Atmospheric Water Deficit Research Articles

Increasing drought sensitivity of plant photosynthetic phenology and physiology

Understanding the impacts of drought on plant photosynthetic phenology and physiology is essential for accurately predicting annual gross primary productivity (GPP) and global carbon cycles. While droughts in different seasons can have different effects on plant growth and photosynthesis, a comprehensive understanding of how plant photosynthetic phenology and physiology respond to different seasons’ droughts and their temporal changes is lacking. Here, we comprehensively evaluated the drought sensitivities of plant photosynthetic phenology and physiology and their temporal trends in the past two decades, using the start/end of the photosynthetic seasons (SOS/EOS) and peak GPP (GPPmax) derived from FLUXNET ground observations since the 1990s and remote-sensing data (2001–2020) over the globe. Our results show that spring droughts leads to delayed SOS in arid ecosystems and advanced SOS in humid ecosystems. In contrast, droughts in summer and autumn generally advance EOS. In addition, spring droughts decrease GPPmax in arid regions but increase it in humid regions, whereas summer droughts lead to significant GPPmax reductions. More importantly, we observed significant increases in the drought sensitivity of SOS, EOS, and GPPmax over the last two decades, which is driven by long-term decreases in background soil moisture and increases in atmospheric water deficit under climate change. Furthermore, these increasing trends were projected to persist in the 21st century under Shared Socioeconomic Pathways 8.5 and 4.0. Overall, our findings underscore the critical role of drought timing in shaping ecosystem responses and highlight the growing vulnerability of ecosystem phenology and physiology to drought, which may restrict the increases in terrestrial carbon uptake under warming.

Alleviation of Drought Stress in Soybean [Glycine max (L.) Merril] by Foliar Application of Thiourea on Productivity and Profitability under Rainfed Condition

Background: In changing climatic scenario, plants often face periods of soil and atmospheric water deficits because of scarcity of water availability and deteriorating quality across the globe. Drought stress is the one of the major abiotic factors that reduce plant water status, obstructs photosynthesis, brings oxidative stress hindering soybean productivity. In view of this, bioregulators (thiourea) are innovative agricultural technique used to protect plants, minimizing the adverse effects caused by environmental stress. Therefore, an alternative to improve crop yield under rainfed condition by application of bioregulators like thiourea and suitable varieties are important in order to mitigate stress in soybean production. Methods: The field experiments were conducted in Factorial RBD with three replications. To know the impact of foliar spray of thiourea on growth, physiological parameters, yield parameters, yield and economics of two soybean varieties were carried out during kharif 2020, 2021 and 2022. Result: Long term results showed that, by using MACS 1188 variety of soybean and foliar spray of thiourea at 500 ppm and 750 ppm during the 25 and 55 DAS is a commendatory option and most remunerative for farmers to improve the productivity and profitability of soybean in Northern Transition Zone of Karnataka.

Atmospheric drought dominates changes in global water use efficiency

Water use efficiency (defined as the ratio of gross primary productivity to plant transpiration, WUET) describes the tradeoff between ecosystem carbon uptake and water loss. However, a comprehensive understanding of the impact of soil and atmospheric moisture deficits on WUET across large regions remains incomplete. Solar-induced chlorophyll fluorescence (SIF) serves as an effective signal for measuring both terrestrial vegetation photosynthesis and transpiration, thereby enabling a rapid response to changes in the physiological status of plants under water stress. The objectives of this study were to: 1) mechanistically calculate WUET using top-of-canopy SIF data and meteorological information by using the revised mechanistic light response model and the Penman-Monteith equation; 2) analyze the effects of atmospheric and soil water deficits on SIF-based WUET by using decoupled soil water content (SWC) and vapor pressure deficit (VPD); 3) evaluate estimated SIF-based WUET against data from 28 eddy covariance (EC) flux sites representing eight different vegetation types. Results indicated that the model performed well in ecosystems with dense canopies, explaining 56 % of the daily variability in EC tower-based WUET. For the years 2019–2020, the global average WUET derived from SIF was 3.49 g C/kg H2O. Notably, this value exceeded 4 g C/kg H2O in tropical rainforest regions near the equator and went beyond 5 g C/kg H2O in the high-latitude regions of the Northern Hemisphere. We found that SIF-based WUET was primarily influenced by VPD rather than SWC in over 90 % of the global vegetated area. The model used in this study increased our ability to mechanistically estimate WUET with SIF at the global scale, thereby highlighting the significance of the global response of SIF-based WUET to water stress, and also enhancing our understanding of the water‑carbon cycle in terrestrial ecosystems.

Testing effects of vapor pressure deficit on fruit growth: a comparative approach using peach, mango, olive, orange, and loquat.

Determining the influence of vapor pressure deficit (VPD) on fruit growth is a key issue under a changing climate scenario. Using a comparative approach across different fruit tree species may provide solid indications of common or contrasting plant responses to environmental factors. Knowing fruit growth responses to VPD may also be useful to optimize horticultural management practices under specific atmospheric conditions. Climate data to calculate VPD and fruit relative growth rates (RGR) by fruit gauges were monitored in peach at cell division, pit hardening and cell expansion stages; in two mango cultivars at cell division, cell expansion and maturation stages; in two olive cultivars, either full irrigated or rainfed, at early and late cell expansion stages; in 'Valencia' orange at early and late cell division stage, before and after mature fruit harvest; in loquat at cell expansion and maturation stages. At the fruit cell division stage, sensitivity of fruit growth to VPD seems to vary with species, time, and probably soil and atmospheric water deficit. 'Keitt' mango and 'Valencia' orange fruit growth responded to VPD in opposite ways, and this could be due to very different time of the year and VPD levels in the monitoring periods of the two species. At pit hardening stage of peach fruit growth, a relatively weak relationship was observed between VPD and RGR, and this is not surprising as fruit growth in size at this stage slows down significantly. A consistent and marked negative relationship between VPD and RGR was observed at cell expansion stage, when fruit growth is directly depending on water intake driving cell turgor. Another behavior common to all observed species was the gradual loss of relationship between VPD and RGR at the onset of fruit maturation, when fruit growth in size is generally programmed to stop. Finally, regardless of fruit type, VPD may have a significant effect on fruit growth and could be a useful parameter to be monitored for tree water management mainly when the cell expansion process prevails during fruit growth.

Evaluation of satellite-based soil moisture for agricultural drought monitoring in the Brazilian semiarid region

The Northeast region of Brazil, particularly the Brazilian semiarid region (BSR), is frequently affected by drought events, such as the great drought that started in 2012 and is considered one of the most severe droughts in recent decades. Monitoring and quantifying this type of event is essential for decision-making and the adoption of impact mitigation strategies. In this study, remotely sensed soil moisture (SM) data from three products derived from Soil Moisture and Ocean Salinity (SMOS-CATDS and SMOS-IC) and Soil Moisture Active Passive (SMAP) were validated in the BSR using a dense network of in situ stations (N = 120) from 2015 to 2020. Subsequently, the best product was selected for the evaluation of agricultural drought, based on the Soil Water Deficit Index (SWDI), which was compared with the Atmospheric Water Deficit (AWD) obtained from in situ data (N = 50). After validation, SMAP was selected as the best product for estimating SM in the BSR, and SWDI-SMAP showed a strong temporal correlation with AWD. Based on these two indices, the results indicate the severity of drought in the BSR during the evaluated period, with significant social and economic impacts, highlighting the need for continuous monitoring, especially to support family farming, which is predominant in the region.

Atmospheric evaporative demand and water deficit on the ecophysiology of Rubber seedlings

The search for genetic materials resistant to adverse weather conditions has been a major focus in studies on species of economic interest. The objective of the present study was to assess the growth and photosynthesis of rubber seedlings clones under two conditions of atmospheric evaporative demand, characterized by fluctuations in temperature (TEMP) and vapor pressure deficit (VPD), associated to two water regimens. Hevea brasiliensis Muell. Arg (RRIM 600 and FX 3864) clones were assessed in two microclimates, at low (TEMP 21.2 ºC and VPD 0.29 Kpa) and high (TEMP 26.9 ºC and VPD 1.49 Kpa) atmospheric evaporative demand, under two water regimens: water deficit and well-watered. Water deficit 50% water availability was sufficient to reduce the net CO2 assimilation rate, leaf area and total chlorophyll of the clones studied that impacted growth in both microclimates. The effects of water deficit on growth and net carbon assimilation rate were intensified under high atmospheric evaporative demand. However, when comparing the two clones studied, RRIM 600 showed greater growth and photosynthesis without water restriction. The FX 3864 clone, despite the high CO2 assimilation values under high atmospheric demand and without water restriction, showed a reduced growth. The results of this study form an important basis for the selection of genotypes with the potential to develop in adverse climatic conditions. In this sense, the RRIM 600 genotype is recommended as a promising material that would best adapt under adverse climatic conditions.

Atmospheric and soil water deficit induced changes in chemical and hydraulic signals in wheat (Triticum aestivum L.)

AbstractPlant responses to soil drying and the metabolic basis of drought‐induced limitations in stomatal opening are still being discussed. In this study, we investigate the roles of root‐born chemical and hydraulic signals on stomatal regulation in wheat genotypes as affected by soil drought and vapour pressure deficit. Twelve consecutive pot experiments were carried out in a glasshouse. Two bread wheat cultivars (Gönen and Basribey) were subjected to drought under high and low vapour pressure deficit (VPD) in a growth chamber. Total dry matter, specific leaf area, xylem ABA content, xylem osmotic potential, xylem pH, root water potential (RWP), stomatal conductance, leaf ABA content and photosynthetic activity were determined daily during 6 days after the onset of treatments (DAT). In the first phase of drought stress, soil drying induced an increase in the xylem ABA with a peak 3 DAT while RWP drastically decreased during the same period. Then the osmotic potential of leaves decreased and leaf ABA content increased 4 DAT. A similar peak was observed for stomatal conductance during the early stress phase, and it became stable and significantly higher than in well‐watered conditions especially in high vapour deficit conditions (H‐VPD). Furthermore, xylem pH and xylem osmotic potential appeared to be mostly associated with atmospheric moisture content than soil water availability. The results are discussed regarding possible drought adaptation of wheat under different atmospheric humidity.

Variety-specific response of bulk stomatal conductance of grapevine canopies to changes in net radiation, atmospheric demand, and drought stress.

In wine growing regions around the world, climate change has the potential to affect vine transpiration and overall vineyard water use due to related changes in daily atmospheric conditions and soil water deficits. Grapevines control their transpiration in response to such changes by regulating conductance of water through the soil-plant-atmosphere continuum. The response of bulk stomatal conductance, the vine canopy equivalent of stomatal conductance, to such changes were studied on Cabernet-Sauvignon, Merlot, Tempranillo, Ugni blanc, and Semillon vines in a non-irrigated vineyard in Bordeaux France. Whole-vine sap flow, temperature and humidity in the vine canopy, and net radiation absorbed by the vine canopy were measured on 15-minute intervals from early July through mid-September 2020, together with periodic measurements of leaf area, canopy porosity, and predawn leaf water potential. From these data, bulk stomatal conductance was calculated on 15-minute intervals, and multiple linear regression analysis was performed to identify key variables and their relative effect on conductance. For the regression analysis, attention was focused on addressing non-linearity and collinearity in the explanatory variables and developing a model that was readily interpretable.Variability of vapour pressure deficit in the vine canopy over the day and predawn water potential over the season explained much of the variability in bulk stomatal conductance overall, with relative differences between varieties appearing to be driven in large part by differences in conductance response to predawn water potential between the varieties. Transpiration simulations based on the regression equations found similar differences between varieties in terms of daily and seasonal transpiration. These simulations also compared well with those from an accepted vineyard water balance model, although there appeared to be differences between the two approaches in the rate at which conductance, and hence transpiration is reduced as a function of decreasing soil water content (i.e., increasing water deficit stress). By better characterizing the response of bulk stomatal conductance, the dynamics of vine transpiration can be better parameterized in vineyard water use modeling of current and future climate scenarios.

Minimum Rainfall Inter-Event Time to Separate Rainfall Events in a Low Latitude Semi-Arid Environment

Water scarcity in dry tropical regions is expected to intensify due to climate change. Characterization of rainfall events is needed for a better assessment of the associated hydrological processes, and the proposition of adaptation strategies. There is still no consensus on the most appropriate method to separate rainfall events from a continuous database, although the minimum inter-event time (MIET) is a commonly used criterion. Semi-arid regions of low latitudes hold a distinct rainfall pattern compared to their equivalent at higher latitudes; these seasonally dry tropical forests experience strong spatial–temporal variability with intense short-duration rainfall events, which, in association with high energy surplus and potential evaporation, leads to an atmospheric water deficit. In this study, we identified the most adequate MIET based on rainfall data continuously measured at 5-min intervals over the last decade (2009–2020) in the semi-arid northeast of Brazil. The rainfall events were grouped according to different MIETs: 15 min, 1 h, 2 h, 3 h, 6 h, 12 h, and 24 h to determine rainfall depth, duration and intensity at intervals of 5, 30, and 60 min, time between events, and respective temporal distribution, with and without single tip events. Including single tip events in the dataset affected the number of rainfall events and respective characteristics up to a MIET of 3 h. A MIET of 6 h is the most appropriate to characterize the rainfall distribution in this tropical semi-arid region. Three classes were defined based on rainfall depth, duration, and intensity: I-small events (77% below 40 mm and 32 mm/h), II-high intensity events (3% between 36 and 76 mm/h), III-longer events of higher depth (20%). This study is useful for understanding how the MIET relates to other ecohydrological processes and provides more precise information on the rainfall characteristics at the event scale.

Fisher discriminant analysis method applied in drought detection: an instance in an alpine meadow ecosystem

Abstract Fisher discriminant analysis can comprehensively take multiple factors into consideration and effectively conduct separations between two classes. If it can be used to detect the occurrences of drought, drought can be detected more effectively and accurately. Based on 9-year carbon flux and corresponding meteorological data, soil water content (SWC) and vapor pressure deficit (VPD) were selected as the discriminant factors. Drought occurrences were detected by applying the Fisher discriminant analysis method in an alpine ecosystem in Tibet. Fisher discriminant analysis was successfully applied to detect drought occurrence in an alpine meadow ecosystem. The soil water deficit and atmospheric water deficit were comprehensively taken into consideration. Consequently, this method could detect the onset and end date of droughts more accurately and reasonably. Based on the characteristics of drought and non-drought samples, the discriminant equation was constructed as y = 24.46SWC − 4.60VPD. When y > 1, the days were distributed above the critical line. In addition, when y was greater than one for more than 10 days, it was labeled as one drought event. If the interval between two drought processes was less than 2 days, it was considered one drought event. With increasing the study period and continued accumulation of observation data, the discriminant equation could be further optimized in the future, resulting in more accurate drought detection.

Remote Sensing of Seasonal Climatic Constraints on Leaf Phenology Across Pantropical Evergreen Forest Biome

AbstractClimatic drivers for canopy leaf shedding and flush of evergreen broadleaved forest biome are still unclear at the continental scale across tropical and subtropical region. This imposes a challenge for modeling pantropical photosynthesis seasonality in Earth system models. Here, we examined three potential climatic triggers, vapor pressure deficit–a proxy of atmospheric water deficit, downward shortwave incoming solar radiation–a proxy of sunlight availability, and terrestrial water storage–a proxy of soil water availability observed by the Gravity Recovery and Climate Experiment, by comparing with two satellite phenological proxies–the Enhanced Vegetation Index and Continuous Solar‐induced chlorophyll fluorescence. Results show that tropical leaf phenology varies greatly from equatorial bimodal seasonality to higher‐latitude unimodal seasonality. Sunlight availability dominantly controls the whole seasonal leaf phenology across the pantropical region. Atmospheric dryness is one main type of water stress for leaf phenology during the first half year. However, soil water stress strongly inhibits the first‐half of leaf phenology in tropical Asia and the second‐half of leaf phenology in Congo, but shows rare constraint on the leaf phenology in Amazon. Ignoring these various roles of soil moisture availability and atmospheric dryness in influencing tropical leaf phenology might lead to unexpected uncertainty for predicting the water and carbon cycles of tropical forest ecosystem in Earth system models.

Assessment of Agricultural Drought Using Soil Water Deficit Index Based on ERA5-Land Soil Moisture Data in Four Southern Provinces of China

It is important to accurately assess agricultural drought because of its harmful impacts on the ecosystem and economy. Soil moisture reanalysis datasets provide an important way to assess agricultural drought. In this study, the ERA5-Land surface and subsurface soil moisture was used to estimate the soil water deficit index (SWDI) in four southern provinces of China. The ERA5-Land dataset was evaluated with in situ soil moisture observations from agrometeorological stations. Agricultural drought was assessed for three climate zones at a weekly scale from 2017 to 2019 and was compared with the atmospheric water deficit (AWD). It was found that both ERA5-Land soil moisture and the derived SWDI have relatively high accuracy, and the wet bias in the ERA5-Land dataset can be reduced by the calculation of the SWDI. The subsurface layer has better performance than the surface layer in drought monitoring, though they are highly correlated. Different climate zones demonstrate different drought periods and drought severity, and the temperate climate zone with no dry season has less droughts. The most severe droughts with the largest spatial extent occurred in the early winter, especially in 2019. Differences in the SWDI and AWD are mainly shown in southwestern Yunnan. The results of this study have important reference values for drought risk management.

Climatic Influences on Agricultural Drought Risks Using Semiparametric Kernel Density Estimation

A bivariate kernel density estimation (KDE) method was utilized to develop a stochastic framework to assess how agricultural droughts are related to unfavorable meteorological conditions. KDE allows direct estimation of the bivariate cumulative density function which can be used to extract the marginal distributions with minimal subjectivity. The approach provided excellent fits to bivariate relationships between the standardized soil moisture index (SSMI) computed at three- and six-month accumulations and standardized measures of precipitation (P), potential evapotranspiration (PET), and atmospheric water deficit (AWD = P − PET) at 187 stations in the High Plains region of the US overlying the Ogallala Aquifer. The likelihood of an agricultural drought given a precipitation deficit could be as high as 40–65% within the study area during summer months and between 20–55% during winter months. The relationship between agricultural drought risks and precipitation deficits is strongest in the agriculturally intensive central portions of the study area. The conditional risks of agricultural droughts given unfavorable PET conditions are higher in the eastern humid portions than the western arid portions. Unfavorable PET had a higher impact on the six-month standardized soil moisture index (SSMI6) but was also seen to influence three-month SSMI (SSMI3). Dry states as defined by AWD produced higher risks than either P or PET, suggesting that both of these variables influence agricultural droughts. Agricultural drought risks under favorable conditions of AWD were much lower than when AWD was unfavorable. The agricultural drought risks were higher during the winter when AWD was favorable and point to the role of soil characteristics on agricultural droughts. The information provides a drought atlas for an agriculturally important region in the US and, as such, is of practical use to decision makers. The methodology developed here is also generic and can be extended to other regions with considerable ease as the global datasets required are readily available.

Statistical techniques approach: two sugarcane genotypes growth under elevated [CO2] atmospheric and drought

This article aims was to compare two sugarcane genotypes under elevated atmospheric carbon dioxide (CO2) concentration and soil water deficit, through an approach based on statistical analysis of plant growth multiple characteristics. For that, Pearson's correlation, dissimilarity and principal components (PC) analysis were performed, of some parameters such as stem length (culm) and roots length, number of leaves, dry mass of plant tissues, among other characteristics. Biometric attributes have a positive and significant correlation with each other. However, the dry mass values ​​have a negative correlation with the other parameters, meaning, therefore, there is a growth reduction as there is also a decrease in plants water conditions subjected to stress. Based on the dissimilarity and PC analysis, observed that genotypes genetically diverge and the imposed environmental condition influences growth responses. This preliminary study is an indication that this approach is essential for understanding the variations between the sugarcane genotypes responses. In addition, is evident (due to divergence) that analyses about the physiological and molecular responses of these genotypes in this environmental condition will contribute to the identification of regulated biological processes and possible tolerance mechanisms.

Connections between the hydrological cycle and crop yield in the rainfed U.S. Corn Belt

Water stress is one of the major abiotic stresses and directly affects crop growth and influences crop yields. To better quantify the responses of crop yield to hydrological variability in the rainfed Corn Belt of the United States (U.S.), we analyzed the relationships between corn/soybean yield and hydrological cycle metrics, as well as their spatio-temporal dynamic at the agricultural district and interannual scale between 2003 and 2014. We used Partial Least Square Regression (PLSR) to optimally integrate different hydrological metrics and drought indices to define a crop-specific new drought index that uses crop yield as the target, and investigated the contributions of those hydrological cycle components to the new drought index. We used both observed and modeled hydrological cycle metrics, as well as several drought indices in this study, including evapotranspiration (ET) and potential ET (PET), terrestrial water storage change (ΔS), surface soil moisture (SSM), river discharge (Q), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), fET (the ratio of ET to PET), and vapor pressure deficit (VPD). Our results revealed that: (1) VPD, SSM, and fET showed the strongest correlations with crop yield, among the observation-based hydrological cycle metrics and drought indices considered here. Most of the hydrological cycle metrics and drought indices showed similar seasonal correlation patterns with crop yield, and this pattern revealed that the sensitivity of crop growth to water stress peaked in July for corn and in August for soybean in the rainfed U.S. Corn Belt. (2) The drought in 2012 started with higher water demand (reflected in abnormally high ET, PET, and VPD) and lower water supply (reflected in abnormally low P), followed by soil water depletion (as revealed in SSM and ΔS), leading to massive crop yield losses due to increased constraints on both water supply and demand. (3) The R2 of the PLSR-based crop yield model reached 0.76 and 0.70 for corn and soybean, respectively. For both corn and soybean, the first PLSR component was mainly composed of information from VPD, fET, ΔS and SSM, indicating atmospheric water deficit and soil water storage both play critical roles in quantifying corn and soybean yield loss due to water stress.

Climate‐risk assessment for winter wheat using long‐term weather data

AbstractTemperature and water deficit stresses cause large year‐to‐year yield variability, and matching crop phenology with periods less prone to stresses can improve yield stability. We used 30 years of daily weather data from 69 stations in the U.S. Great Plains to quantify the risk of water deficit and temperature stresses for winter wheat (Triticum aestivum L.) cultivars differing in maturity, and to evaluate whether the selected variables explained variability in yield and area abandonment. Crop phenology was estimated using a simple temperature‐based model based on 282 field observations. A difference between the 15‐d running sums of reference evapotranspiration (ETo) and precipitation greater than 40% of the soil's available water holding capacity (AWHC) determined atmospheric water deficit (AWD). Heat and freeze stresses occurred when maximum temperatures >27 °C and minimum temperatures <0 °C occurred around heading. Probabilities of AWD in the spring was greater in the west and in the south; however, latitudinal AWD gradients dissipated when crop maturity was considered. The day of year (DOY) for last freeze increased from south to north and from east to west; and the DOY for onset of heat stress increased from south to north but did not follow a longitudinal gradient. Early maturing varieties avoided heat and AWD stresses during heading but were more likely to experience freezing conditions. Regional yield decreased and area abandonment increased with early onset of spring AWD and heat stresses. This conceptual framework for evaluating the risk of environmental stresses can be applied to other regions and cropping systems.

Soil water deficit promotes the effect of atmospheric water deficit on solar-induced chlorophyll fluorescence

Solar-induced chlorophyll fluorescence (SIF) is a novel optical signal that has been successfully used to track plant dynamics with the influence of soil water deficit. However, the effect of atmospheric water deficit on SIF under the impact of soil water deficit still remains unclear. Here, continuous measurements of SIF (at 760 nm, F760) of winter wheat under different soil water deficit were collected with a self-developed system. Additionally, soil moisture and atmosphere parameters [including air temperature (Ta), relative air humidity (Rh), and photosynthetically active radiation at 400–700 nm (PAR)] were also synchronously collected by common commercial devices. Vapor pressure deficit (VPD) was calculated based on the measurements of Ta and Rh. The results showed that the driving effect of PAR on F760 was obvious as we expected. Additionally, such effects of PAR on AF760 (F760/PAR) and Fy760 (F760/L685, L685 was canopy radiance at 685 nm) still existed when the PAR influences were partially removed by the calculation of F760/PAR and F760/L685. Furthermore, the relationship of PAR with AF760 or Fy760 was observed to be strengthened under the situation of water deficit through the analysis of Pearson correlations. With the influence of PAR, the accelerative effect of VPD on SIF under soil water deficit was not always observed in our study. Nevertheless, when the effect of PAR was removed by using partial correlation, VPD showed much stronger correlation with SIF in soil water stressed plot than that in unstressed one both at diurnal and seasonal scales. These results revealed that soil water deficit might promote the effect of atmospheric water deficit on SIF. This study has great significance for the application of SIF in drought monitoring and health assessments in terrestrial ecosystem.

Determinants of leaf area index and understorey light availability in New Zealand old‐growth forests

AbstractAimGlobal studies show strong climatic control of leaf area index (LAI) and related ecosystem properties. However, alternative states stabilized by positive feedbacks have the potential to produce appreciable differences in LAI in a given environment. On certain sites in New Zealand, ectomycorrhizal (EM) southern beech forest (Nothofagaceae) appear to form a stable alternative to more species‐rich conifer‐broadleaved forest dominated by arbuscular mycorrhizal (AM) trees. We asked which climate variables best predict LAI of New Zealand's remaining old‐growth forests, and if stands dominated by Nothofagaceae have lower LAI and better‐lit understories than conifer‐broadleaved forests, when climate and other site factors are held constant.LocationNew Zealand.TaxonSeventy‐two tree species belonging to 37 angiosperm, conifer and pteridophyte families, the most frequent occurrences being Cunoniaceae, Cyatheaceae, Dicksoniaceae, Lauraceae, Nothofagaceae, Podocarpaceae and Violaceae.MethodsWe quantified overstorey composition of 45 old‐growth stands, and used the LAI‐2200C Plant Canopy Analyzer to measure LAI and understorey light. We used generalized linear mixed models to determine how these variables were influenced by environment and by dominance of Nothofagaceae.ResultsLAI ranged from 3.5 to 6.9, and increased linearly with mean annual temperature (MAT); percentage light transmission to the understorey spanned an order of magnitude and decreased exponentially with increasing MAT. However, at a given MAT, LAI of stands dominated by Nothofagaceae averaged 0.8–0.9 units lower than conifer‐broadleaf stands, resulting in twofold higher understorey light levels in the former. Soil water deficits also significantly depressed LAI, and increased understorey light; atmospheric water deficits had the opposite effect.Main conclusionsTemperature is the best climatic predictor of LAI and understorey light in New Zealand's remaining old‐growth forests. However, the lower LAI and canopy light interception in southern beech stands presumably reflects the light‐demanding nature of Nothofagaceae, and their apparent ability to inhibit invasion by more shade‐tolerant AM trees with heavier crowns. This inhibitory effect may reflect reduced N supply to AM plants because of suppression of N mineralization by EM fungi, as observed in some EM systems elsewhere.

Quantification of leaf-scale light energy allocation and photoprotection processes in a Mediterranean pine forest under extensive seasonal drought.

Photoprotection strategies in a Pinus halepensis Mill. forest at the dry timberline that shows sustained photosynthetic activity during 6-7month summer drought were characterized and quantified under field conditions. Measurements of chlorophyll fluorescence, leaf-level gas exchange and pigment concentrations were made in both control and summer-irrigated plots, providing the opportunity to separate the effects of atmospheric from soil water stress on the photoprotection responses. The proportion of light energy incident on the leaf surface ultimately being used for carbon assimilation was 18% under stress-free conditions (irrigated, winter), declining to 4% under maximal stress (control, summer). Allocation of absorbed light energy to photochemistry decreased from 25 to 15% (control) and from 50% to 30% (irrigated) between winter and summer, highlighting the important role of pigment-mediated energy dissipation processes. Photorespiration or other non-assimilatory electron flow accounted for 15-20% and ~10% of incident light energy during periods of high and low carbon fixation, respectively, representing a proportional increase in photochemical energy going to photorespiration in summer but a decrease in the absolute amount of photorespiratory CO2 loss. Resilience of the leaf photochemical apparatus was expressed in the complete recovery of photosystem II (PSII) efficiency (ΦPSII) and relaxation of the xanthophyll de-epoxidation state on the diurnal cycle throughout the year, and no seasonal decrease in pre-dawn maximal PSII efficiency (Fv/Fm). The response of CO2 assimilation and photoprotection strategies to stomatal conductance and leaf water potential appeared independent of whether stress was due to atmospheric or soil water deficits across seasons and treatments. The range of protection characteristics identified provides insights into the relatively high carbon economy under these dry conditions, conditions that are predicted for extended areas in the Mediterranean and other regions due to global climate change.

Drought Monitoring Utility using Satellite-Based Precipitation Products over the Xiang River Basin in China

Drought is a natural hazard disaster that can deeply affect environments, economies, and societies around the world. Therefore, accurate monitoring of patterns in drought is important. Precipitation is the key variable to define the drought index. However, the spare and uneven distribution of rain gauges limit the access of long-term and reliable in situ observations. Remote sensing techniques enrich the precipitation data at different temporal–spatial resolutions. In this study, the climate prediction center morphing (CMORPH) technique (CMORPH-CRT), the tropical rainfall measuring mission (TRMM) multi-satellite precipitation analysis (TRMM 3B42V7), and the integrated multi-satellite retrievals for global precipitation measurement (IMERG V05) were evaluated and compared with in situ observations for the drought monitoring in the Xiang River Basin, a humid region in China. A widely-used drought index, the standardized precipitation index (SPI), was chosen to evaluate the drought monitoring utility. The atmospheric water deficit (AWD) was used for comparison of the drought estimation with SPI. The results were as follows: (1) IMERG V05 precipitation products showed the highest accuracy against grid-based precipitation, followed by CMORPH-CRT, which performed better than TRMM 3B42V7; (2) IMERG V05 showed the best performance in SPI-1 (one-month SPI) estimations compared with CMORPH-CRT and TRMM 3B42V7; (3) SPI-1 was more suitable for drought monitoring than AWD in the Xiang River Basin, because its high R-values and low root mean square error (RMSE) compared with the corresponding index based on in situ observations; (4) drought conditions in 2015 were apparently more severe than that in 2016 and 2017, with the driest area mainly distributed in the southwest part of the Xiang River Basin.