Mild Drought Research Articles

Response of Hydraulic and Photosynthetic Characteristics of Caroxylon passerinum (Bunge) Akhani and Roalson to Prolonged Drought and Short-Term Rehydration

Hydraulic traits are essential functional characteristics of plants related to water absorption, transport, and loss, serving as indicators of a plant’s adaptability to prevailing environmental water conditions. However, the hydraulic traits of shrub, particularly desert plants in arid and semi-arid regions, have been underexplored. In this study, we conducted a pot experiment using Caroxylon passerinum (Bunge) Akhani and Roalson as the subject. Three treatment groups were established: adequate water supply, mild drought, and severe drought. After subjecting the shrub to drought and subsequent rehydration, we measured hydraulic conductivity, net photosynthetic rate, and stomatal conductance. We found that leaf water potential decreased and stomatal conductance and net photosynthesis decreased with increasing drought intensity. We found that leaf water potential and stomatal conductance decreased with increasing drought intensity. Although there was no significant change in hydraulic conductivity in the two drought groups, the values were greater in the drought group than in the control, and greater in the mild drought group than in the severe drought group. Meanwhile, the embolism resistance decreased with increasing drought intensity. After rehydration, hydraulic conductivity did not return to control levels in the severe drought group, as did embolism resistance in the two drought groups, and leaf water potential did not recover significantly. The results showed that drought stress increased the hydraulic conductivity of C. passerinum, and this effect was more pronounced under mild drought stress. After the stress was lifted, C. passerinum continued to maintain a lower leaf water potential to promote water uptake. This result provides a reference for us to study water use of desert shrubs under different drought stresses.

Adaptation of rhizosphere bacterial communities of drought-resistant sugarcane varieties under different degrees of drought stress.

Sugarcane is highly sensitive to changes in moisture, and increased drought severely restricts its growth and productivity. Recent studies have shown that plant growth-promoting microorganisms are essential to reduce the adverse effects of environmental stresses, especially drought. However, our knowledge about the dynamics of rhizosphere microbial community structure in sugarcane under varying degrees of drought stress is limited. We analyzed the effects of different degrees of drought stress on the rhizosphere microbial communities of Zhongzhe 1(ZZ1) and Zhongzhe 6(ZZ6) with differences in drought resistance, by combining soil enzyme activity, nutrient content, and physiological and morphological characteristics of sugarcane roots. The results showed that rhizosphere bacterial community began to change at a field capacity of 50%, enriching the sugarcane rhizosphere with drought-resistant bacteria. The core strains of ZZ1 and ZZ6 rhizosphere enrichment were mainly Streptomycetales, Sphingomonadales, and Rhizobiales. However, compared to ZZ1, the changes in rhizosphere bacterial abundance in ZZ6 were primarily associated with the abundance of Streptomycetales as drought levels increased. Rhizobiales and Streptomycetales, enriched in the rhizosphere of ZZ6 under drought, were positively correlated with root tip number and total root length (TRL), increasing the distribution area of roots and, thus, improving water and nutrient uptake by the roots thereby enhancing the resistance of sugarcane to drought stress. This research enhances our understanding of the composition of the rhizosphere microbial community in sugarcane under different levels of drought stress and its interaction with the roots, thereby providing valuable insights for enhancing drought resistance in sugarcane. IMPORTANCE Drought stress is expected to further increase in intensity, frequency, and duration, causing substantial losses in sugarcane yields. Here, we exposed sugarcane to varying degrees of drought treatment during growth and quantified the eventual composition of the resulting sugarcane rhizosphere bacterial community groups. We found that sugarcane rhizosphere under mild drought began to recruit specific bacterial communities to resist drought stress and used the interactions of root tip number, total root length, and drought-resistant strains to improve sugarcane survival under drought. This research provides a theoretical basis for the rhizosphere microbiome to help sugarcane improve its resistance under different levels of drought stress.

Mild drought priming-induced salicylic acid involves in subsequent drought tolerance by modulating glutathione redox in antagonism with abscisic acid in Brassica napus

Mild drought priming-induced salicylic acid involves in subsequent drought tolerance by modulating glutathione redox in antagonism with abscisic acid in Brassica napus

Detection of paddy rice drought stress with sentinel image vegetation index and the relation with productivity in Allatengae Village, Bantimurung District, Maros Regency

Maros Regency is one of the rice storage areas in South Sulawesi. According to the Central Bureau of Statistics for Maros Regency in 2020, the harvested area of rice decreased by 10.11% or 4,849.55 Ha compared to 2018 and rice production decreased by 16.96% or 37,719.68 tons. This causes the productivity of rice also decreased. One of the factors causing the decline in rice production in Maros Regency is drought. Sentinel 2 imagery is one of the remote sensing data that can be used to detect rice drought using the drought index method. This study aims to detect dryness of paddy rice in Allatengae Village using Sentinel-2A satellite imagery based on NDDI index analysis and determine the relationship between drought index and rice productivity. The method used is the Normalized Difference Drought Index (NDDI) method to determine the dryness level of paddy fields based on NDVI and NDWI parameters and uses regression and correlation analysis methods. From the results of this study, dry rice in Allatengae Village was detected in September and October 2021. In September (42 HST), the average NDDI value was 0.0254 and was in a mild drought condition while in October (62 HST), the average NDDI value is 0.2425 and is in moderate class drought conditions. From the results of the analysis of the relationship between the drought index and rice productivity, there is a strong (negative) correlation, where the higher the NDDI index value, the lower the rice productivity value.

Assessment of drought conditions and prediction by machine learning algorithms using Standardized Precipitation Index and Standardized Water-Level Index (case study: Yazd province, Iran).

Drought as a natural phenomenon has always been a serious threat to regions with hot and dry climates. One of the major effects of drought is the drop in groundwater level. This paper focused on the SPI (Standardized Precipitation Index) and SWI (Standardized Water-Level Index) to assess meteorological and hydrological drought, respectively. In the first part, we used different time frames of SPI (3, 6, 12, and 24 months) to investigate drought in Yazd, a dry province in the center of Iran for 29 years (1990-2018). Then, in the second part, the relationship between SPI and SWI was investigated in the three aquifers of Yazd by some rain gauge stations and the closest observation wells to them. In addition to using SPI and SWI, we also used different machine learning (ML) algorithms to predict drought conditions including linear model and six non-linear models of K_Nearest_Neighbors, Gradient_Boosting, Decision_Tree, XGBoost, Random_Forest, and Neural_Net. To evaluate the accuracy of the mentioned models, three statistical indicators including Score, RMSE, and MAE were used. Based on the results of the first part, Yazd province has changed from mild wet to mild drought in terms of meteorological drought (the amount of rainfall according to SPI), and this condition can worsen due to climate change. The models used in ML showed that SPI-6 (score ave = 0.977), SPI-3 (score ave = 0.936), SPI-24 (score ave = 0.571), and SPI-12 (score ave = 0.413) indices had the highest accuracy, respectively. The models of Neural_Net (score ave = 0.964-RMSE ave = 0.020-MAE ave = 0.077) and Gradient_Boosting (score ave = 0.551-RMSE ave = 0.124-MAE ave = 0.248) had the highest and lowest accuracy in prediction of the SPI in all four-time scales. Based on the results of the second part, about the SWI, Random_Forest model (score = 0.929-RMSE = 0.052-MAE = 0.150) and model of Neural_Net (score = 0.755-RMSE = 0.235-MAE = 0.456) had the highest and lowest accuracy, respectively. Also, hydrological drought (reduction of the groundwater level) of the region has been much more severe, and according to the low correlation coefficient of average SPI and SWI (R2 = 0.14), we found that the uncontrolled pumping wells, as a main factor than a shortage of rainfall, have aggravated the hydrological drought, and this region is at risk of becoming a more arid region in the future.

Phosphate starvation response precedes abscisic acid response under progressive mild drought in plants

Drought severely damages crop production, even under conditions so mild that the leaves show no signs of wilting. However, it is unclear how field-grown plants respond to mild drought. Here, we show through six years of field trials that ridges are a useful experimental tool to mimic mild drought stress in the field. Mild drought reduces inorganic phosphate levels in the leaves to activate the phosphate starvation response (PSR) in soybean plants in the field. Using Arabidopsis thaliana and its mutant plants grown in pots under controlled environments, we demonstrate that PSR occurs before abscisic acid response under progressive mild drought and that PSR plays a crucial role in plant growth under mild drought. Our observations in the field and laboratory using model crop and experimental plants provide insight into the molecular response to mild drought in field-grown plants and the relationship between nutrition and drought stress response.

Drought prediction: Insights from the fusion of LSTM and multi-source factors

In the context of current global climate change, accurate drought prediction is crucial for water resources management and agricultural production. Although traditional drought forecasting methods largely rely on historical climatic data, these methods cannot fully consider the long-term effects of factors, such as climate change, and the evaluation of prediction results is limited. Therefore, this study proposed a drought prediction and evaluation framework based on Long Short-Term Memory (LSTM), integrating multi-source factors to significantly enhance the accuracy and reliability of drought prediction models. This framework applied two distinct forecasting schemes. The first scheme utilized ten diverse factors, including precipitation, evaporation, bare soil percentage area coverage, percentage crop cover, leaf area index, runoff, surface runoff, soil moisture, temperature, and total vegetated percentage cover, to predict future precipitation and evaporation, which was then used to calculate the Standardized Precipitation-Evaporation Index (SPEI) to evaluate drought characteristics. The second scheme directly used these ten factors and historical SPEI to predict future SPEI, further assessing future drought characteristics. By comparing the drought prediction results of the two schemes in terms of data statistics, drought characteristics, and spatial patterns, it was found that the LSTM model significantly improved accuracy when handling high-dimensional complex data and predicting key factors such as precipitation, evaporation, temperature, and soil moisture. The first scheme was more accurate when predicting severe and extreme droughts, whereas the second scheme was more sensitive to predicting moderate and mild droughts and exhibited higher stability and regularity in predicting the spatial variability of drought. In summary, LSTM has made significant improvements in the accuracy, stability, and reliability of drought prediction, providing stronger support for practical applications, such as agriculture and water resources management, and offering a new research tool for further climate change research.

Biochar with Organic and Inorganic Fertilizers Improves Defenses, Nitrogen Use Efficiency, and Yield of Maize Plants Subjected to Water Deficit in an Alkaline Soil

Nutrient management practices, such as optimum fertilizer addition rate and co-addition of inorganic fertilizers and organic amendments (compost and biochar), were investigated to enhance crop production and nitrogen (N) use efficiency. However, how these practices improve the defense system, N use efficiency, yield quantity and quality, and physio-biochemical constituents of maize (Zea mays L.) plants grown on an alkaline soil under different irrigation levels (well-watered conditions, mild drought, and severe drought) remains unclear. A two-year field trial was carried out in a split–split plot with a randomized complete block design with three irrigation levels (100% evapotranspiration (ET), 80% ET, and 60% ET) as the main plots, two amendments (5 Mg ha–1 biochar or compost) as subplots, and three regimes of inorganic fertilization (119-16-69, 179-24-99, and 238-31-138 kg N-phosphorus (P)-potassium (K) ha−1) as sub-subplots. We found that maize yield, oil, starch, protein, carbohydrates, and NPK uptake significantly decreased with increasing drought levels, but catalase, peroxidase, superoxide dismutase, and proline contents significantly increased. The addition of organic amendments (compost or biochar) with inorganic fertilizers was more effective in enhancing the above attributes than inorganic fertilizers alone, but these attributes were positively related to inorganic fertilizer rates. The treatment of compost or biochar plus 238-31-138 kg N-P-K ha−1 was the best treatment. The agronomic efficiency of applied fertilizer N (NAE) significantly decreased with increasing drought levels by 28.4–34.7%. The addition of biochar with inorganic fertilizers significantly enhanced NAE by 11.6% compared to inorganic fertilizers alone. Comparing the effect of inorganic fertilizer rates across all irrigation levels, the treatment of 119-16-69 kg N-P-K ha−1 gave the highest NAE. Thus, the addition of optimum NPK fertilizer rate with biochar or compost is suitable to enhance the yield quantity and quality of maize plants grown on alkaline soils by improving its defensive system and N use efficiency, especially under the expected increase in aridity response to climate change.

Daily dynamic thresholds of different agricultural drought grades for summer maize based on the Vegetation Water Index

Effective daily drought monitoring for summer maize (Zea mays L.) is critical to prevent crop yield reduction. Most of the vegetation indicators used for drought identification have been based on changes in canopy greenness that may not change immediately under drought stress, and have relatively long-time intervals (e.g., eight or 16 days) that are limited by available remote sensing products. Moreover, drought thresholds, may be potentially different during different crop growth stages, rather than constant during the entire growing season, as has been widely used in most existing drought indicators. We used the orthorectified reflectance in the short-wave infrared (SWIR) band, extracted from MODIS MCD43A4 because of its high sensitivity to variations in vegetation water content due to this waveband’s liquid water absorption characteristics. The Vegetation Water Index (VWI), calculated with the Normalized Difference Water Index (NDWI), was proposed for daily drought monitoring of summer maize in order to minimize the effects of geographical location, soil conditions, and ecological systems in different areas. Additionally, daily dynamic thresholds for drought-free, mild drought, moderate drought, and severe drought were determined with double logistic fitting functions having the highest R2 (0.79), based on the observed drought disaster and phenophase records of summer maize in the Huang-Huai-Hai region (HHH). Drought samples constructed from regional drought records and the Yearbook of Meteorological Disasters in China were used for drought validations. The results exhibited high accuracy (78.04% of total drought samples correctly showing complete correspondence with historical records regarding drought grades, and 96.90% of drought samples being within one drought grade level). Additionally, compared with the Crop Water Deficit Index (CWDI), the temporal and spatial evolution of typical drought processes were more accurately characterized by VWI. The results of this study provide a scientific basis and achieve quantitative monitoring for daily drought assessment of summer maize in HHH, and also provide a new perspective in dynamic and quantitative monitoring of agricultural disasters over large regions based on actual disaster records and remotely sensed images.

Organic Osmolytes Regulate Substomatal Apoplast Water Potential in Pea (Pisum sativum L.) Leaves during Mild Drought

Organic Osmolytes Regulate Substomatal Apoplast Water Potential in Pea (Pisum sativum L.) Leaves during Mild Drought

Morphological and Molecular Diversity of Traditional Upland Rice (Oryza sativa L.) Varieties for Drought Tolerance at Seedling Stage

Drought is considered the major threat and most damaging abiotic stress for rice production.However, some traditional upland rice varieties (TURVs) may have some forms of tolerance to various stresses compared to new elite varieties. Two experiments were conducted. Experiment to determine the morpho-physiological response, phenotypic diversity, and similarity of 13 TURVs and 2 check varieties to mild drought stress at the seedling stage (Experiment 1 (E1) and to determine the molecular diversity and genetic similarity of the genotypes using selected simple sequence repeat (SSR) markers ((Experiment 2 (E2). In E1, all TURVs were highly tolerant under mild drought stress for a physiological response. Standardized Shannon-Weaver Diversity Index(H’) showed zero to low phenotypic diversity for qualitative traits. However, the phenotypic diversity of quantitative traits ranged from moderate to high for well-watered conditions, low to high for drought conditions, and moderate to high for re-watered conditions. Cluster analysis through Ward’s minimum variance based on pooled phenotypic data grouped the genotypes into three major clusters at 7 Euclidean distances. For E2, polymorphic information content values from 24 polymorphic SSR markers ranged from slightly informative (RM256) to highly informative (RM206), with a mean of 0.61. Nei’s gene diversity mean was 0.62 and values varied from 0.26 (RM256) to 0.86 (RM206). Based on Jaccard’s similarity coefficient, rice genotypes were grouped into nine minor clusters. The results indicate that TURVs harbor moderate to high allelic diversity and there are potential tolerance genes for mild drought stress that can be utilized in breeding programs for drought-tolerant rice varieties.

Original

The present study attempts to assess drought in the Tel River basin, the second largest tributary of Mahanadi flowing through one of the most drought-frequented regions, viz. Nabarangpur, Kalahandi, Bolangir, Boudh, and Kandhamal districts of Odisha using Standard Precipitation Index (SPI). The SPI is one of the most widely used indices for monitoring drought based on rainfall data. It expresses the actual rainfall as a standardized departure concerning the rainfall probability distribution function. The values of SPI are expressed in standard deviations, with positive SPI indicating greater than median precipitation and negative values indicating less than median precipitation. A monthly time series climatic dataset is obtained from the NASA power data for 15 meteorological observation sites around the study basin from 1981 to 2021. The long-term data is then fitted to a probability distribution to create a normal distribution to find the cumulative probability of an observed precipitation event for the given month and time scale at the location in question. The cumulative probability H(x) is then converted to the conventional normal random variable z with a mean of zero and a variance of one yielding the SPI value. A drought event occurs when the index reaches -1.0 or below continuously. For three-time scale analysis of three months SPI 3, six months SPI 6, and twelve months SPI, DrinC software and Arc GIS 10.5 are used. The result shows that in the 40 years (1981-2021), 67 per cent of the droughts have been mild droughts, 18 per cent moderate droughts, 10 per cent severe droughts, and 5 per cent extreme droughts in the study basin. The regional distribution at the sub-basin level did not show any significant pattern based on the selected years of drought in the study basin.

Multi-omics reveals the sugarcane rhizosphere soil metabolism-microbiota interactions affected by drought stress

Drought is considered one of the most damaging stresses affecting crop productivity. Although rhizosphere bacterial communities contribute to improved crop resistance, little is known about the dynamics of these communities in sugarcane under various drought conditions. The rhizosphere bacterial community structure results from a series of complex interactions and feedback between plant roots, bacteria, and the soil physicochemical environment. Therefore, in the current study, we assessed the impact of root phenomes, soil metabolites, soil nutrients, and other multi-omics factors on rhizosphere bacterial community structure under different levels of drought stress. The results showed that different degrees of drought stress may strongly affect bacterial community structure and function by affecting rhizosphere soil metabolite composition. Specifically, sugarcane under mild drought may improve soil nutrient availability and provide an abundant carbon source for bacteria through diversifying rhizosphere soil metabolites (maybe via root exudation). In addition, rhizosphere bacteria may also produce derived metabolites to cross-feed other rhizosphere bacteria to stabilize the bacterial community under mild drought. When drought stress intensifies, the hosts recruit specific bacterial populations to resist drought stress by releasing metabolites and reducing community diversity through this recruitment. In particular, we found that Streptomyces had the greatest contribution to the stress-related microbiota recruited by sugarcane under high drought stress levels. This may be an important target for sugarcane drought-resistance microbiome engineering. This study provides a novel theoretical foundation for improving the stress resistance of sugarcane under different drought stress levels by optimizing the bacterial community.

Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia

Abstract The contribution of this paper is to assess the drought patterns using the Land Surface Temperature (LST) estimation index and examine the correlation between the Normalized Difference Vegetation Index (NDVI). The main objective was to evaluate the spatiotemporal variation in agricultural drought patterns and severity in order to estimate and measure climate variability. According to the study's findings, the region experienced mild to severe meteorological drought periods 15–18 times over the study period. The majority of these periods (62.72%) were classified as mild drought (unusual dry circumstances), which usually only showed a slight departure from the distribution of rainfall that is close to normal. According to the findings, cropping seasons from 2013 to 2022 saw an increase in agricultural dryness and a decrease in grain yield, with varying degrees of severity in different geographic locations. Based on the result, the major difficulties and challenges identified were the shortage of drinking water, and impacts on air quality, and food and nutrition. Accordingly, agricultural drought risk mapping can be utilized to mitigate the risk associated with drought on agricultural productivity and guide decision-making processes in drought monitoring.

Nitrogen uptake preference and allocation in Populus cathayana in response to drought stress

The preference for different nitrogen (N) forms may enhance plant survival and fitness. However, little information is known about how soil water availability, N addition, and their interaction dynamically impact plant N uptake preference and allocation. Here, we conducted a pot experiment using Populus cathayana cuttings, consisting of soil water regime (well watering control/mild drought/intensive drought: 80/60/40 % of field capacity) combined with N addition (N0 as control/N4/N8: 0/4/8 g N m−2 yr−1) treatments based on 15N isotope tracer technology. Two tracer solution (15NH4NO3/NH415NO3, both at 10.2 atom%) were used in N4/N8 treatments. Root, stem and leaf were collected at 6 h, 1, 3, 7, 14, and 31 days after labeling. Results showed that N addition significantly increased plant biomass and N accumulation, and decreased N allocation to leaf. Drought significantly decreased plant biomass, N accumulation, and N uptake (indicated by δ15N), and intensive drought reduced more than mild drought did. Nitrogen allocation to leaf was increased by drought. NO3- uptake by P. cathayana (indicated by δ15N in NH415NO3 treatment) was correlated significantly positively with total root length (TRL), total root surface area (TRA), specific root length (SRL), specific root area (SRA), root vitality, and root nitrate reductase (NR) activity. Intensive drought significantly reduced TRL, TRA, SRL, SRA, root vitality, and root NR activity under N4 and N8 treatments, which resulted δ15N in NH415NO3 treatment reduction and lower than in 15NH4NO3 treatment, so P. cathayana exhibited ammonium preference under intensive drought treatment. Our study provides an essential insight into how plants adapt and prefer different N forms under drought stress in nature.

Responses of Trollius chinensis to drought stress and rehydration: From photosynthetic physiology to gene expression

Drought stress occurs more frequently in recent years due to the global climate change. Widely distributed in northern China, Mongolia, and Russia, Trollius chinensis Bunge has high medicinal and ornamental values and is often exposed to drought stress, while the mechanism underlying its drought response is still unclear. In this study, we applied 74–76% (control, CK), 49–51% (mild drought), 34–36% (moderate drought), and 19–21% (severe drought, SD) of the soil gravimetric water content to T. chinensis, and measured leaf physiological characteristics on the 0, 5th, 10th, 15th day after the soil reaching the set drought severities, and on the 10th day after rehydration. The results showed that many physiological parameters, such as chlorophyll contents, Fv/Fm, ΦPSⅡ, Pn, and gs decreased with the deepening of severity and duration of drought stress and recovered to some extent after rehydration. On the 10th day of drought stress, leaves in SD and CK were selected for RNA-Seq, and 1649 differentially expressed genes (DEGs) were found, including 548 up-regulated and 1101 down-regulated DEGs. Gene Ontology enrichment found that the DEGs were mainly enriched in catalytic activity and thylakoid. Koyto Encyclopedia of Genes and Genomes enrichment found that DEGs were enriched in some metabolic pathways such as carbon fixation and photosynthesis. Among them, the differential expression of genes related to photosynthesis process, ABA biosynthesis and signaling pathway, such as NCED, SnRK2, PsaD, PsbQ, and PetE, might explain why T. chinensis could tolerate and recover from as long as 15 days of severe drought conditions.

An improved global vegetation health index dataset in detecting vegetation drought

Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981–2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.

Mineral Nutrient Uptake, Accumulation, and Distribution in Cunninghamia lanceolata in Response to Drought Stress.

Mineral accumulation in plants under drought stress is essential for drought tolerance. The distribution, survival, and growth of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), an evergreen conifer, can be affected by climate change, particularly seasonal precipitation and drought. Hence, we designed a drought pot experiment, using 1-year-old Chinese fir plantlets, to evaluate drought effects under simulated mild drought, moderate drought, and severe drought, which corresponds to 60%, 50%, and 40% of soil field maximum moisture capacity, respectively. A treatment of 80% of soil field maximum moisture capacity was used as control. Effects of drought stress on mineral uptake, accumulation, and distribution in Chinese fir organs were determined under different drought stress regimes for 0-45 days. Severe drought stress significantly increased phosphorous (P) and potassium (K) uptake at 15, 30 and 45 days, respectively, within fine (diameter < 2 mm), moderate (diameter 2-5 mm), and large (diameter 5-10 mm) roots. Drought stress decreased magnesium (Mg) and manganese (Mn) uptake by fine roots and increased iron (Fe) uptake in fine and moderate roots but decreased Fe uptake in large roots. Severe drought stress increased P, K, calcium (Ca), Fe, sodium (Na), and aluminum (Al) accumulation in leaves after 45 days and increased Mg and Mn accumulation after 15 days. In stems, severe drought stress increased P, K, Ca, Fe, and Al in the phloem, and P, K, Mg, Na, and Al in the xylem. In branches, P, K, Ca, Fe, and Al concentrations increased in the phloem, and P, Mg, and Mn concentrations increased in the xylem under severe drought stress. Taken together, plants develop strategies to alleviate the adverse effects of drought stress, such as promoting the accumulation of P and K in most organs, regulating minerals concentration in the phloem and xylem, to prevent the occurrence of xylem embolism. The important roles of minerals in response to drought stress should be further evaluated.

Heat-Priming during Somatic Embryogenesis Increased Resilience to Drought Stress in the Generated Maritime Pine (Pinus pinaster) Plants.

Drought stress is becoming the most important factor of global warming in forests, hampering the production of reproductive material with improved resilience. Previously, we reported that heat-priming maritime pine (Pinus pinaster) megagametophytes during SE produced epigenetic changes that generated plants better adapted to subsequent heat stress. In this work, we tested, in an experiment performed under greenhouse conditions, whether heat-priming will produce cross-tolerance to mild drought stress (30 days) in 3-year-old priming-derived plants. We found that they maintain constitutive physiological differences as compared to controls, such as higher proline, abscisic acid, starch, and reduced glutathione and total protein contents, as well as higher ΦPSII yield. Primed plants also displayed a constitutive upregulation of the WRKY transcription factor and the Responsive to Dehydration 22 (RD22) genes, as well as of those coding for antioxidant enzymes (APX, SOD, and GST) and for proteins that avoid cell damage (HSP70 and DHNs). Furthermore, osmoprotectants as total soluble sugars and proteins were early accumulated in primed plants during the stress. Prolongated water withdrawal increased ABA accumulation and negatively affected photosynthesis in all plants but primed-derived plants recovered faster than controls. We concluded that high temperature pulses during somatic embryogenesis resulted in transcriptomic and physiological changes in maritime pine plants that can increase their resilience to drought stress, since heat-primed plants exhibit permanent activation of mechanisms for cell protection and overexpression of stress pathways that pre-adapt them to respond more efficiently to soil water deficit.

Effects of combined drought and pathogen stress on growth, resistance, and gene expression in young Norway spruce trees.

Drought-induced mortality is a major direct effect of climate change on tree health, but drought may also affect trees indirectly by altering their susceptibility to pathogens. Here we report how a combination of mild or severe drought and pathogen infection affected growth, pathogen resistance, and gene expression in potted 5-year-old Norway spruce trees (Picea abies). After 5weeks of drought, trees were inoculated with the fungal pathogen Endoconidiophora polonica. Combined drought-pathogen stress over the next 8weeks led to significant reductions in growth of drought-treated trees relative to well-watered trees, and more so in trees subjected to severe drought. Belowground, growth of the smallest fine roots was most affected. Aboveground, shoot diameter change was most sensitive to the combined stress, followed by shoot length growth and twig biomass. Both drought-related and some resistance-related genes were upregulated in bark samples collected after five weeks of drought (but before pathogen infection), and gene expression levels scaled with the intensity of drought stress. Trees subjected to severe drought were much more susceptible to pathogen infection than well-watered trees or trees subjected to mild drought. Overall, our results show that mild drought stress may increase tree resistance to pathogen infection by upregulating resistance-related genes. Severe drought stress, on the other hand, decreased tree resistance. Because drought episodes are expected to become more frequent with climate change, combined effects of drought and pathogen stress should be studied in more detail to understand how these stressors interactively influence tree susceptibility to pests and pathogens.