dry season was unusually intense. Relative to pre-2005 conditions, forest subjected to a 100-millimeter increase in water deficit lost 5.3 megagrams of aboveground biomass of carbon per hectare. The drought had a total biomass carbon impact of 1.2 to 1.6 petagrams (1.2 x 10(15) to 1.6 x 10(15) grams). Amazon forests therefore appear vulnerable to increasing moisture stress, with the potential for large carbon losses to exert feedback on climate change.

The effect of humidity on the gas exchange of leaves of the dicotyledons soybean (Glycine max (L.) Merrill), sunflower (Helianthus annuus L.), jojoba (Simmondsia chinensis (L.) Schneider), and saltbush (Atriplex halimus L.) and the monocotyledons wheat (Triticum aestivum L.), barley (Hordeum vulgare L.) sorghum (Sorghum bicolor (L.) Moench) and barnyard grass (Echinochloa crus-galli (L.) Beauv.) was examined under conditions of adequate soil moisture in a controlled environment. Photosynthesis and stomatal and internal diffusion resistances of whole, attached, single leaves were not affected by changes in humidity as the vapour pressure deficit between the leaf and atmosphere ranged from 8 to 27 mb. Transpiration increased linearly with increasing vapour pressure deficit. Whole plants of barley exhibited a different response. As humidity was increased, photosynthesis increased, transpiration expressed per unit of vapour pressure difference increased, and diffusion resistances became smaller. Reasons for the different behaviour of single leaves and whole plants are suggested. An index for water use efficiency, expressed per millibar of vapour pressure deficit, was calculated for single leaves of each species used in the experiments. This showed that water use efficiency was highest in the C4 xerophytes and lowest in the C3 mesophytes. The effect of environment on water use efficiency is examined using data from the literature.

Global vegetation greening trend stalled after the late 1990s due to increased atmospheric water demand.

Droughts are expected to become more frequent and more intense under climate change. Plant mortality rates and biomass declines in response to drought depend on stomatal and xylem flow regulation. Plants operate on a continuum of xylem and stomatal regulation strategies from very isohydric (strict regulation) to very anisohydric. Coexisting species may display a variety of isohydricity behaviors. As such, it can be difficult to predict how to model the degree of isohydricity at the ecosystem scale by aggregating studies of individual species. This is nonetheless essential for accurate prediction of ecosystem drought resilience. In this study, we define a metric for the degree of isohydricity at the ecosystem scale in analogy with a recent metric introduced at the species level. Using data from the AMSR-E satellite, this metric is evaluated globally based on diurnal variations in microwave vegetation optical depth (VOD), which is directly related to leaf water potential. Areas with low annual mean radiation are found to be more anisohydric. Except for evergreen broadleaf forests in the tropics, which are very isohydric, and croplands, which are very anisohydric, land cover type is a poor predictor of ecosystem isohydricity, in accordance with previous species-scale observations. It is therefore also a poor basis for parameterizing water stress response in land-surface models. For taller ecosystems, canopy height is correlated with higher isohydricity (so that rainforests are mostly isohydric). Highly anisohydric areas show either high or low underlying water use efficiency. In seasonally dry locations, most ecosystems display a more isohydric response (increased stomatal regulation) during the dry season. In several seasonally dry tropical forests, this trend is reversed, as dry-season leaf-out appears to coincide with a shift toward more anisohydric strategies. The metric developed in this study allows for detailed investigations of spatial and temporal variations in plant water behavior.© 2016 John Wiley & Sons Ltd.

Recent decades have been characterized by increasing temperatures worldwide, resulting in an exponential climb in vapor pressure deficit (VPD). VPD has been identified as an increasingly important driver of plant functioning in terrestrial biomes and has been established as a major contributor in recent drought-induced plant mortality independent of other drivers associated with climate change. Despite this, few studies have isolated the physiological response of plant functioning to high VPD, thus limiting our understanding and ability to predict future impacts on terrestrial ecosystems. An abundance of evidence suggests that stomatal conductance declines under high VPD and transpiration increases in most species up until a given VPD threshold, leading to a cascade of subsequent impacts including reduced photosynthesis and growth, and higher risks of carbon starvation and hydraulic failure. Incorporation of photosynthetic and hydraulic traits in 'next-generation' land-surface models has the greatest potential for improved prediction of VPD responses at the plant- and global-scale, and will yield more mechanistic simulations of plant responses to a changing climate. By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of climate impacts can be made.© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.

Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.

Terrestrial ecosystems are essential for food and water security and CO2 uptake. Ecosystem function is dependent on the availability of soil moisture, yet it is unclear how climate change will alter soil moisture limitation on vegetation. Here we use an ecosystem index that distinguishes energy and water limitations in Earth system model simulations to show a widespread regime shift from energy to water limitation between 1980 and 2100. This shift is found in both space and time. While this is mainly related to a reduction in energy-limited regions associated with increasing incoming shortwave radiation, the largest shift towards water limitation is found in regions where incoming shortwave radiation increases are accompanied by soil moisture decreases. We therefore demonstrate a widespread regime shift in ecosystem function that is stronger than implied by individual trends in incoming shortwave radiation, soil moisture and terrestrial evaporation, with important implications for future ecosystem services.

The degree of plant iso/anisohydry is a popular framework for characterising species-specific drought responses. However, we know little about associations between below-ground and above-ground hydraulic traits as well as the broader ecological implications of this framework. For 24 understory shrub species in seasonally dry subtropical coniferous plantations, we investigated contributions of the degree of isohydry to species' resource economy strategies, abundance, and importance value, and quantified the hydraulic conductance (K ) of above-ground and below-ground organs, magnitude of deep water acquisition (WA ), shallow absorptive root traits (diameter, specific root length, tissue density), and resource-use efficiencies (A, maximum photosynthesis rate; PNUE, photosynthetic nitrogen-use efficiency). The extreme isohydric understory species had lower wood density (a proxy for higher growth rates) because their higher WA and whole-plant K allowed higher A and PNUE, and thus did not necessarily show lower abundance and importance values. Although species' K was coordinated with their water foraging capacity in shallow soil, the more acquisitive deep roots were more crucial than shallow roots in shaping species' extreme isohydric behaviour. Our results provide new insights into the mechanisms through which below-ground hydraulic traits, especially those of deep roots, determine species' degree of isohydry and economic strategies.© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.

. High-quality gridded soil moisture products are essential for many Earth system science applications, while the recent reanalysis and\nremote sensing soil moisture data are often available at coarse resolution\nand remote sensing data are only for the surface soil. Here, we present a 1 km resolution long-term dataset of soil moisture derived through machine\nlearning trained by the in situ measurements of 1789 stations over China, named SMCI1.0 (Soil Moisture of China by in situ data, version 1.0). Random forest is used as a robust machine learning approach to predict soil moisture using ERA5-Land time series, leaf area index, land\ncover type, topography and soil properties as predictors. SMCI1.0 provides\n10-layer soil moisture with 10 cm intervals up to 100 cm deep at daily\nresolution over the period 2000–2020. Using in situ soil moisture as the benchmark, two independent experiments were conducted to evaluate the estimation\naccuracy of SMCI1.0: year-to-year (ubRMSE ranges from 0.041 to 0.052 and R ranges from 0.883 to 0.919) and station-to-station experiments (ubRMSE ranges from 0.045 to 0.051 and R ranges from 0.866 to 0.893). SMCI1.0 generally has advantages over other gridded soil moisture products, including ERA5-Land, SMAP-L4, and SoMo.ml. However, the high errors of soil moisture are often located in the North China Monsoon Region. Overall, the highly accurate estimations of both the\nyear-to-year and station-to-station experiments ensure the applicability of\nSMCI1.0 to study the spatial–temporal patterns. As SMCI1.0 is based on in situ data, it can be a useful complement to existing model-based and satellite-based soil moisture datasets for various hydrological,\nmeteorological, and ecological analyses and models. The DOI link for the dataset is http://dx.doi.org/10.11888/Terre.tpdc.272415 (Shangguan et al., 2022).\n

. A process-based methodology is applied to estimate land-surface evaporation from multi-satellite information. GLEAM (Global Land-surface Evaporation: the Amsterdam Methodology) combines a wide range of remotely-sensed observations to derive daily actual evaporation and its different components. Soil water stress conditions are defined from a root-zone profile of soil moisture and used to estimate transpiration based on a Priestley and Taylor equation. The methodology also derives evaporationfrom bare soil and snow sublimation. Tall vegetation rainfall interception is independently estimated by means of the Gash analytical model. Here, GLEAM is applied daily, at global scale and a quarter degree resolution. Triple collocation is used to calculate the error structure of the evaporation estimates and test the relative merits of two different precipitation inputs. The spatial distribution of evaporation – and its different components – is analysed to understand the relative importance of each component over different ecosystems. Annual land evaporation is estimated as 67.9 × 103 km3, 80% corresponding to transpiration, 11% to interception loss, 7% to bare soil evaporation and 2% snow sublimation. Results show that rainfall interception plays an important role in the partition of precipitation into evaporation and water available for runoff at a continental scale. This study gives insights into the relative importance of precipitation and net radiation in driving evaporation, and how the seasonal influence of these controls varies over different regions. Precipitation is recognised as an important factor driving evaporation, not only in areas that have limited soil water availability, but also in areas of high rainfall interception and low available energy.\n

. The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks.\n

. The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project aims to advance the development of land evaporation estimates on global and regional scales. Its main objective is the derivation, validation, and intercomparison of a group of existing evaporation retrieval algorithms driven by a common forcing data set. Three commonly used process-based evaporation methodologies are evaluated: the Penman–Monteith algorithm behind the official Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Global Land Evaporation Amsterdam Model (GLEAM), and the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL). The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets, and the discrete estimation of land evaporation components or sources (i.e. transpiration, interception loss, and direct soil evaporation) are investigated using river discharge data, independent global evaporation data sets and results from previous studies. In a companion article (Part 1), Michel et al. (2016) inspect the performance of these three models at local scales using measurements from eddy-covariance towers and include in the assessment the Surface Energy Balance System (SEBS) model. In agreement with Part 1, our results indicate that the Priestley and Taylor products (PT-JPL and GLEAM) perform best overall for most ecosystems and climate regimes. While all three evaporation products adequately represent the expected average geographical patterns and seasonality, there is a tendency in PM-MOD to underestimate the flux in the tropics and subtropics. Overall, results from GLEAM and PT-JPL appear more realistic when compared to surface water balances from 837 globally distributed catchments and to separate evaporation estimates from ERA-Interim and the model tree ensemble (MTE). Nonetheless, all products show large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into its different components. This observed inter-product variability, even when common forcing is used, suggests that caution is necessary in applying a single data set for large-scale studies in isolation. A general finding that different models perform better under different conditions highlights the potential for considering biome- or climate-specific composites of models. Nevertheless, the generation of a multi-product ensemble, with weighting based on validation analyses and uncertainty assessments, is proposed as the best way forward in our long-term goal to develop a robust observational benchmark data set of continental evaporation.\n

Successfully applied in the carbon research area, sun-induced chlorophyll fluorescence (SIF) has raised the interest of researchers from the water research domain. However, current works focused on the empirical relationship between SIF and plant transpiration (T), while the mechanistic linkage between them has not been fully explored. Two mechanism methods were developed to estimate T via SIF, namely the water-use efficiency (WUE) method and conductance method based on the carbon–water coupling framework. The T estimated by these two methods was compared with T partitioned from eddy covariance instrument measured evapotranspiration at four different sites. Both methods showed good performance at the hourly (R2 = 0.57 for the WUE method and 0.67 for the conductance method) and daily scales (R2 = 0.67 for the WUE method and 0.78 for the conductance method). The developed mechanism methods provide theoretical support and have a great potential basis for deriving ecosystem T by satellite SIF observations.

The opening and closing of plant stomata regulates the global water, carbon and energy cycles. Biophysical feedbacks on climate are highly dependent on transpiration, which is mediated by vegetation phenology and plant responses to stress conditions. Here, we explore the potential of satellite observations of solar-induced chlorophyll fluorescence (SIF)—normalized by photosynthetically-active radiation (PAR)—to diagnose the ratio of transpiration to potential evaporation (‘transpiration efficiency’, τ). This potential is validated at 25 eddy-covariance sites from seven biomes worldwide. The skill of the state-of-the-art land surface models (LSMs) from the eartH2Observe project to estimate τ is also contrasted against eddy-covariance data. Despite its relatively coarse (0.5°) resolution, SIF/PAR estimates, based on data from the Global Ozone Monitoring Experiment 2 (GOME-2) and the Clouds and Earth’s Radiant Energy System (CERES), correlate to the in situ τ significantly (average inter-site correlation of 0.59), with higher correlations during growing seasons (0.64) compared to decaying periods (0.53). In addition, the skill to diagnose the variability of in situ τ demonstrated by all LSMs is on average lower, indicating the potential of SIF data to constrain the formulations of transpiration in global models via, e.g., data assimilation. Overall, SIF/PAR estimates successfully capture the effect of phenological changes and environmental stress on natural ecosystem transpiration, adequately reflecting the timing of this variability without complex parameterizations.

Solar-induced chlorophyll fluorescence (SIF) brings major advancements in measuring terrestrial photosynthesis. Several recent studies have evaluated the potential of SIF retrievals from the Orbiting Carbon Observatory-2 (OCO-2) in estimating gross primary productivity (GPP) based on GPP data from eddy covariance (EC) flux towers. However, the spatially and temporally sparse nature of OCO-2 data makes it challenging to use these data for many applications from the ecosystem to the global scale. Here, we developed a new global ‘OCO-2’ SIF data set (GOSIF) with high spatial and temporal resolutions (i.e., 0.05°, 8-day) over the period 2000–2017 based on a data-driven approach. The predictive SIF model was developed based on discrete OCO-2 SIF soundings, remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological reanalysis data. Our model performed well in estimating SIF (R2 = 0.79, root mean squared error (RMSE) = 0.07 W m−2 μm−1 sr−1). The model was then used to estimate SIF for each 0.05° × 0.05° grid cell and each 8-day interval for the study period. The resulting GOSIF product has reasonable seasonal cycles, and captures the similar seasonality as both the coarse-resolution OCO-2 SIF (1°), directly aggregated from the discrete OCO-2 soundings, and tower-based GPP. Our SIF estimates are highly correlated with GPP from 91 EC flux sites (R2 = 0.73, p < 0.001). They capture the expected spatial and temporal patterns and also have remarkable ability to highlight the crop areas with the highest daily productivity across the globe. Our product also allows us to examine the long-term trends in SIF globally. Compared with the coarse-resolution SIF that was directly aggregated from OCO-2 soundings, GOSIF has finer spatial resolution, globally continuous coverage, and a much longer record. Our GOSIF product is valuable for assessing terrestrial photosynthesis and ecosystem function, and benchmarking terrestrial biosphere and Earth system models.

Spring greening has been widely observed across the Northern Hemisphere (NH) using a remotely sensed vegetation index (e.g., the normalized difference vegetation index, NDVI). However, there is still a debate on the ecological effects of spring greening on seasonal carbon and water budgets. This study jointly investigated the concurrent and lagged effects of spring greening on carbon gain (gross primary productivity, GPP) and water loss (evapotranspiration, ET) in the summer-active ecosystems at mid and high latitudes of NH using remote sensing and multimodel ensemble data during 1982-2013. The results showed that the collective promotion of spring greening to concurrent GPP and ET is widespread despite variations in magnitude and significance. Both beneficial and adverse lagged effects of spring greening on summer GPP commonly appear with an obvious spatial heterogeneity and difference among climate-plant types. However, the expected significant suppression of spring greening to summer GPP was rarely observed even in the areas where spring ET was significantly promoted by spring greening. Nevertheless, when drought was taken into account, the response patterns of spring water use to spring greening varied to some extent, and the adverse lagged effect of spring greening to summer GPP appeared or strengthened in some regions, especially during the years with dry summer. Given the predicted warming of the climate and more frequent climatic extremes, the adverse effect of spring greening should be given more attention.

Both low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates.© 2022. The Author(s).

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg C in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr−1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. In light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems.

\n Plant water stress occurs at the point when soil moisture (SM) limits transpiration, defining a critical SM threshold (θ\n crit\n ). Knowledge of the spatial distribution of θ\n crit\n is crucial for future projections of climate and water resources. Here, we use global eddy covariance observations to quantify θ\n crit\n and evaporative fraction (EF) regimes. Three canonical variables describe how EF is controlled by SM: the maximum EF (EF\n max\n ), θ\n crit\n, and slope (S) between EF and SM. We find systematic differences of these three variables across biomes. Variation in θ\n crit\n, S, and EF\n max\n is mostly explained by soil texture, vapor pressure deficit, and precipitation, respectively, as well as vegetation structure. Dryland ecosystems tend to operate at low θ\n crit\n and show adaptation to water deficits. The negative relationship between θ\n crit\n and S indicates that dryland ecosystems minimize θ\n crit\n through mechanisms of sustained SM extraction and transport by xylem. Our results further suggest an optimal adaptation of local EF-SM response that maximizes growing-season evapotranspiration and photosynthesis.\n

Irrigation is an important adaptation to reduce crop yield loss due to water stress from both soil water deficit (low soil moisture) and atmospheric aridity (high vapor pressure deficit, VPD). Traditionally, irrigation has primarily focused on soil water deficit. Observational evidence demonstrates that stomatal conductance is co-regulated by soil moisture and VPD from water supply and demand aspects. Here we use a validated hydraulically-driven ecosystem model to reproduce the co-regulation pattern. Specifically, we propose a plant-centric irrigation scheme considering water supply-demand dynamics (SDD), and compare it with soil-moisture-based irrigation scheme (management allowable depletion, MAD) for continuous maize cropping systems in Nebraska, United States. We find that, under current climate conditions, the plant-centric SDD irrigation scheme combining soil moisture and VPD, could significantly reduce irrigation water use (-24.0%) while maintaining crop yields, and increase economic profits (+11.2%) and irrigation water productivity (+25.2%) compared with MAD, thus SDD could significantly improve water sustainability.© 2021. The Author(s).

Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, prediction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and insect resistance that allowed development and examination of hypotheses regarding survival and mortality. Multiple mechanisms may cause mortality during drought. A common mechanism for plants with isohydric regulation of water status results from avoidance of drought-induced hydraulic failure via stomatal closure, resulting in carbon starvation and a cascade of downstream effects such as reduced resistance to biotic agents. Mortality by hydraulic failure per se may occur for isohydric seedlings or trees near their maximum height. Although anisohydric plants are relatively drought-tolerant, they are predisposed to hydraulic failure because they operate with narrower hydraulic safety margins during drought. Elevated temperatures should exacerbate carbon starvation and hydraulic failure. Biotic agents may amplify and be amplified by drought-induced plant stress. Wet multidecadal climate oscillations may increase plant susceptibility to drought-induced mortality by stimulating shifts in hydraulic architecture, effectively predisposing plants to water stress. Climate warming and increased frequency of extreme events will probably cause increased regional mortality episodes. Isohydric and anisohydric water potential regulation may partition species between survival and mortality, and, as such, incorporating this hydraulic framework may be effective for modeling plant survival and mortality under future climate conditions.

Terrestrial photosynthesis is regulated by plant phenology and environmental conditions, both of which experienced substantial changes in recent decades. Unlike early-season photosynthesis, which is mostly driven by temperature or wet-season onset, late-season photosynthesis can be limited by several factors and the underlying mechanisms are less understood. Here, we analyze the temperature and water limitations on the ending date of photosynthesis (EOP), using data from both remote-sensing and flux tower-based measurements. We find a contrasting spatial pattern of temperature and water limitations on EOP. The threshold separating these is determined by the balance between energy availability and soil water supply. This coordinated temperature and moisture regulation can be explained by "law of minimum," i.e., as temperature limitation diminishes, higher soil water is needed to support increased vegetation activity, especially during the late growing season. Models project future warming and drying, especially during late season, both of which should further expand the water-limited regions, causing large variations and potential decreases in photosynthesis.