Drought Research Articles

Rescue and return: Translocating a semi‐wild platypus (Ornithorhynchus anatinus) population during the 2019 drought

SummaryPlatypus (Ornithorhynchus anatinus) are an endemic Australian freshwater mammal, impacted by synergistic threats across their range. During the extreme drought of 2017–2019, declining water levels threatened Platypus at Tidbinbilla Nature Reserve (TNR), Australian Capital Territory (ACT), Australia. TNR supports a population of Platypus, occupying interconnected ponds within a predator proof fence. During drought conditions in 2019, Platypuses could not move out of the fenced area to refugia as floodgates were closed due to low water levels. In winter of 2019, eight Platypuses were found deceased resulting from starvation. By December, water levels were extremely low and ponds were continuing to dry. Given these circumstances, a rescue intervention was undertaken to capture stranded Platypuses. They were temporarily relocated and housed at Taronga Zoo, Sydney, until they were returned when conditions at TNR improved. Seven Platypuses were rescued, with five successfully housed at Taronga for 5 months. One Platypus was lost after escaping from its enclosure and another Platypus died when trapped in a crevice. The Platypuses were returned after water levels increased at TNR and were monitored for 500 days post‐release, demonstrating successful repatriation. This case study outlines the key stages and considerations required for this intervention, providing critical information for rescue attempts on drought‐affected Platypus populations. There is a need to continue developing a decision framework for interventions of climate‐affected populations, including quantifying trigger thresholds and conservation prioritisation of populations. This will become increasingly necessary given the trajectories of habitat degradation, coupled with the increasingly frequent and severe droughts, expected under anticipated climate change scenarios.

Oryza sativa Stress Associated Protein (OsSAP) Promoter Modulates Gene Expression in Response To Abiotic Stress by Utilizing Cis Regulatory Elements Within The Promoter Region

The occurrence of extreme weather patterns induced by climate change has resulted in abiotic stress problems impacting the growth and productivity of plants. Rice (Oryza sativa), a staple food source for most Asians, is similarly affected by these challenges. Previous studies have identified the Oryza sativa Stress Associated Protein (OsSAP) genes to play a significant role in responding to abiotic stress. Among the 18 Stress Associated Protein members, OsSAP4 was highly expressed during drought and salinity conditions. Therefore, further experiments have been conducted, focusing specifically on the promoter region, to comprehend its regulation in response to abiotic stresses. Various types of cis-elements binding sites have been identified within the OsSAP4 promoter, encompassing MYB, CAMTA, CPP, C3H, HDZIP, bZIP, WRKY, and ERF. However, promoter analysis revealed that the distribution of the Cis-Regulatory elements bound by the Ethylene Response Factor (ERF) was the most prominent in the OsSAP4 promoter. Consequently, an analysis of promoter regulation was conducted using GUS reporter in Arabidopsis thaliana (A. thaliana) on two different sizes of OsSAP4 promoter sequences, each containing different quantities of ERF transcription factor binding sites. A noticeable difference in GUS staining activity was observed between pOsSAP4(1524 pb)::GUS and pOsSAP4(460 pb)::GUS, where pOsSAP4(1524 pb)::GUS exhibited higher GUS staining activity than pOsSAP4(460 pb)::GUS. The differences in GUS staining analysis are evident at the vegetative stage (leaf), silique, and inflorescence stages. This implies the participation of various other cis-element binding sites that influence the expression pattern of the OsSAP4 promoter during abiotic stress.

Advancing Knowledge in Forest Water Use Efficiency Under Global Climate Change Through Scientometric Analysis

Forests are critical in regulation of carbon and water cycles and mitigation of climate change. Forest water-use efficiency (WUE) refers to the ratio of biomass produced (or assimilated carbon) to the amount of water used by forests, which indicates how effectively a forest utilizes water to achieve productivity. Climate change and its impact on forest WUE are important research directions that explore the complex relationship between global environmental change and the forest ecosystem dynamics. The global intensification of climate change underscores the need for an inclusive understanding of forest water use and makes it crucial to know how forests balance carbon and water resources, which is essential for effective forest management and predicting ecosystem responses to climate change. This study aims to comprehensively and objectively analyze current research trends and future directions related to the response of forest WUE to climate change. Our database included 1755 research papers from the Web of Science Core Collection, spanning from 2000 to 2023. Our analysis included cooperative networks of countries, authors, and institutions, as well as the most frequently cited journals and articles, keyword co-occurrence analysis, and a keyword burst analysis. The results showed that the top cooperative country, author, and institution is PR China, Prof. Dr. Jesús Julio Camarero from the Consejo Superior de Investigaciones Científicas (CSIC), and the Chinese Academy of Sciences, respectively. The leading journal in this field is “Global Change Biology”. Critical research hot topics include gas exchange, modeling, altitudinal gradients, tree growth dynamics, net carbon exchange, global change drivers, tropical forests, nitrogen stoichiometry, Northern China plains, and extreme drought conditions. Frontier topics that have emerged in recent years include studies on China’s Loess Plateau, stable isotopes, radial growth, gross primary productivity, and Scots pine. The insights from this analysis are vital for researchers, decision-makers, and forestry professionals aiming to mitigate the impacts of climate change on forest WUE and overall ecosystem health and resilience. This study emphasizes the importance of sustained research efforts and global research collaboration in addressing the intricate challenges posed by climate change to forest ecosystems.

Adapting to Climate Change with Machine Learning: The Robustness of Downscaled Precipitation in Local Impact Analysis

The skill, assumptions, and uncertainty of machine learning techniques (MLTs) for downscaling global climate model’s precipitation to the local level in Bolivia were assessed. For that, an ensemble of 20 global climate models (GCMs) from CMIP6, with random forest (RF) and support vector machine (SVM) techniques, was used on four zones (highlands, Andean slopes, Amazon lowlands, and Chaco lowlands). The downscaled series’ skill was evaluated in terms of relative errors. The uncertainty was analyzed through variance decomposition. In most cases, MLTs’ skill was adequate, with relative errors less than 50%. Moreover, RF tended to outperform SVM. Robust (weak) stationary (perfect prognosis) assumptions were found in the highlands and Andean slopes. The weakness was attributed to topographical complexity. The downscaling methods were shown to be the dominant source of uncertainties. This analysis allowed the derivation of robust future projections, showing higher annual rainfall, shorter dry spell duration, and more frequent but less intense high rainfall events in the highlands. Apart from the dry spell’s duration, a similar pattern was found for the Andean slopes. A decrease in annual rainfall was projected in the Amazon lowlands and an increase in the Chaco lowlands.

Impact of Mild Field Drought on the Aroma Profile and Metabolic Pathways of Fresh Tea (Camellia sinensis) Leaves Using HS-GC-IMS and HS-SPME-GC-MS.

Aroma plays a pivotal role in defining tea quality and distinctiveness, and tea producers have often observed that specific drought conditions are closely associated with the formation and accumulation of characteristic aroma compounds in tea leaves. However, there is still limited understanding of the differential strategies employed by various tea cultivars in response to drought stress for the accumulation of key volatile aroma compounds in fresh tea leaves, as well as the associated metabolic pathways involved in aroma formation. In this study, two widely cultivated tea cultivars in China, Fuding Dabai (FD) and Wuniuzao (WNZ), were examined to assess the impact of mild field drought stress on the composition and accumulation of key volatile aroma compounds in fresh leaves using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase micro-extraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) technologies. Results revealed that drought stress led to a substantial increase in the diversity of volatile compounds (VOCs) in FD, while WNZ exhibited a notable rise in low-threshold VOC concentrations, amplifying sweet, floral, fruity, and earthy aroma profiles in post-drought fresh leaves. Through partial least squares discriminant analysis (PLS-DA) of HS-GC-IMS and HS-SPME-GC-MS data, integrating variable importance projection (VIP) scores and odor activity values (OAVs) above 1, 9, and 13, key odor-active compounds were identified as potential markers distinguishing the drought responses in the two cultivars. These compounds serve as crucial indicators of the aromatic profile shifts induced by drought, providing insights into the differential metabolic strategies of the cultivars. Additionally, KEGG enrichment analysis revealed 12 metabolic pathways, such as terpenoid biosynthesis, fatty acid synthesis, cutin, suberine, and wax biosynthesis, and phenylalanine metabolism, which may play crucial roles in the formation and accumulation of VOCs in tea leaves under drought stress. These findings provide a comprehensive framework for understanding the cultivar-specific mechanisms of aroma formation and accumulation in tea leaves under mild drought conditions.

Leveraging leaf spectroscopy to identify drought-tolerant soybean cultivars

Understanding cultivars' physiological traits variations under abiotic stresses is critical to improve phenotyping and selections of resistant crop varieties. Traditional methods of accessing physiological traits in plants are costly and time consuming, which prevents their use in breeding programs. Spectroscopy data and statistical approaches such as partial least square regression could be applied to rapidly collect and predict several physiological parameters at leaf-level, allowing phenotyping several genotypes in a high-throughput manner. We collected spectroscopy data of twenty soybean cultivars planted under well-watered and drought conditions during the reproductive phase. At 20 days after drought was imposed, we measured leaf pigments content (chlorophyll a and b, and carotenoids), specific leaf area, electrons transfer rate, and photosynthetic active radiation. At 28 days after drought imposition, we measured leaf pigments content, specific leaf area, relative water content, and leaf temperature. Partial least square regression models accurately predicted leaf pigments content, specific leaf area, and leaf temperature (cross-validation R2 ranging from 0.56 to 0.84). Discriminant analysis using 54 wavelengths was able to select the best-performance cultivars regarding all evaluated physiological traits. We showed the great potential of using spectroscopy as a feasible, non-destructive, and accurate method to estimate physiological traits and screening of superior genotypes.

Detection of changes in local-scale statistical distribution of daily temperature and precipitation in dryland region: a case study of Ningxia, China

Identifying alterations in the local-scale statistical distributions of daily temperature indices and precipitation is crucial for adapting to climate change and combating desertification in arid regions. This study focuses on Ningxia, a representative dryland area in China, where we investigated changes in the statistical distributions of daily temperature and precipitation across ten weather stations over two 30-year periods: 1991–2020 compared to 1961–1990. From 1961 to 2020, annual air temperature indices (mean, maximum, and minimum) exhibited a significant upward trend at all ten weather stations (P < 0.05). Specifically, when comparing the decades of 1961–1970 with those of 2001–2020, annual air temperature indices increased by 1.2–2.2 °C for annual air temperatures, by 0.91–1.97 °C for maximum air temperature, and by 1.26–3.28 °C for minimum air temperature; these corresponded to rates of increase ranging from 0.20–0.40 °C per decade for mean air temperatures, from 0.15–0.33 °C per decade for maximum air temperatures, and from 0.21–0.55 °C per decade for minimum air temperatures, respectively during this period. The observed differences in the statistical distributions of daily temperature indices between the two periods were statistically significant (P < 0.05), indicating an increase rate of approximately 1 °C during the period from 1991 to 2020 relative to that from 1961 to 1990 across various weather stations. In contrast, there were no significant increasing or decreasing trends in annual precipitation (P > 0.05). Similarly, the changes in statistical distributions of daily precipitation also did not reach a significance level (P > 0.05) when comparing data from both periods within these stations. Furthermore, the correlation coefficients between daily temperature indices and daily precipitation have decreased across these stations during the later period compared to earlier years. These findings suggest that while there has been a notable shift toward higher values in the statistical distribution of daily temperature indices—indicating rising temperatures—the corresponding distribution patterns for daily precipitation have remained relatively stable between these time frames. Consequently, this research confirmed an escalation in localized drought conditions within certain dryland areas despite broader regional trends toward humidification observed over recent decades; thus implying an increased risk of desertification as aridity intensifies.

Drought field experiments: how to adapt rainout shelters to agroforestry?

AbstractAgroforestry could be a major strategy to adapt agriculture to climate change, thanks to the microclimate effects of trees and improved infiltration. However, the experimental validation of these claims is scarce. In this methodological review, we discuss options for the experimental simulation of drought conditions in agroforestry field experiments, comparing it with strategies adopted in natural, agricultural, or forestry ecosystems. We classify rainout shelters used in field experiments according to mobility, completeness of rain interception and height of rainout shelter. We show that specificities of agroforestry systems create constraints and require compromises in the design and operation of rainout shelters. We conclude that large rainout shelters, which induce drought for both the trees and the crops while limiting artifacts and biases, would be most relevant for studying the resistance of agroforestry systems to drought. Unfortunately, the review of rainout shelters already used in agroforestry systems reveals a lack of rainout shelters capable of intercepting rain on both trees and crops, achieving total rain interception, while being relatively low-cost and manageable by a small team. Therefore, we benchmark three novel rainout shelter designs that we tested in a mature agroforestry system under Mediterranean climatic conditions. We discuss their advantages and disadvantages in terms of both scientific and operational aspects. While compromises had to be done between experimental design, risks of artifact/bias, effectiveness, ease of installation, operation and maintenance, and agricultural management, these prototypes are starting points for achieving well-performing rainout shelters and testing the effects of drought in agroforestry experiments.

Seasonal shifts in depth-to-water uptake by young thinned and overstocked lodgepole pine (Pinus contorta) forests under drought conditions in the Okanagan Valley, British Columbia, Canada

Abstract. As drought and prolonged water stress become more prevalent in dry regions under climate change, preserving water resources becomes a focal point for maintaining forest health. Forest regeneration after forest loss or disturbance can lead to overstocked juvenile stands with high water demands and low water-use efficiency. Forest thinning is a common practice with the goal of improving tree health, carbon storage, and water use while decreasing stand demands in arid and semi-arid regions. However, little is known about the impacts of stand density on seasonal variation in depth-to-water uptake or the magnitude of the effect of growing season drought conditions on water availability. Existing reports are highly variable by climatic region, species, and thinning intensity. In this study, stable isotope ratios of deuterium (δ2H) and oxygen (δ18O) in water collected from various soil depths and from branches of lodgepole pine (Pinus contorta) under different degrees of thinning (control: 27 000 stems per hectare; moderately thinned: 4500 stems per hectare; heavily thinned: 1100 stems per hectare) over the growing season were analyzed using the MixSIAR Bayesian mixing model to calculate the relative contributions of different water sources in the Okanagan Valley in the interior of British Columbia, Canada. We found that under drought conditions the lodgepole pine trees shifted their depth-to-water uptake through the growing season (June to October) to rely more heavily on older precipitation events that percolated through the soil profile when shallow soil water became less accessible. Decreased forest density subsequent to forest thinning did not cause a significant difference in the isotopic composition of branch water but did cause changes in the timing and relative proportion of water utilized from different depths. Thinned lodgepole pine stands were able to maintain water uptake from 35 cm below the soil profile, whereas the overstocked stands relied on a larger proportion of deep soil water and groundwater towards the end of the growing season. Our results support other findings by indicating that, although lodgepole pines are drought-tolerant and have dimorphic root systems, they do not shift back from deep water sources to shallow soil water when soil water availability increases following precipitation events at the end of the growing season.

Co-applied biochar and drought tolerant PGPRs induced more improvement in soil quality and wheat production than their individual applications under drought conditions.

Plant growth and development can be greatly impacted by drought stress. Suitable plant growth promoting rhizobacteria (PGPR) or biochar (BC) application has been shown to alleviate drought stress for plants. However, their co-application has not been extensively explored in this regard. We isolated bacterial strains from rhizospheric soils of plants from arid soils and characterized them for plant growth promoting characteristics like IAA production and phosphate solubilization as well as for drought tolerance. Three bacterial strains or so called PGPRs, identified as Bacillus thuringiensis, Bacillus tropicus, and Bacillus paramycoides based on their 16S rRNA, were screened for further experiments. Wheat was grown on normal, where soil moisture was maintained at 75% of water holding capacity (WHC), and induced-drought (25% WHC) stressed soil in pots. PGPRs were applied alone or in combination with a biochar derived from pyrolysis of tree wood. Drought stress substantially inhibited wheat growth. However, biochar addition under stressed conditions significantly improved the wheat growth and productivity. Briefly, it increased straw yield by 25%, 100-grain weight by 15% and grain yield by 10% compared to the control. Moreover, co-application of biochar with PGPRs B. thuringiensis, B. tropicus and B. paramycoides further enhanced straw yield by 37-41%, 100-grain weight by 30-36%, and grain yield by 22-22.57%, respectively. The co-application also enhanced soil quality by increasing plant-available phosphorus by 4-31%, microbial biomass by 33-45%, and soil K+/Na+ ratio by 41-44%. Co-application of PGPRs and biochar alleviated plant drought stress by improving nutrient availability and absorption. Acting as a nutrient reservoir, biochar worked alongside PGPRs, who solubilized nutrients from the former and promoted wheat growth. We recommend that the co-application of suitable PGPRs and biochar is a better technology to produce wheat under drought conditions than using these enhancers separately.

Evaluating and Predicting Meteorological Drought Using Different Climate Reanalysis Datasets over New South Wales, Australia

AbstractDroughts are one of the most disastrous natural hazards, primarily due to their persistence and spatial distribution. Drought prediction is one of the key challenges for effective drought management and to do so, studies often involve the use of station-based data which are effective only in regions with high-gauge density. Therefore, there is growing interest in the use of interpolated climatic grids to predict droughts. In recent decades, drought conditions have been aggravated by climate change and for that reason the use of climatic variables is important to accurately predict droughts. The analysis of any aspect of drought can be affected by the choice of data and drought index. Therefore, this study aims to identify the most suitable dataset and drought index for the New South Wales (NSW) region of Australia. The present study evaluates various precipitation datasets (Climate Research Unit (CRU), ERA-5, and Scientific Information for Land Owners (SILO)) and their corresponding variations on the Standardised Precipitation Index (SPI) at different time scales. Based on the findings, CRU was used to predict meteorological drought using machine learning techniques. The different machine learning models are Support Vector Regression, Random Forest and Artificial Neural Networks. The results suggest SVM to be the best performing model among these models for predicting SPI at short time scales (1 month and 3 month) and ANN to be the best performing model for long-term scales (6 months and 12 months). Such findings depict the capabilities of different models in examining drought characteristics and confirming the use of interpolated climatic grids thereby assisting in regional drought management.

Physiological Behavior of Rubber Plants (&lt;i&gt;Hevea Brasilliensis&lt;/i&gt;) to Different Soil Moisture Conditions

Drought conditions can severely impact rubber (&lt;i&gt;Hevea brasiliensis&lt;/i&gt;) plantations, leading to economic loss in Malaysia. The study aimed to assess the impact of varying soil moisture levels on the physiological characteristics of five latex timber clones (LTCs) of rubber, with the goal of identifying the most suitable clone for specific soil moisture conditions. These conditions include (1) field capacity, (2) 75% available water (AW), (3) 50% AW, (4) 25% AW, and (5) wilting point, with the ultimate objective of optimizing cultivation methods and fostering sustainable rubber production in Malaysia. The five clones under investigation include RRIM3001, RRIM2025, RRIM2001, RRIM928, and PB350. Leaf chlorophyll content, stomatal conductance, and net photosynthesis were measured 4 and 8 months after treatment (MAT). The findings indicated significant effects of moisture stress on various physiological attributes, including total chlorophyll content, relative chlorophyll content, stomatal conductance, and net photosynthesis rate. At 4 and 8 MATs, the clones subjected to field capacity exhibited the highest values for these physiological characteristics, followed by those exposed to 75% available water, with the lowest values observed at the wilting point. RRIM3001 consistently exhibited the highest total chlorophyll content, stomatal conductance, and net photosynthesis among the clones at both sampling dates. The highest net photosynthesis was observed in the RRIM3001 clone under field capacity conditions. Furthermore, a significant positive correlation was identified between total chlorophyll and relative chlorophyll contents, as well as between net photosynthesis and stomatal conductance. These findings carry practical implications for water management during the initial growth phase of rubber seedlings and for replanting initiatives in rubber plantations.

Comparative Study on the Response of Hyssop (Hyssopus officinalis L.), Salvia (Salvia officinalis L.), and Oregano (Origanum vulgare L.) to Drought Stress Under Foliar Application of Selenium.

Drought is one of the most important abiotic factors limiting plant productivity. Although the aromatic plants of the Lamiaceae family often grow in arid regions, drought tolerance varies greatly among the different species of this family. The effect of induced drought stress can be reduced by the application of selenium. The current study aims to compare the growth and biochemical responses of three species of the Lamiaceae family (hyssop, salvia, and oregano) to drought stress and the possibility of reducing the effect of stress in these plants by foliar treatment with selenium. Drought stress reduced the fresh and dry biomass of hyssop (by 35% and 15%), salvia (by 45% and 41%), and oregano (by 51% and 32%). Se treatment did not affect the growth of plants under drought stress, but it improved relative water content in hyssop and salvia under moderate drought conditions. A reduction in the content of chlorophyll a and chlorophyll b (in hyssop and salvia). In addition, an increase in the content of hydrogen peroxide (in oregano and salvia), malondialdehyde, and proline in plants cultivated under drought conditions was observed. Se treatment led to reduced levels of hydrogen peroxide and malondialdehyde, along with an increase in chlorophyll a content (in hyssop and oregano) and proline content. The response of the antioxidant system depended on the plant species. Hyssop exhibited a significant increase in glutathione peroxidase, superoxide dismutase, and peroxidase activities. Oregano showed enhanced catalase activity. Salvia experienced a sharp increase in ascorbic acid content. Se treatment stimulated the accumulation of phenolic compounds and increased glutathione peroxidase activity in all studied species.

Genome-Wide Analysis of the MAPKKK Gene Family Under Abiotic Stresses in Moso Bamboo (Phyllostachys edulis)

Mitogen-activated protein kinase kinase kinases (MAPKKKs) are the upstream components of MAPK cascades and are involved in mediating stress responses and developmental processes. Although MAPKKK genes have been investigated in many plants, the identification and characterization of MAPKKKs in moso bamboo were still limited. Here, 134 MAPKKKs were identified as unevenly distributed on 23 chromosomes (except for chromosome 1) of moso bamboo and divided into three subfamilies by phylogenetic analysis. The gene structure and conserved motif of PeMAPKKKs were investigated. The expansions of PeMAPKKKs were driven by whole-genome duplication (WGD) or segmental duplication events. The duplicated gene pairs were under purifying selection based on the Ka/Ks ratios, suggesting they underwent functional conservation. Most PeMAPKKKs contained cis-elements related to development, hormones, and stress responses. Tissue expression patterns showed that PeMAPKKKs had multiple expression patterns. The qPCR analysis showed distinct expression patterns of PeMAPKKKs under drought, salt, and cold stress conditions. Taken together, this study provides a solid foundation for future functional characterizations of MAPKKKs and identifies candidate stress-responsive genes for further study in moso bamboo.

Unlocking the Potential of Teff for Sustainable, Gluten-Free Diets and Unravelling Its Production Challenges to Address Global Food and Nutrition Security: A Review.

Sustainable diets, as defined by the Food and Agriculture Organisation, aim to be nutritionally adequate, safe, and healthy, while optimising natural and human resources. Teff (Eragrostis tef), a gluten-free grain primarily grown in Ethiopia, has emerged as a key contender in this context. Widely regarded as a "supergrain", teff offers an outstanding nutrition profile, making it an excellent choice for people with gluten-related disorders. Rich with protein, essential amino acids, polyunsaturated fats, and fibre, and abundant in minerals like calcium and iron, teff rivals other popular grains like quinoa and durum wheat in promoting human health. Beyond its nutritional benefits, teff is a hardy crop that thrives in diverse climates, tolerating both drought and waterlogged conditions. Due to its resilience and rich nutrient content, teff holds the potential to address nine of the 17 United Nations' Sustainable Development Goals (SDGs), including SDG 1 (no poverty), SDG 2 (zero hunger), and SDG 3 (good health and wellbeing), which are tied to improving food and nutrition security. However, teff production in Ethiopia faces significant issues. Traditional farming practices, insufficient storage infrastructure, and food safety challenges, including adulteration, hinder teff's full potential. This review explores teff's dual role as a nutritious, sustainable food source and outlines the key challenges in its production to conclude on what needs to be done for its adoption as a golden crop to address global food and nutrition security.

THE IMPACT OF SEED SIZE ON INITIAL DROUGHT STRESS RESILIENCE AND YIELD IN WHEAT CULTIVATION

Wheat yield is affected severely by drought in this era of changing climate patterns, including high temperatures and altered precipitation patterns. Drought is among the most challenging environmental stressors, limiting wheat cultivars' growth, productivity, and performance. The current study was conducted during the rabi season 2022 at the Research Area, Department of Agronomy, University of the Punjab, Lahore, Pakistan. Therefore, the present study evaluated the potential of diverse seed sizes to advance wheat crop growth, development, and yield when subjected to different drought levels. The study comprised two experiments. The first was a lab experiment that included different drought levels (DL), DL0: 0.0 bar, DL1: -2 bar, DL2: -4 bar, and DL3: -6 bar (drought levels were induced by solutions of PEG-6000 at different concentrations) and three wheat seed size classes, i.e., bold grain (&gt;38 g), medium grain (&lt;33 g), and small grain (&lt;25 g). In the field experiment, drought stress levels were DL0 (regular irrigation), DL1 (first irrigation at 30 days), DL2 (first irrigation at 45 days), and DL3 (first irrigation at 60 days). Seed sizes included W1 (bold &gt;38 g), W2 (medium &lt;33 g), and W3 (small &lt;25 g). Drought severity increased with DL1 to DL3. The outcomes of the field experiment revealed that varying levels of drought stress and seed size classes significantly affected parameters such as emergence time, growth traits, biomass allocation, tiller count, plant height, and grain and biomass outcomes. Bold seeds contributed to higher biomass and grain yield, while severe drought decreased yields. Notably, the Harvest Index was affected, indicating bold seeds allocate more biomass to grains. In conclusion, proper seed size selection, favouring bold seeds, can enhance resilience to drought, benefiting wheat cultivation in water-scarce regions.

Assessment of farmers’ resilience to drought and its influencing components: the case of Fars Province, Iran

ABSTRACT Drought is a complex socio-natural hazard that increases in magnitude with climate changes. Fars province, in the south of Iran, as one of the agricultural poles of Iran, has experienced severe droughts in recent years. Therefore, the present descriptive-correlational research was conducted aiming at assessing farmers’ resilience to drought within the province. Using a structured questionnaire, 420 farmers were surveyed following a multi-stage cluster random sampling method. Results of the research demonstrate that the farmers’ social resilience levels to drought are slightly higher than the average. Furthermore, three independent variables including adaptive capacity, job satisfaction, and learning capacity have the highest positive and significant correlations with social resilience. In addition, the results of multiple regression analysis showed that seven variables including adaptive capacity, perceived social support, learning capacity, social capital, coping capacity, job satisfaction, and drought perception had positive and statistically significant effects on the farmers’ resilience to drought. When considered together, these seven predicting variables account for about 41% of the variance of the dependent variable. In general, the results of this research can be useful in better understanding the social aspects of agricultural societies and increasing planners’ awareness concerning farmers’ resilience to climatic and environmental challenges.

Evaluation of the spatial responses in vegetation phenology to drought and the analysis of their driving factors in China

The warming and drying trend accompanying climate change challenges global ecosystem stability. Vegetation phenology, which can serve as a sensitive indicator of climate change, is crucial in understanding ecosystem carbon cycling and climate-carbon cycle feedback. Therefore, assessing the phenological responses to drought is essential for addressing climate change. In this study, vegetation phenology data [including the start and end of season (SOS, EOS) and length of growing season (LOS)] and the Palmer drought severity index (PDSI) were employed to analyze the impacts of drought on plant phenology in China by maximum Pearson correlation coefficients and partial least squares regression. The findings showed that drought significantly affected the timing of phenology, delaying senescence in approximately 62% of China and extending the growing season in about 53% of the country, indicating the critical role of water availability in vegetation biomass. Preseason nocturnal warming was found to advance SOS, delay EOS, and extend LOS across China, with significant effects observed in approximately 60% of the country. Meanwhile, daytime warming delayed SOS, delayed EOS and extended LOS in 50∼60% of the regions. Moreover, preseason precipitation is conducive to advanced SOS, delayed EOS and extended LOS in northern China and areas susceptible to drought. It is suggested that vegetation management should be strengthened to mitigate the impact of climate change in temperate and drought-prone regions in China since climate warming will lead to frequent droughts.

Google Earth Engine application for mapping and monitoring drought patterns and trends: A case study in Arkansas, USA

Drought is a prolonged dry period that can have severe impacts on the environment, human health, economies, agriculture, and energy resources. It can lead to water shortages, ruin crops, dry out forests, and reduce the availability of food and water for wildlife and livestock. The primary objectives of this study are to: 1) quantify the variability and distributions of drought patterns in Arkansas, United States (US), 2) use remotely sensed indices to investigate the correlation between drought and vegetation cover in the area, and 3) develop a cloud-based framework (user-friendly app) to facilitate the assessment of drought impact in Arkansas over the past decades. A correlation analysis was also performed between the Vegetation Health Index (VHI) and meteorological indices to better understand the impact of meteorological drought on vegetation stress. In addition, Mann-Kendall trend analysis was used to assess trends in meteorological drought indices. The results indicate that drought is most prevalent during March and August months. The results of this study revealed that approximately 31% of the study area fell under the four drought classes (i.e., 1% Extreme drought, 4% Severe drought, 9% moderate drought, and 19% mild drought), with spring and the growing season experiencing moderate drought, particularly in agricultural areas, most notably within the Mississippi Alluvial Valley Plain at both state and county levels. In August, approximately 31% of the study area fell under the Four drought classes (i.e., 1% Extreme drought, 4% Severe drought, 9% moderate drought, and 19% mild drought), with spring and the growing season experiencing moderate drought, particularly in agricultural areas, most notably within the Mississippi Alluvial Valley Plain at both state and county levels. This study provides an essential foundation for policymakers, environmental scientists, and agricultural stakeholders aiming to mitigate drought impacts and safeguard against future climate uncertainties.

Pollarding May Relieve Drought Stress in Black Poplars

Pollarding has historically been used in broadleaf tree species across European woodlands. However, despite pollarding enhances vigor growth in the short term, it is still unclear how long this effect lasts and whether it can alleviate drought stress in seasonally dry regions. We compared the radial growth and wood δ13C (13C/12C), a proxy of intrinsic water-use efficiency (iWUE), of trees pollarded 10 and 20 years ago in two black poplar (Populus nigra L.) riparian stands located in North Eastern Spain and subjected to different ecohydrological conditions. We also assessed if pollarded trees showed different leaf phenology as compared with uncut trees of coexisting white poplar (Populus alba L.) trees. The relationships between growth, climate variables, drought severity and river flow were quantified. Pollarded and uncut trees showed a similar leaf phenology with a trend towards earlier leaf unfolding as springs become warmer. Pollarding increased growth rates by 54% (ratio between trees pollarded 10 and 20 years ago, respectively), but this enhancement was transitory and lasted ca. 10 years, whereas wood δ13C decreased −5%. The growth of black poplar increased in response to high precipitation in the previous winter, cool wet conditions, and a higher river flow in summer. Pollarding improves growth and relieves drought stress.