Air Vapor Pressure Deficit Research Articles

Real-Time Assessment of Mandarin Crop Water Stress Index.

The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level of water stress in plants continuously and to provide automatic sensing and controls. This research aimed at determining the viability, efficiency, and swiftness in employing the commercial Workswell WIRIS Agro R infrared camera (WWARIC) in monitoring water stress and scheduling appropriate irrigation regimes in mandarin plants. The experiment used a four-by-three randomized complete block design with 80–100% FC water treatment as full field capacity and three deficit irrigation treatments at 70–75% FC, 60–65% FC, and 50–55% FC. Air temperature, canopy temperature, and vapor pressure deficits were measured and employed to deduce the empirical crop water stress index, using the Idso approach (CWSI(Idso)) as well as baseline equations to calculate non-water stress and water stressed conditions. The relative leaf water content (RLWC) of mandarin plants was also determined for the growing season. From the experiment, CWSI(Idso) and CWSI were estimated using the Workswell Wiris Agro R infrared camera (CWSIW) and showed a high correlation (R2 = 0.75 at p < 0.05) in assessing the extent of water stress in mandarin plants. The results also showed that at an altitude of 12 m above the mandarin canopy, the WWARIC was able to identify water stress using three modes (empirical, differential, and theoretical). The WWARIC’s color map feature, presented in real time, makes the camera a suitable device, as there is no need for complex computations or expert advice before determining the extent of the stress the crops are subjected to. The results prove that this novel use of the WWARIC demonstrated sufficient precision, swiftness, and intelligibility in the real-time detection of the mandarin water stress index and, accordingly, assisted in scheduling irrigation.

Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U.S. Southwest hot drought.

Earth's ecosystems are increasingly threatened by “hot drought,” which occurs when hot air temperatures coincide with precipitation deficits, intensifying the hydrological, physiological, and ecological effects of drought by enhancing evaporative losses of soil moisture (SM) and increasing plant stress due to higher vapor pressure deficit (VPD). Drought‐induced reductions in gross primary production (GPP) exert a major influence on the terrestrial carbon sink, but the extent to which hotter and atmospherically drier conditions will amplify the effects of precipitation deficits on Earth's carbon cycle remains largely unknown. During summer and autumn 2020, the U.S. Southwest experienced one of the most intense hot droughts on record, with record‐low precipitation and record‐high air temperature and VPD across the region. Here, we use this natural experiment to evaluate the effects of hot drought on GPP and further decompose those negative GPP anomalies into their constituent meteorological and hydrological drivers. We found a 122 Tg C (>25%) reduction in GPP below the 2015–2019 mean, by far the lowest regional GPP over the Soil Moisture Active Passive satellite record. Roughly half of the estimated GPP loss was attributable to low SM (likely a combination of record‐low precipitation and warming‐enhanced evaporative depletion), but record‐breaking VPD amplified the reduction of GPP, contributing roughly 40% of the GPP anomaly. Both air temperature and VPD are very likely to continue increasing over the next century, likely leading to more frequent and intense hot droughts and substantially enhancing drought‐induced GPP reductions.

The accuracy improvement of sap flow prediction in Picea crassifolia Kom. based on the back‐propagation neural network model

AbstractTree transpiration is an important water movement process in forest ecosystems, and it plays a decisive role in the coupling feedback of hydrological and ecological processes. Therefore, identifying the impact of different factors on sap flow can promote efficient water management and improve assessment of the climate change impacts. However, the interaction between sap flow and control factors is not clear, and there is no accurate model to predict sap flow change of Picea crassifolia Kom. This study explored the correlation between sap flow and environmental factors and compared the performances of the back‐propagation neural network (BPANN) and multiple regression (MLR) models, and the importance of the time‐lag effect and different soil moisture conditions in the response mechanism of sap flow was also explained. A higher fitting performance was found in the BPANN model (R2 &gt; 0.90) based on the relationships between air temperature (Ta), air relative humidity (RH), solar radiation (Rn) and vapour pressure deficit (VPD) and sap flux density (Q) than that MLR (R2 = 0.8915). The correlation was improved due to the consideration of time‐lag effect. Other variables, such as maximum temperature (Tmax), wind speed (WS) and precipitation (P), explained smaller portions of the variance in sap flow, while minimum temperature (Tmin) and leaf area index (LAI) had almost no effect. Moreover, the R2 of the water stress condition (REW &lt;0.38) was lower than that of the non‐water stress condition (REW ≥0.38), and even lower than the R2 of the whole experimental period. Therefore, the sap flow prediction model based on BPANN could more reasonably explain the nonlinear relationship between transpiration and control factors, which provided a basis for the estimation of plant water‐use and the construction and management of ecological vegetation in alpine arid and semi‐arid areas, especially in response to the continuous enhancement of aridification and climate warming.

Patterns of daily stem growth in different tree species in a warm-temperate forest in northern China

Radial growth in trees responds to environmental changes in various ways ranging from immediate to hysteretic responses. However, species-specific tree radial growth patterns and their responses to short-term weather changes are not fully understood. Here, the daily stem radial changes (SRCs) in four common tree species, linden (Tilia mongolica), birch (Betula dahurica), oak (Quercus wutaishanica) and larch (Larix principis-rupprechtii), were monitored with high-resolution point dendrometers during the main growing seasons in 2017–2019 on Dongling Mountain, northern China. The SRC was differentiated into tree water deficit-induced stem shrinkage (TWD) and growth-induced irreversible stem expansion (GRO) to evaluate species-specific responses to weather variables and short-term drought events. We found that the TWD and GRO of the four species were significantly different. The TWD was influenced primarily by the vapor pressure deficit (VPD), whereas the GRO was influenced primarily by precipitation (P). In linden and birch, a larger proportion of the GRO occurred at higher air temperature (Tmean) and VPD values; in contrast, the range of these changes was lower in oak and larch. With the increased durations of drought periods, oak and larch experienced large and rapid increases in TWD, whereas birch and linden showed small and slow increases. These results indicate that oak and larch would be sensitive to warmer and drier weather conditions predicted for the future, while linden and birch would have a conservative growth strategy. Our results provide further insights into the physiology of these four tree species and allow us to better predict the growth response of forest dynamics under climate change.

Swiss stone pine growth benefits less from recent warming than European larch at a dry-inner alpine forest line as it reacts more sensitive to humidity

High elevation mountain forests in the European Alps are strongly affected by climate change. In this study we aimed to investigate the long- and short-term effects of climate on radial stem growth and tree hydraulics of the two dominant tree species at the forest line of the Eastern central Alps, European larch (Larix decidua Mill. and Swiss stone pine (Pinus cembra L). To this end, we analyzed tree ring widths from stem cores from five sites between 1990 and 2320 m above sea level (a.s.l.) and measured sap flow for three years and radial stem variation for four years at three sites between 1990 and 2100 m a.s.l. in an inner alpine dry valley in Northern Italy. We found that tree ring width of larch responded stronger to temperature and increased more with warming in the last decades than in Swiss stone pine. In the short term, low soil moisture reduced sap flow during the summer in Swiss stone pine but not in larch. Additionally, air vapor pressure deficit clearly reduced the number of days with radial stem growth in Swiss stone pine, leading to lower annual growth than in larch. Consequently, larch at high elevation might actually benefit from climate change at the expense of Swiss stone pine.

Enhancements of Light Use Efficiency by Diffuse Photosynthetically Active Radiation Were More Sensitive to Air Temperature and Vapor Pressure Deficit at Four Forests

Enhancements of Light Use Efficiency by Diffuse Photosynthetically Active Radiation Were More Sensitive to Air Temperature and Vapor Pressure Deficit at Four Forests

Influence of water and nutrients on cork oak radial growth – looking for an efficient fertirrigation regime

The widespread cork oak (Quercus suber L.) mortality and reduced afforestation /regeneration are causing an overall reduction in cork production. To enhance trees’ growth and vitality, afforestation techniques using fertirrigation were tested. The main objective was the promotion of trees’ growth on new dense plantations using minimum water requirements until reaching productive forests. The experimental plot – Irricork – was installed in 2017 in a ≈1 ha stand with 14 years’ age cork oaks summer-fertirrigated since plantation. Four fertirrigation treatments were applied during fertirrigation campaigns. Radial growth, meteorological parameters and fertirrigation volume were measured every 15–30 days over four years. It was observed that weather, tree size, debarking and trees’ intra-competition had a significant effect on radial increments. Fertirrigation significantly enhanced growth during summer drought and decoupled increments from air vapor pressure deficit constraints. There was a linear relationship between trees’ radial increments and fertirrigation volume up to 140 m3 week–1. Above this value, increments were smoother. In conclusion, summer fertirrigation of 140 m3 week–1 efficiently enhanced the radial growth of trees with 50–75 circumference at breast height, under the particular edaphoclimatic conditions of the stand. This study showed to be, therefore, promising in the use of efficient fertirrigation the enhance cork oaks’ radial growth.

Natural variation in stomatal dynamics drives divergence in heat stress tolerance and contributes to seasonal intrinsic water-use efficiency in Vitis vinifera (subsp. sativa and sylvestris).

Stomata control CO2 uptake for photosynthesis and water loss through transpiration, thus playing a key role in leaf thermoregulation, water-use efficiency (iWUE), and plant productivity. In this work, we investigated the relationship between several leaf traits and hypothesized that stomatal behavior to fast (i.e. minutes) environmental changes co-determines, along with steady-state traits, the physiological response of grapevine to the surrounding fluctuating environment over the growing season. No relationship between iWUE, heat stress tolerance, and stomatal traits was observed in field-grown grapevine, suggesting that other physiological mechanisms are involved in determining leaf evaporative cooling capacity and the seasonal ratio of CO2 uptake (A) to stomatal conductance (gs). Indeed, cultivars that in the field had an unexpected combination of high iWUE but low sensitivity to thermal stress displayed a quick stomatal closure to light, but a sluggish closure to increased vapor pressure deficit (VPD) levels. This strategy, aiming both at conserving water under a high to low light transition and in prioritizing evaporative cooling under a low to high VPD transition, was mainly observed in the cultivars Regina and Syrah. Moreover, cultivars with different known responses to soil moisture deficit or high air VPD (isohydric versus anisohydric) had opposite behavior under fluctuating environments, with the isohydric cultivar showing slow stomatal closure to reduced light intensity but quick temporal responses to VPD manipulation. We propose that stomatal behavior to fast environmental fluctuations can play a critical role in leaf thermoregulation and water conservation under natural field conditions in grapevine.

Regional soil moisture prediction system based on Long Short-Term Memory network

In the context of climate change, drought has been recognised as one of the most severe threats for agricultural production since absence of water is one of the most limiting factors for the growth of plants. In this study, a regional system for soil moisture prediction based on ERA5 climate reanalysis dataset, an open-source meteorological dataset issued by Copernicus Climate Change Service, was developed. It consisted of the relevant meteorological parameters for Serbia, during the period 2011–2020. Daily values of maximum and minimum air temperature, precipitation and vapour pressure deficit were used as features, and they were fed to recurrent neural network in order to predict volumetric soil moisture for three days ahead. A Long Short-Term Memory (LSTM) network was designed and trained at a regional scale using the data from the 2011–2016 period, at 28 locations that cover four major soil types. Validation was done on 2017–2018 data and LSTM was compared with a statistical forecasting technique and a classical machine learning approach. Evaluation was done with error measures commonly used in literature. The resulting network yielded the lowest errors and proved to have good generalisation properties. The system was tested from September 2019 to April 2020 using short-range weather forecasts of Yr service. It will present the cornerstone of the irrigation scheduling service in AgroSense.rs, the Serbian national platform for digital agriculture.

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ∼ 82%) and physiological information (i.e. physiological SIF yield, ΦF, 17% ∼ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether ΦF indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that ΦF responded to the proxy for physiological stress (partial correlation coefficient, r p= 0.40, p< 0.001) while non-physiological signals of SIF did not respond (p> 0.1). The field-scale ΦF data showed water deficit stress from the comparison between irrigated and rainfed fields, and ΦF was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r= 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed ΦF was more strongly correlated spatially with air temperature and VPD (r= 0.23 and 0.39) than SIF (r= 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that ΦF reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of ΦF is spatially scalable. Utilizing ΦF for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

Establishing a Reference Baseline for Midday Stem Water Potential in Olive and Its Use for Plant-Based Irrigation Management.

Midday stem water potential (SWP) is rapidly becoming adopted as a standard tool for plant-based irrigation management in many woody perennial crops. A reference or “baseline” SWP has been used in some crops (almond, prune, grape, and walnut) to account for the climatic influence of air vapor pressure deficit (VPD) on SWP under non-limiting soil moisture conditions. The baseline can be determined empirically for field trees maintained under such non-limiting conditions, but such conditions are difficult to achieve for an entire season. We present the results of an alternative survey-based approach, using a large set of SWP and VPD data collected over multiple years, from irrigation experiments in olive orchards located in multiple countries [Spain, United States (California), Italy, and Argentina]. The relation of SWP to midday VPD across the entire data set was consistent with an upper limit SWP which declined with VPD, with the upper limit being similar to that found in Prunus. A best fit linear regression estimate for this upper limit (baseline) was found by selecting the maximum R2 and minimum probability for various upper fractions of the SWP/VPD relation. In addition to being surprisingly similar to the Prunus baseline, the olive baseline was also similar (within 0.1 MPa) to a recently published mechanistic olive soil-plant-atmosphere-continuum (SPAC) model for “super high density” orchard systems. Despite similarities in the baseline, the overall physiological range of SWP exhibited by olive extends to about −8 MPa, compared to about −4 MPa for economically producing almond. This may indicate that, despite species differences in physiological responses to low water availability (drought), there may be convergent adaptations/acclimations across species to high levels of water availability. Similar to its use in other crops, the olive baseline will enable more accurate and reproducible plant-based irrigation management for both full and deficit irrigation practices, and we present tentative SWP guidelines for this purpose.

Modifying root-to-shoot ratio improves root water influxes in wheat under drought stress.

Drought intensity as experienced by plants depends upon soil moisture status and atmospheric variables such as temperature, radiation, and air vapour pressure deficit. Although the role of shoot architecture with these edaphic and atmospheric factors is well characterized, the extent to which shoot and root dynamic interactions as a continuum are controlled by genotypic variation is less well known. Here, we targeted these interactions using a wild emmer wheat introgression line (IL20) with a distinct drought-induced shift in the shoot-to-root ratio and its drought-sensitive recurrent parent Svevo. Using a gravimetric platform, we show that IL20 maintained higher root water influx and gas exchange under drought stress, which supported a greater growth. Interestingly, the advantage of IL20 in root water influx and transpiration was expressed earlier during the daily diurnal cycle under lower vapour pressure deficit and therefore supported higher transpiration efficiency. Application of a structural equation model indicates that under drought, vapour pressure deficit and radiation are antagonistic to transpiration rate, whereas the root water influx operates as a feedback for the higher atmospheric responsiveness of leaves. Collectively, our results suggest that a drought-induced shift in root-to-shoot ratio can improve plant water uptake potential in a short preferable time window during early morning when vapour pressure deficit is low and the light intensity is not a limiting factor for assimilation.

Changes in Dry-Season Water Availability and Attributions in the Yellow River Basin, China

Global warming will significantly change patterns of precipitation (P) and evapotranspiration (E) and thus the surface water availability (P minus E, P–E). Changes in P–E will challenge freshwater supply, food security, and sustainability of the ecosystems. Therefore, understanding the spatiotemporal change in P–E and its drivers is key for water resources management. Here, we quantified the changes in water availability during the driest month of the year and identified its drivers in the Yellow River Basin (YRB), China, during 1982–2016. Our results showed that 89.6% of the YRB showed declining dry-season water availability in 2000–2016 compared with 1982–1999, although the total dry-season water resources (defined as the proportion of the sum of monthly P–E to the P) remained nearly unchanged due to the increased P. Changes in seasonal P and E contributed to 87.0 and 99.0% declines in dry-season water availability, respectively, demonstrating the key role of E in net seasonal water fluxes. Increased air temperature (41.8%), vegetation greening (30.8%), and vapor pressure deficit (19.2%) were the main factors driving changes in E in the YRB during the study period. Our study highlighted a drier dry season in the YRB during 1982–2016 and illustrated that climate and vegetation changes played important roles in driving changes in dry-season water availability. Seasonal water fluxes must be considered in future water resources management in the YRB, especially in the context of climate warming and revegetation programs.

Mixed Temperature-Moisture Signal in δ18O Records of Boreal Conifers from the Permafrost Zone

Global climatic changes have been observed for all natural biomes, with the greatest impact in the permafrost zone. The short series of direct observations of air temperature and precipitation from meteorological stations for this territory make it difficult to use them in studies of the impact of climate change on forest and forest-tundra ecosystems, but only longer series of gridded data expand the temporal-spatial resolution of this analysis. We compared local and gridded air temperature, precipitation and vapor pressure deficit (VPD) data, analyzed the trends of their changes over the last century for three sites in the permafrost zone (YAK and TAY in Russia, and CAN in Canada), and estimated the effect of their variability on oxygen isotopes in the tree-ring cellulose (δ18Ocell) of three different species (Larix cajanderi Mayr, Larix gmelinii Rupr. Rupr and Piceaglauca (Moench) Voss). Climate trend analysis showed strong changes after the 1980s, and even more pronounced from 2000 to 2020. We revealed that δ18Ocell-YAK showed mixed signals of the July temperature (r = 0.49; p = 0.001), precipitation (r = −0.37; p = 0.02) and vapor pressure deficit (VPD) (r = 0.31; p = 0.02), while δ18Ocell-CAN captured longer March–May (r = 0.37, p = 0.001) and July (r = 0.32, p &lt; 0.05) temperature signals as well as spring VPD (r = 0.54, p = 0.001). The δ18Ocell-TAY showed a significant correlation with air temperature in July (r = 0.23, p = 0.04) and VPD in March (r = −0.26, p = 0.03). The obtained eco-hydrological relationships indicate the importance of temperature and moisture to varying degrees, which can be explained by site- and species-specific differences.

Drivers and Environmental Impacts of Vegetation Greening in a Semi-Arid Region of Northwest China since 2000

The dynamics of terrestrial vegetation have changed a lot due to climate change and direct human interference. Monitoring these changes and understanding the mechanisms driving them are important for better understanding and projecting the Earth system. Here, we assessed the dynamics of vegetation in a semi-arid region of Northwest China for the years from 2000 to 2019 through satellite remote sensing using Vegetation Index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and analyzed the interannual covariation between vegetation and three climatic factors—air temperature, precipitation, and vapor pressure deficit (VPD)—at nine meteorological stations. The main findings of this research are: (1) herbaceous land greened up much more than forests (2.85%/year vs. 1.26%/year) in this semi-arid region; (2) the magnitudes of green-up for croplands and grasslands were very similar, suggesting that agricultural practices, such as fertilization and irrigation, might have contributed little to vegetation green-up in this semi-arid region; and (3) the interannual dynamics of vegetation at high altitudes in this region correlate little with temperature, precipitation, or VPD, suggesting that factors other than temperature and moisture control the interannual vegetation dynamics there.

Water and carbon dioxide fluxes over a “floating blanket” wetland in southwest of China with eddy covariance method

Large uncertainties exist in carbon sequestration and water exchange process in wetland ecosystems under climate change. Beihai wetland is a very rare special type of alpine marsh with plants floating on the water surface located in the southeast margin area of the Tibetan Plateau. Based on the eddy covariance measurements from July 2015 to December 2016 over Baihai wetland, we have investigated the patterns of energy and carbon dioxide fluxes between the air and the alpine marsh and their main drivers. The latent heat flux (LE) was the main consumer of available radiation which accounted for 63% of net radiation (Rn) in 2016. Rn was the main factor determining H at both wet and dry season. Air temperature (Ta) and vapor pressure deficit (VPD)were most influenced with half-hourly LE during both wet and dry season, and VPD showed a larger influence on NEE in dry season than that in wet season. The total evapotranspiration (ET) in wet season occupied 60% of annual ET with an amount of 762.3 mm yr−1 in 2016, which was much lower than the annual total precipitation (1780.2 mm yr−1). Photosynthetic active radiation (PAR) was the main controller in the half-hourly net ecosystem exchange (NEE), while Ta mainly controlled the seasonal variations in NEE. The annual total NEE, gross primary production (GPP) and ecosystem respiration (RE) were -233.8, 796.6 and 562.8 g C m−2 yr−1 in 2016. The fraction of vegetation to water surface changed from 66% to 74% in the study period. A positive linearly relationship was both found between the fraction of vegetation to water surface and CO2 uptake and evapotranspiration. The fraction of vegetation to water surface could explain 40% variation of ET and 62% variation of NEE, respectively.

Contrasting heat tolerance of urban trees to extreme temperatures during heatwaves

Extreme climate conditions, including more frequent and prolonged heatwaves, are increasing in many regions throughout the world. Urban trees can aid in mitigating the adverse impacts of climate extremes; however, their capacity to do so is limited by species differences in ability to maintain function and retain leaves to provide shade under extreme temperatures. To assess tree vulnerability to heatwaves, we used a common garden experiment in Western Sydney, Australia, which included four widely-planted tree species; two native evergreen and two exotic deciduous species. Data were collected during 2019 and 2020, the two hottest summers on local record with maximum air temperatures reaching 45 °C. We monitored plant physiological status as stomatal conductance (gS) and midday leaf water potential (Ψmid). We determined heat tolerance by measuring the leaf critical temperature (Tcrit) for photosynthesis and leaf turgor loss point (πtlp) as thresholds for loss of function and calculated the thermal safety margin. Plant performance was assessed by measuring tree growth and leaf damage after heatwaves. Species responded dynamically with gS decreasing as air temperature and vapor pressure deficit increased during heatwaves. Exotic species had higher gS, Tcrit and πtlp than native species. Leaf damage under heatwave conditions was overall lower in native species. Our results highlight the impact of heatwaves on urban trees and the value of physiological metrics to inform tree species selection to create more resilient urban environments.

Hybrid Bermudagrass and Tall Fescue Turfgrass Irrigation in Central California: II. Assessment of NDVI, CWSI, and Canopy Temperature Dynamics

As the drought conditions persist in California and water continues to become less available, the development of methods to reduce water inputs is extremely important. Therefore, improving irrigation water use efficiency and developing water conservation strategies is crucial for maintaining urban green infrastructure. This two-year field irrigation project (2018–2019) focused on the application of optical and thermal remote sensing for turfgrass irrigation management in central California. We monitored the response of hybrid bermudagrass and tall fescue to varying irrigation treatments, including irrigation levels (percentages of reference evapotranspiration, ETo) and irrigation frequency. The ground-based remote sensing data included NDVI and canopy temperature, which was subsequently used to calculate the crop water stress index (CWSI). The measurements were done within two hours of solar noon under cloud-free conditions. The NDVI and canopy temperature data were collected 21 times in 2018 and 10 times in 2019. For the tall fescue, a strong relationship was observed between NDVI and visual rating (VR) values in both 2018 (r = 0.92) and 2019 (r = 0.83). For the hybrid bermudagrass, there was no correlation in 2018 and a moderate correlation (r = 0.72) in 2019. There was a moderate correlation of 0.64 and 0.88 in 2018 and 2019 between tall fescue canopy minus air temperature difference (dt) and vapor pressure deficit (VPD) for the lower CWSI baseline. The correlation between hybrid bermudagrass dt and VPD for the lower baseline was 0.69 in 2018 and 0.64 in 2019. Irrigation levels significantly impacted tall fescue canopy temperature but showed no significant effect on hybrid bermudagrass canopy temperature. For the same irrigation levels, increasing irrigation frequency slightly but consistently decreased canopy temperature without compromising the turfgrass quality. The empirical CWSI values violated the minimum expected value (of 0) 38% of the time. Our results suggest NDVI thresholds of 0.6–0.65 for tall fescue and 0.5 for hybrid bermudagrass to maintain acceptable quality in the central California region. Further investigation is needed to verify the thresholds obtained in this study, particularly for hybrid bermudagrass, as the recommendation is only based on 2019 data. No CWSI threshold was determined to maintain turf quality in the acceptable range because of the high variability of CWSI values over time and their low correlation with VR values.

Carbon flux around leaf-cytosolic glyceraldehyde-3-phosphate dehydrogenase introduces a 13C signal in plant glucose.

Within the plant and Earth sciences, stable isotope analysis is a versatile tool conveying information (inter alia) about plant physiological and paleoclimate variability across scales. Here, we identify a 13C signal (i.e. systematic 13C/12C variation) at tree-ring glucose C-4 and report an experimentally testable theory on its origin. We propose the signal is introduced by glyceraldehyde-3-phosphate dehydrogenases in the cytosol of leaves. It conveys two kinds of (potentially convoluted) information: (i) commitment of glyceraldehyde 3-phosphate to 3-phosphoglycerate versus fructose 1,6-bisphosphate metabolism; and (ii) the contribution of non-phosphorylating versus phosphorylating glyceraldehyde-3-phosphate dehydrogenase to catalysing the glyceraldehyde 3-phosphate to 3-phosphoglycerate forward reaction of glycolysis. The theory is supported by 13C fractionation modelling. Modelling results provide the first evidence in support of the cytosolic oxidation-reduction (COR) cycle, a carbon-neutral mechanism supplying NADPH at the expense of ATP and NADH, which may help to maintain leaf-cytosolic redox balances. In line with expectations related to COR cycling, we found a positive correlation between air vapour pressure deficit and 13C discrimination at glucose C-4. Overall, 13C-4 signal analysis may enable an improved understanding of leaf carbon and energy metabolism.

Intra-annual tree growth responds to micrometeorological variability in the central Amazon

Intra-annual distribution of precipitation in central Amazonia leads to a short mild dry season, which is associated with an increase in irradiance and temperature and a decline in relative humidity; however, the independent effect of each individual climatic variable on tree growth is still under investigation. The objective of this study was to determine how tree growth (inferred from radial stem increment) responds to monthly variations of micrometeorological variables in the central Amazon. During five years (2013-2017) we measured tree growth in 51 trees from nine species and, above the forest canopy, collected environmental data, such as photosynthetically active radiation (PAR), air temperature (T), precipitation, air relative humidity (RH), air vapor pressure deficit (VPD), reference evapotranspiration (ETo), and soil water content (SWC). We used principal component regression to evaluate the effect of micrometeorological variability on tree growth. Mean tree growth across species was responsive to variations in almost all the micrometeorological variables examined, with the exception of mean and minimum temperature, maximum RH, and minimum VPD. Mean tree growth across species increased with increasing precipitation, RHmean, RHmin and SWC, while it decreased with increasing PAR, Tmax, and ETo. It was also shown that an increase in VPDmean and VPDmax has a negative effect on tree growth. These results contribute to improve our understanding of effect of climate variability on tree growth, and shed light on the potential effect of severe droughts in the central Amazon.