Aridity threshold for alpine soil nitrogen isotope signature and ecosystem nitrogen cycling.

Determination of tipping points in nitrogen (N) isotope (δ15N) natural abundance, especially soil δ15N, with increasing aridity, is critical for estimating N-cycling dynamics and N limitation in terrestrial ecosystems. However, whether there are linear or nonlinear responses of soil δ15N to increases in aridity and if these responses correspond well with soil N cycling remains largely unknown. In this study, we investigated soil δ15N and soil N-cycling characteristics in both topsoil and subsoil layers along a drought gradient across a 3000-km transect of drylands on the Qinghai-Tibetan Plateau. We found that the effect of increasing aridity on soil δ15N values shifted from negative to positive with thresholds at aridity index (AI) = 0.27 and 0.29 for the topsoil and subsoil, respectively, although soil N pools and N transformation rates linearly decreased with increasing aridity in both soil layers. Furthermore, we identified markedly different correlations between soil δ15N and soil N-cycling traits above and below the AI thresholds (0.27 and 0.29 for topsoil and subsoil, respectively). Specifically, in wetter regions, soil δ15N positively correlated with most soil N-cycling traits, suggesting that high soil δ15N may result from the "openness" of soil N cycling. Conversely, in drier regions, soil δ15N showed insignificant relationships with soil N-cycling traits and correlated well with factors, such as soil-available phosphorus and foliage δ15N, demonstrating that pathways other than typical soil N cycling may dominate soil δ15N under drier conditions. Overall, these results highlight that different ecosystem N-cycling processes may drive soil δ15N along the aridity gradient, broadening our understanding of N cycling as indicated by soil δ15N under changing drought regimes. The aridity threshold of soil δ15N should be considered in terrestrial N-cycling models when incorporating 15N isotope signals to predict N cycling and availability under climatic dryness.

Association of the electrical parameters and photosynthetic characteristics of the tea tree manifests its response to simulated karst drought.

Tea plantations in Karst regions suffer from the serious effects of frequent temporary karst droughts, leading to a decline in tea production and quality in the region. The close relationship between growth and electrical parameters of plants, including physiological capacitance, resistance and impedance, can be used to accurately monitor their plant water status online, quickly, accurately, timely and nondestructively. In this study, three tea tree cultivars of Zhonghuang No.2 (ZH), Wuniuzao (WNZ), and Longjing 43 (LJ) with different levels of drought resistance were selected as experimental materials, and experiments were carried out under controlled conditions according to control (soil water content of 40-45%, D0), (keeping D0 no watering to 5 days, D5), (keeping D0 no watering to 10 days, D10), (the first day after D10 is rehydrated to D0 is regarded as R1) and (the fifth day after D10 rehydration to D0 is regarded as R5), to determine intracellular water metabolism and nutrient translocation characteristics based on intrinsic electrical parameters. The photosynthetic characteristics and chlorophyll fluorescence parameters were also determined to investigate the response of water metabolism to simulated karst drought in the three tea tree cultivars. The results indicated that the water metabolism patterns responded to environmental water changes with a medium water-holding capacity, medium water transport rate, and low water-use efficiency, and the nutrient patterns in those tea tree varieties demonstrated with a high nutrient flux per unit area, low nutrient transfer rate, and high nutrient transport capacity. After rehydration, only the electrical characteristics of WNZ returned to the D0 levels, but the net photosynthetic rate of all varieties returned to or even exceeded the D0 levels. The chlorophyll fluorescence parameters could not be used to characterize the recoverability of metabolism in tea trees. The electrical characteristics quickly reflected the response of the water metabolism in plants to environmental changes, and the fusion of electrical characteristics and photosynthetic characteristics was able to more quickly, accurately, and comprehensively reflect the response of water metabolism to temporary karst drought.

Screening and functional verification of drought resistance-related genes in castor bean seeds.

Drought is one of the natural stresses that greatly impact plants. Castor bean (Ricinus communis L.) is an oil crop with high economic value. Drought is one of the factors limiting castor bean growth. The drought resistance mechanisms of castor bean have become a research focus. In this study, we used castor germinating embryos as experimental materials, and screened genes related to drought resistance through physiological measurements, proteomics and metabolomics joint analysis; castor drought-related genes were subjected to transient silencing expression analysis in castor leaves to validate their drought-resistant functions, and heterologous overexpression and backward complementary expression in Arabidopsis thaliana, and analysed the mechanism of the genes' response to the participation of Arabidopsis thaliana in drought-resistance.Three drought tolerance-related genes, RcECP 63, RcDDX 31 and RcA/HD1, were obtained by screening and analysis, and transient silencing of expression in castor leaves further verified that these three genes corresponded to drought stress, and heterologous overexpression and back-complementary expression of the three genes in Arabidopsis thaliana revealed that the function of these three genes in drought stress response.In this study, three drought tolerance related genes, RcECP 63, RcDDX 31 and RcA/HD1, were screened and analysed for gene function, which were found to be responsive to drought stress and to function in drought stress, laying the foundation for the study of drought tolerance mechanism in castor bean.

Biochemical characterization and metabolic reprogramming of amino acids in Soybean roots under drought stress.

Amino acids play important roles in stress resistance, plant growth, development, and quality, with roots serving as the primary organs for drought response. We conducted biochemical and multi-omics analyses to investigate the metabolic processes of root amino acids in drought-resistant (HN44) and drought-sensitive (HN65) soybean (Glycine max) varieties. Our analysis revealed an increase in total amino acid content in both varieties, with phenylalanine, proline, and methionine accumulating in both. Additionally, several amino acids exhibited significant decreases in HN65 but slight increases in HN44. Multi-omics association analysis identified 13 amino acid-related pathways. We thoroughly examined the changes in genes and metabolites involved in various amino acid metabolism/synthesis and determined core genes and metabolites through correlation networks. The phenylalanine, tyrosine, and tryptophan metabolic pathways and proline, glutamic acid and sulfur-containing amino acid pathways were particularly important for drought resistance. Some candidate genes, such as ProDH and P4HA family genes, and metabolites, such as O-acetyl-L-serine, directly affected up- and downstream metabolism to induce drought resistance. This study provided a basis for soybean drought resistance breeding.

Inferred drought-induced plant allocation shifts and their impact on drought legacy at a tropical forest site.

While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long-lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought-induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model-data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5 months. The inferred allocation shifts influenced the post-drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust-boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought-free conditions. Overall, allocation shifts accounted for 65% [45%-75%] of drought legacy effects in modeled NBE. In summary, drought-induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land-atmosphere CO2 exchanges and should be accounted for in ecosystem models.

Alpha lipoic acid mitigates adverse impacts of drought stress on growth and yield of mungbean: photosynthetic pigments, and antioxidative defense mechanism.

Context: Exogenous use of potential organic compounds through different modes is a promising strategy for the induction of water stress tolerance in crop plants for better yield. Aims: The present study aimed to explore the potential role of alpha-lipoic acid (ALA) in inducing water stress tolerance in mungbean lines when applied exogenously through various modes. Methods: The experiment was conducted in a field with a split-plot arrangement, having three replicates for each treatment. Two irrigation regimes, including normal and reduced irrigation, were applied. The plants allocated to reduced irrigation were watered only at the reproductive stage. Three levels of ALA (0, 0.1, 0.15 mM) were applied through different modes (seed priming, foliar or priming+foliar). Key results: ALA treatment through different modes manifested higher growth under reduced irrigation (water stress) and normal irrigation. Compared to the other two modes, the application of ALA as seed priming was found more effective in ameliorating the adverse impacts of water stress on growth and yield associated with their better content of leaf photosynthetic pigments, maintenance of plant water relations, levels of non-enzymatic antioxidants, improved activities of enzymatic antioxidants, and decreased lipid peroxidation and H2O2 levels. The maximum increase in shoot fresh weight (29% and 28%), shoot dry weight (27% and 24%), 100-grain weight (24% and 23%) and total grain yield (20% and 21%) in water-stressed mungbean plants of line 16003 and 16004, respectively, was recorded due to ALA seed priming than other modes of applications. Conclusions: Conclusively, 0.1 and 0.15 mM levels of ALA as seed priming were found to reduce the adverse impact of water stress on mungbean yield that was associated with improved physio-biochemical mechanisms. Implications: The findings of the study will be helpful for the agriculturalists working in arid and semi-arid regions to obtain a better yield of mungbean that will be helpful to fulfill the food demand in those areas to some extent.

Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand.

Grasslands provide important ecosystem services to society, including biodiversity, water security, erosion control, and forage production. Grasslands are also vulnerable to droughts, rendering their future vitality under climate change uncertain. Yet, the grassland response to drought is not well understood, especially for heterogeneous Central European grasslands. We here fill this gap by quantifying the spatiotemporal sensitivity of grasslands to drought using a novel remote sensing dataset from Landsat/Sentinel-2 paired with climate re-analysis data. Specifically, we quantified annual grassland vitality at fine spatial scale and national extent (Germany) from 1985 to 2021. We analyzed grassland sensitivity to drought by testing for statistically robust links between grassland vitality and common drought indices. We furthermore explored the spatiotemporal variability of drought sensitivity for 12 grassland habitat types given their different biotic and abiotic features. Grassland vitality maps revealed a large-scale reduction of grassland vitality during past droughts. The unprecedented drought of 2018-2019 stood out as the largest multi-year vitality decline since the mid-1980s. Grassland vitality was consistently coupled to drought (R2 = .09-.22) with Vapor Pressure Deficit explaining vitality best. This suggests that high atmospheric water demand, as observed during recent compounding drought and heatwave events, has major impacts on grassland vitality in Central Europe. We found a significant increase in drought sensitivity over time with highest sensitivities detected in periods of extremely high atmospheric water demand, suggesting that drought impacts on grasslands are becoming more severe with ongoing climate change. The spatial variability of grassland drought sensitivity was linked to different habitat types, with declining sensitivity from dry and mesic to wet habitats. Our study provides the first large-scale, long-term, and spatially explicit evidence of increasing drought sensitivities of Central European grasslands. With rising compound droughts and heatwaves under climate change, large-scale grassland vitality loss, as in 2018-2019, will thus become more likely in the future.

Plasticity and implications of water-use traits in contrasting tropical tree species under climate change.

Plants face a trade-off between hydraulic safety and growth, leading to a range of water-use strategies in different species. However, little is known about such strategies in tropical trees and whether different water-use traits can acclimate to warming. We studied five water-use traits in 20 tropical tree species grown at three different altitudes in Rwanda (RwandaTREE): stomatal conductance (gs), leaf minimum conductance (gmin), plant hydraulic conductance (Kplant), leaf osmotic potential (ψo) and net defoliation during drought. We also explored the links between these traits and growth and mortality data. Late successional (LS) species had low Kplant, gs and gmin and, thus, low water loss, while low ψo helped improve leaf water status during drought. Early successional (ES) species, on the contrary, used more water during both moist and dry conditions and exhibited pronounced drought defoliation. The ES strategy was associated with lower mortality and more pronounced growth enhancement at the warmer sites compared to LS species. While Kplant and gmin showed downward acclimation in warmer climates, ψo did not acclimate and gs measured at prevailing temperature did not change. Due to distinctly different water use strategies between successional groups, ES species may be better equipped for a warmer climate as long as defoliation can bridge drought periods.

An evaluative technique for drought impact on variation in agricultural LULC using remote sensing and machine learning.

Drought events threaten freshwater reservoirs and agricultural productivity, particularly in semi-arid regions characterized by erratic rainfall. This study evaluates a novel technique for assessing the impact of drought on LULC variations in the context of climate change from 2018 to 2022. Various data sources were harnessed, encompassing Sentinel-2 satellite imagery for LULC classification, climate data from the CHIRPS and AgERA5 databases, geomorphological data from JAXA's ALOS satellite, and a drought indicator (Vegetation Health Index (VHI)) derived from MODIS data. Two classifier models, namely gradient tree boost (GTB) and random forest (RF), were trained and assessed for LULC classification, with performance evaluated by overall accuracy (OA) and kappa coefficient (K). Notably, the GTB model exhibited superior performance, with OA > 90% and a K > 0.9. Over the period from 2018 to 2022, Fez experienced LULC changes of 19.92% expansion in built-up areas, a 34.86% increase in bare land, a 17.86% reduction in water bodies, and a 37.30% decrease in agricultural land. Positive correlations of 0.81 and 0.89 were observed between changes in agricultural LULC, rainfall, and VHI. Furthermore, mild drought conditions were identified in the years 2020 and 2022. This study emphasizes the importance of AI and remote sensing techniques in assessing drought and environmental changes, with potential applications for improving existing drought monitoring systems.

Effects of experimental drought and plant diversity on multifunctionality of a model system for crop rotation.

In low-diversity productive grasslands, modest changes to plant diversity (richness, composition and relative abundance) may affect multiple ecosystem functions (multifunctionality), including yield. Despite the economic importance of productive grasslands, effects of plant diversity and environmental disturbance on multifunctionality are very rarely quantified. We systematically varied species richness, composition, and relative abundance of grassland ley communities and manipulated water supply (rainfed and drought) to quantify effects of diversity and environmental disturbance on multifunctionality. We then replaced the grassland leys with a monoculture crop to investigate 'follow-on' effects. We measured six agronomy-related ecosystem functions across one or both phases: yield, yield consistency, digestibility and weed suppression (grassland ley phase), legacy effect (effect on follow-on crop yield), and nitrogen fertiliser efficiency (full rotation). Drought reduced most ecosystem functions, although effects were species- and function-specific. Increased plant diversity affected mean performance, and reduced variation, across the six functions (contributing to multifunctional stability). Multifunctionality index values across a wide range of mixture diversity were higher than the best monoculture under both rainfed and drought conditions (transgressive over-performance). Higher-diversity, lower-nitrogen (150N) mixtures had higher multifunctionality than a low-diversity, higher-nitrogen (300N) grass monoculture. Plant diversity in productive grasslands is a practical farm-scale management action to mitigate drought impacts and enhance multifunctionality of grassland-crop rotation systems.

Characterizing stay-green in barley across diverse environments: unveiling novel haplotypes.

KEY MESSAGE: There is variation in stay-green within barley breeding germplasm, influenced by multiple haplotypes and environmental conditions. The positive genetic correlation between stay-green and yield across multiple environments highlights the potential as a future breeding target. Barley is considered one of the most naturally resilient crops making it an excellent candidate to dissect the genetics of drought adaptive component traits. Stay-green, is thought to contribute to drought adaptation, in which the photosynthetic machinery is maintained for a longer period post-anthesis increasing the photosynthetic duration of the plant. In other cereal crops, including wheat, stay-green has been linked to increased yield under water-limited conditions. Utilizing a panel of diverse barley breeding lines from a commercial breeding program we aimed to characterize stay-green in four environments across two years. Spatiotemporal modeling was used to accurately model senescence patterns from flowering to maturity characterizing the variation for stay-green in barley for the first time. Environmental effects were identified, and multi-environment trait analysis was performed for stay-green characteristics during grain filling. A consistently positive genetic correlation was found between yield and stay-green. Twenty-two chromosomal regions with large effect haplotypes were identified across and within environment types, with ten being identified in multiple environments. In silico stacking of multiple desirable haplotypes showed an opportunity to improve the stay-green phenotype through targeted breeding. This study is the first of its kind to model barley stay-green in a large breeding panel and has detected novel, stable and environment specific haplotypes. This provides a platform for breeders to develop Australian barley with custom senescence profiles for improved drought adaptation.

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages.

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the lag and limitations inherent in traditional drought monitoring methods, this paper proposes a multimodal deep learning-based drought stress monitoring S-DNet model for winter wheat during its critical growth periods. Drought stress images of winter wheat during the Rise-Jointing, Heading-Flowering and Flowering-Maturity stages were acquired to establish a dataset corresponding to soil moisture monitoring data. The DenseNet-121 model was selected as the base network to extract drought features. Combining the drought phenotypic characteristics of wheat in the field with meteorological factors and IoT technology, the study integrated the meteorological drought index SPEI, based on WSN sensors, and deep image learning data to build a multimodal deep learning-based S-DNet model for monitoring drought stress in winter wheat. The results show that, compared to the single-modal DenseNet-121 model, the multimodal S-DNet model has higher robustness and generalization capability, with an average drought recognition accuracy reaching 96.4%. This effectively achieves non-destructive, accurate, and rapid monitoring of drought stress in winter wheat.

Water for agriculture: more crop per drop.

Global crop production in agriculture depends on water availability. Future scenarios predict increasing occurrence of flash floods and rapidly developing droughts accompanied by heatwaves in humid regions that rely on rain-fed agriculture. It is challenging to maintain high crop yields, even in arid and drought-prone regions that depend on irrigation. The average water demand of crops varies significantly, depending on plant species, development stage, and climate. Most crops, such as maize and wheat, require relatively more water during the vegetative phase compared to the ripening phase. In this review, we explain WUE and options to improve water use and thus crop yield. Nutrient management might represent another possibility to manipulate water uptake and use by plants. An emerging topic involves agroforest co-cultivation, where trees in the system facilitate water transfer through hydraulic lift, benefiting neighbouring crops. Other options to enhance crop yield per water use are discussed.

Genome-wide identification and expression analysis of the SET domain-containing gene family in potato (Solanum tuberosum L.).

Genes containing the SET domain can catalyse histone lysine methylation, which in turn has the potential to cause changes to chromatin structure and regulation of the transcription of genes involved in diverse physiological and developmental processes. However, the functions of SET domain-containing (StSET) genes in potato still need to be studied. The objectives of our study can be summarized as in silico analysis to (i) identify StSET genes in the potato genome, (ii) systematically analyse gene structure, chromosomal distribution, gene duplication events, promoter sequences, and protein domains, (iii) perform phylogenetic analyses, (iv) compare the SET domain-containing genes of potato with other plant species with respect to protein domains and orthologous relationships, (v) analyse tissue-specific expression, and (vi) study the expression of StSET genes in response to drought and heat stresses. In this study, we identified 57 StSET genes in the potato genome, and the genes were physically mapped onto eleven chromosomes. The phylogenetic analysis grouped these StSET genes into six clades. We found that tandem duplication through sub-functionalisation has contributed only marginally to the expansion of the StSET gene family. The protein domain TDBD (PFAM ID: PF16135) was detected in StSET genes of potato while it was absent in all other previously studied species. This study described three pollen-specific StSET genes in the potato genome. Expression analysis of four StSET genes under heat and drought in three potato clones revealed that these genes might have non-overlapping roles under different abiotic stress conditions and durations. The present study provides a comprehensive analysis of StSET genes in potatoes, and it serves as a basis for further functional characterisation of StSET genes towards understanding their underpinning biological mechanisms in conferring stress tolerance.

Analysis of drought and heat stress response genes in rice using co-expression network and differentially expressed gene analyses.

Studies on Oryza sativa (rice) are crucial for improving agricultural productivity and ensuring global sustenance security, especially considering the increasing drought and heat stress caused by extreme climate change. Currently, the genes and mechanisms underlying drought and heat resistance in rice are not fully understood, and the scope for enhancing the development of new strains remains considerable. To accurately identify the key genes related to drought and heat stress responses in rice, multiple datasets from the Gene Expression Omnibus (GEO) database were integrated in this study. A co-expression network was constructed using a Weighted Correlation Network Analysis (WGCNA) algorithm. We further distinguished the core network and intersected it with differentially expressed genes and multiple expression datasets for screening. Differences in gene expression levels were verified using quantitative real-time polymerase chain reaction (PCR). OsDjC53, MBF1C, BAG6, HSP23.2, and HSP21.9 were found to be associated with the heat stress response, and it is also possible that UGT83A1 and OsCPn60a1, although not directly related, are affected by drought stress. This study offers significant insights into the molecular mechanisms underlying stress responses in rice, which could promote the development of stress-tolerant rice breeds.

Improvement of morphophysiological and anatomical attributes of plants under abiotic stress conditions using plant growth-promoting bacteria and safety treatments.

Drought and salinity are the major abiotic stress factors negatively affecting the morphophysiological, biochemical, and anatomical characteristics of numerous plant species worldwide. The detrimental effects of these environmental factors can be seen in leaf and stem anatomical structures including the decrease in thickness of cell walls, palisade and spongy tissue, phloem and xylem tissue. Also, the disintegration of grana staking, and an increase in the size of mitochondria were observed under salinity and drought conditions. Drought and salt stresses can significantly decrease plant height, number of leaves and branches, leaf area, fresh and dry weight, or plant relative water content (RWC%) and concentration of photosynthetic pigments. On the other hand, stress-induced lipid peroxidation and malondialdehyde (MDA) production, electrolyte leakage (EL%), and production of reactive oxygen species (ROS) can increase under salinity and drought conditions. Antioxidant defense systems such as catalase, peroxidase, glutathione reductase, ascorbic acid, and gamma-aminobutyric acid are essential components under drought and salt stresses to protect the plant organelles from oxidative damage caused by ROS. The application of safe and eco-friendly treatments is a very important strategy to overcome the adverse effects of drought and salinity on the growth characteristics and yield of plants. It is shown that treatments with plant growth-promoting bacteria (PGPB) can improve morphoanatomical characteristics under salinity and drought stress. It is also shown that yeast extract, mannitol, proline, melatonin, silicon, chitosan, α-Tocopherols (vitamin E), and biochar alleviate the negative effects of drought and salinity stresses through the ROS scavenging resulting in the improvement of plant attributes and yield of the stressed plants. This review discusses the role of safety and eco-friendly treatments in alleviating the harmful effects of salinity and drought associated with the improvement of the anatomical, morphophysiological, and biochemical features in plants.

Drought shortens subtropical understory growing season by advancing leaf senescence.

Subtropical forests, recognized for their intricate vertical canopy stratification, exhibit high resistance to extreme drought. However, the response of leaf phenology to drought in the species-rich understory remains poorly understood. In this study, we constructed a digital camera system, amassing over 360,000 images through a 70% throughfall exclusion experiment, to explore the drought response of understory leaf phenology. The results revealed a significant advancement in understory leaf senescence phenology under drought, with 11.75 and 15.76 days for the start and end of the leaf-falling event, respectively. Pre-season temperature primarily regulated leaf development phenology, whereas soil water dominated the variability in leaf senescence phenology. Under drought conditions, temperature sensitivities for the end of leaf emergence decreased from -13.72 to -11.06 days °C-1, with insignificance observed for the start of leaf emergence. Consequently, drought treatment shortened both the length of the growing season (15.69 days) and the peak growth season (9.80 days) for understory plants. Moreover, this study identified diverse responses among intraspecies and interspecies to drought, particularly during the leaf development phase. These findings underscore the pivotal role of water availability in shaping understory phenology patterns, especially in subtropical forests.

Interactive effects of drought and deforestation on multitrophic communities and aquatic ecosystem functions in the Neotropics-a test using tank bromeliads.

Background: Together with the intensification of dry seasons in Neotropical regions, increasing deforestation is expected to exacerbate species extinctions, something that could lead to dramatic shifts in multitrophic communities and ecosystem functions. Recent studies suggest that the effects of habitat loss are greater where precipitation has decreased. Yet, experimental studies of the pure and interactive effects of drought and deforestation at ecosystem level remain scarce. Methods: Here, we used rainshelters and transplantation from rainforest to open areas of natural microcosms (the aquatic ecosystem and microbial-faunal food web found within the rainwater-filled leaves of tank bromeliads) to emulate drought and deforestation in a full factorial experimental design. We analysed the pure and interactive effects of our treatments on functional community structure (including microorganisms, detritivore and predatory invertebrates), and on leaf litter decomposition in tank bromeliad ecosystems. Results: Drought or deforestation alone had a moderate impact on biomass at the various trophic level, but did not eliminate species. However, their interaction synergistically reduced the biomass of all invertebrate functional groups and bacteria. Predators were the most impacted trophic group as they were totally eliminated, while detritivore biomass was reduced by about 95%. Fungal biomass was either unaffected or boosted by our treatments. Decomposition was essentially driven by microbial activity, and did not change across treatments involving deforestation and/or drought. Conclusions: Our results suggest that highly resistant microorganisms such as fungi (plus a few detritivores) maintain key ecosystem functions in the face of drought and habitat change. We conclude that habitat destruction compounds the problems of climate change, that the impacts of the two phenomena on food webs are mutually reinforcing, and that the stability of ecosystem functions depends on the resistance of a core group of organisms. Assuming that taking global action is more challenging than taking local-regional actions, policy-makers should be encouraged to implement environmental action plans that will halt habitat destruction, to dampen any detrimental interactive effect with the impacts of global climate change.

Transcription factor ZmDof22 enhances drought tolerance by regulating stomatal movement and antioxidant enzymes activities in maize (Zea mays L.).

KEY MESSAGE: The Dof22 gene encoding a deoxyribonucleic acid binding with one finger in maize, which is associated with its drought tolerance. The identification of drought stress regulatory genes is essential for the genetic improvement of maize yield. Deoxyribonucleic acid binding with one finger (Dof), a plant-specific transcription factor family, is involved in signal transduction, morphogenesis, and environmental stress responses. In present study, by weighted correlation network analysis (WGCNA) and gene co-expression network analysis, 15 putative Dof genes were identified from maize that respond to drought and rewatering. A real-time fluorescence quantitative PCR showed that these 15 genes were strongly induced by drought and ABA treatment, and among them ZmDof22 was highly induced by drought and ABA treatment. Its expression level increased by nearly 200 times after drought stress and more than 50 times after ABA treatment. After the normal conditions were restored, the expression levels were nearly 100 times and 40 times of those before treatment, respectively. The Gal4-LexA/UAS system and transcriptional activation analysis indicate that ZmDof22 is a transcriptional activator regulating drought tolerance and recovery ability in maize. Further, overexpressed transgenic and mutant plants of ZmDof22 by CRISPR/Cas9, indicates that the ZmDof22, improves maize drought tolerance by promoting stomatal closure, reduces water loss, and enhances antioxidant enzyme activity by participating in the ABA pathways. Taken together, our findings laid a foundation for further functional studies of the ZmDof gene family and provided insights into the role of the ZmDof22 regulatory network in controlling drought tolerance and recovery ability of maize.

Unveiling the landscape predictors of resilient vegetation in coastal wetlands to inform conservation in the face of climate extremes.

Unveiling spatial variation in vegetation resilience to climate extremes can inform effective conservation planning under climate change. Although many conservation efforts are implemented on landscape scales, they often remain blind to landscape variation in vegetation resilience. We explored the distribution of drought-resilient vegetation (i.e., vegetation that could withstand and quickly recover from drought) and its predictors across a heterogeneous coastal landscape under long-term wetland conversion, through a series of high-resolution satellite image interpretations, spatial analyses, and nonlinear modelling. We found that vegetation varied greatly in drought resilience across the coastal wetland landscape and that drought-resilient vegetation could be predicted with distances to coastline and tidal channel. Specifically, drought-resilient vegetation exhibited a nearly bimodal distribution and had a seaward optimum at ~2 km from coastline (corresponding to an inundation frequency of ~30%), a pattern particularly pronounced in areas further away from tidal channels. Furthermore, we found that areas with drought-resilient vegetation were more likely to be eliminated by wetland conversion. Even in protected areas where wetland conversion was slowed, drought-resilient vegetation was increasingly lost to wetland conversion at its landward optimum in combination with rapid plant invasions at its seaward optimum. Our study highlights that the distribution of drought-resilient vegetation can be predicted using landscape features but without incorporating this predictive understanding, conservation efforts may risk failing in the face of climate extremes.