Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

Overexpression of Potato PYL16 Gene in Tobacco Enhances the Transgenic Plant Tolerance to Drought Stress

PYR/PYL/RCAR proteins are abscisic acid (ABA) receptors that play a crucial role in plant responses to abiotic stresses. However, there have been no research reports on potato PYL so far. In this study, a potato PYL gene named StPYL16 was identified based on transcriptome data under drought stress. Molecular characteristics analysis revealed that the StPYL16 protein possesses an extremely conserved PYL family domain. The tissue expression results indicated that the StPYL16 is predominantly expressed at high levels in the underground parts, particularly in tubers. Abiotic stress response showed that StPYL16 has a significant response to drought treatment. Further research on the promoter showed that drought stress could enhance the activation activity of the StPYL16 promoter on the reporter gene. Then, transient and stable expression of StPYL16 in tobacco enhanced the drought resistance of transgenic plants, resulting in improved plant height, stem thickness, and root development. In addition, compared with wild-type plants, StPYL16 transgenic tobacco exhibited lower malondialdehyde (MDA) content, higher proline accumulation, and stronger superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities. Meanwhile, StPYL16 also up-regulated the expression levels of stress-related genes (NtSOD, NtCAT, NtPOD, NtRD29A, NtLEA5, and NtP5CS) in transgenic plants under drought treatment. These findings indicated that the StPYL16 gene plays a positive regulatory role in potato responses to drought stress.

Characterization and Identification of Drought-Responsive ABA-Aldehyde Oxidase (AAO) Genes in Potato (Solanum tuberosum L.)

Abscisic acid (ABA) is an important stress hormone that affects plants' tolerance to stress. Changes in the content of abscisic can have an impact on plant responses to abiotic stress. The abscisic acid aldehyde oxidase (AAO) plays a crucial role in the final step in the synthesis of abscisic acid; therefore, understanding the function of the AAO gene family is of great significance for insight into plants' response to abiotic stresses. In this study, Solanum tuberosum AAO (StAAO) members were exhaustively explored using genome databases, and nine StAAOs were identified. Chromosomal location analysis indicated that StAAO genes mapped to 4 of the 14 potato chromosomes. Further analyses of gene structure and motif composition showed that members of the specific StAAO subfamily showed relatively conserved characteristics. Phylogenetic relationship analysis indicated that StAAOs proteins were divided into three major clades. Promoter analysis showed that most StAAO promoters contained cis-elements related to abiotic stress response and plant hormones. The results of tissue-specific expression analysis indicated that StAAO4 was predominantly expressed in the roots. Analysis of transcriptome data revealed that StAAO2/4/6 genes responded significantly to drought treatments. Moreover, further qRT-PCR analysis results indicated that StAAO2/4/6 not only significantly responded to drought stress but also to various phytohormone (ABA, SA, and MeJA) and abiotic stresses (salt and low temperature), albeit with different expression patterns. In summary, our study provides comprehensive insights into the sequence characteristics, structural properties, evolutionary relationships, and expression patterns of the StAAO gene family. These findings lay the foundation for a deeper understanding of the StAAO gene family and offer a potential genetic resource for breeding drought-resistant potato varieties.

Integrated Modeling of Agronomic and Water Resources Management Scenarios in a Degraded Coastal Watershed (Almyros Basin, Magnesia, Greece)

The scope of this study is to assess the effects of agronomic and water resources management scenarios on groundwater balance, seawater intrusion, and nitrate pollution and the comparison of the developed scenarios relative to the current crop production and water management regime in the coastal agricultural Almyros basin in the Thessaly region, Greece. Agronomic and water resources scenarios have been simulated and analyzed for a period of 28 years, from 1991 to 2018. The analysis has been conducted with the use of an Integrated Modeling System for agricultural coastal watersheds, which consists of coupled and interlinked simulation models of surface water hydrology (UTHBAL), reservoir operation (UTHRL), agronomic/nitrate leaching model (REPIC), and groundwater models for the simulation of groundwater flow (MODFLOW) and contaminant transport of nitrates (MT3DMS) and chlorides (SEAWAT). The pressure on water resources has been estimated with the Water Exploitation Index (WEI+) and the reservoirs’ operation with the Reliability index to cover the water demands. The indices of Crop Water Productivity, Nitrogen Use Efficiency, and Economic Water Productivity have been used to quantify the benefits and the feasibility of the alternative scenarios. The best results for the sustainability of water resources are achieved under the deficit irrigation and rain-fed scenario, while the best results for water resources and the local economy are achieved under deficit irrigation and reduced fertilization scenario.

Estimating resilience of crop production systems: From theory to practice

Agricultural production systems are sensitive to weather and climate anomalies and extremes as well as to other environmental and socio-economic adverse events. An adequate evaluation of the resilience of such systems helps to assess food security and the capacity of society to cope with the effects of global warming and the associated increase of climate extremes. Here, we propose and apply a simple indicator of resilience of annual crop production that can be estimated from crop production time series. First, we address the problem of quantifying resilience in a simplified theoretical framework, focusing on annual crops. This results in the proposal of an indicator, measured by the reciprocal of the squared coefficient of variance, which is proportional to the return period of the largest shocks that the crop production system can absorb, and which is consistent with the original ecological definition of resilience. Subsequently, we show the sensitivity of the crop resilience indicator to the level of management of the crop production system, to the frequency of extreme events as well as to simplified socio-economic impacts of the production losses. Finally, we demonstrate the practical applicability of the indicator using historical production data at national and sub-national levels for France. The results show that the value of the resilience indicator steeply increases with crop diversity until six crops are considered, and then levels off. The effect of diversity on production resilience is highest when crops are more diverse (i.e. as reflected in less well correlated production time series). In the case of France, the indicator reaches about 60% of the value that would be expected if all crop production time-series were uncorrelated.

Projection of meteorological droughts in Nigeria during growing seasons under climate change scenarios

Like many other African countries, incidence of drought is increasing in Nigeria. In this work, spatiotemporal changes in droughts under different representative concentration pathway (RCP) scenarios were assessed; considering their greatest impacts on life and livelihoods in Nigeria, especially when droughts coincide with the growing seasons. Three entropy-based methods, namely symmetrical uncertainty, gain ratio, and entropy gain were used in a multi-criteria decision-making framework to select the best performing General Circulation Models (GCMs) for the projection of rainfall and temperature. Performance of four widely used bias correction methods was compared to identify a suitable method for correcting bias in GCM projections for the period 2010–2099. A machine learning technique was then used to generate a multi-model ensemble (MME) of the bias-corrected GCM projection for different RCP scenarios. The standardized precipitation evapotranspiration index (SPEI) was subsequently computed to estimate droughts from the MME mean of GCM projected rainfall and temperature to predict possible spatiotemporal changes in meteorological droughts. Finally, trends in the SPEI, temperature and rainfall, and return period of droughts for different growing seasons were estimated using a 50-year moving window, with a 10-year interval, to understand driving factors accountable for future changes in droughts. The analysis revealed that MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0, and CESM1-CAM5 are the most appropriate GCMs for projecting rainfall and temperature, and the linear scaling (SCL) is the best method for correcting bias. The MME mean of bias-corrected GCM projections revealed an increase in rainfall in the south-south, southwest, and parts of the northwest whilst a decrease in the southeast, northeast, and parts of central Nigeria. In contrast, rise in temperature for entire country during most of the cropping seasons was projected. The results further indicated that increase in temperature would decrease the SPEI across Nigeria, which will make droughts more frequent in most of the country under all the RCPs. However, increase in drought frequency would be less for higher RCPs due to increase in rainfall.

Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China

As the second largest inland river basin situated in the middle of the Hexi Corridor, Northwest China, the Heihe River basin (HRB) has been facing a severe water shortage problem, which seriously restricts its green and sustainable development. The evaluation of climate change impact on water productivity inferred by crop yield and actual evapotranspiration is of significant importance for water-saving in agricultural regions. In this study, the multi-model projections of climate change under the three Representative Concentration Pathways emission scenarios (RCP2.6, RCP4.5, RCP8.5) were used to drive an agro-hydrological model to evaluate the crop water productivity in the middle irrigated oases of the HRB from 2021–2050. Compared with the water productivity simulation based on field experiments during 2012–2015, the projected water productivity in the two typical agricultural areas (Gaotai and Ganzhou) both exhibited an increasing trend in the future 30 years, which was mainly attributed to the significant decrease of the crop water consumption. The water productivity in the Gaotai area under the three RCP scenarios during 2021–2050 increased by 9.2%, 14.3%, and 11.8%, while the water productivity increased by 15.4%, 21.6%, and 19.9% in the Ganzhou area, respectively. The findings can provide useful information on the Hexi Corridor and the Belt and Road to policy-makers and stakeholders for sustainable development of the water-ecosystem-economy system.

Sustainable Groundwater Exploitation Aiming at the Reduction of Water Vulnerability in the Brazilian Semi-Arid Region

Semi-arid regions have historically suffered from low water availability. In addition, the increasing frequency and intensity of extreme weather events credited to global climate change has made it increasingly clear that among the challenges faced by society water resource management is extremely necessary. In this context, desalination based on renewable energy resources integrated with production systems that make use of the waste resulting from this process becomes a socio-environmentally indicated alternative to expand existing supply strategies and sustainable water use in isolated locations, and/or areas distant from large urban centers, thus addressing local potential and reducing environmental impacts. This study assesses the use of Photovoltaic Solar Power Plants (PSPPs), as well as of residues generated in a Brackish Water Reverse Osmosis System (BWRO), in productive units linked to fish and family farming. This is as an alternative way to reduce water vulnerability in the Brazilian semi-arid area (BS), adhering to climate change adaptation measures in the light of Brazilian public policies through the Freshwater Program (Programa Água Doce—PAD), which aims to promote access to good quality water to approximately 500 thousand people in the Brazilian semi-arid region.

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims. We considered three locations in New South Wales, Australia, six times of sowing (TOS) and three bread wheat (Triticum aestivum L.) cultivars in this study. Simulation results show that in 2030 (1) for impact analysis, wheat phenological events are expected to occur earlier and crop water use is expected to decrease across all cases (the combination of three locations, six TOS and three cultivars), wheat grain yield would increase or decrease depending on locations and TOS; and WUE would increase in most of the cases; (2) for adaptation considerations, the combination of TOS and cultivars with the highest yield varied across locations. Wheat growers at different locations will require different strategies in managing the negative impacts or taking the opportunities of future CC.