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Crops are increasingly affected by drought; hence, the current study explored the potential role of three desert endophytic fungi, Aspergillus fumigatus, Aspergillus terreus and Talaromyces variabilis, in conferring drought tolerance in tomato plants.

Preserved endophytic fungi from a Rhazya stricta desert plant were adopted to obtain the required fungal treatment; tomatoes received fungal treatments directly in plastic trays and subsequently in pots. Drought was applied using 15% of PEG-6000 at two stages: flowering and fruiting. The following parameters were measured: pollen sterility, growth characteristics, morphological analysis and biochemical analysis, including proline, gibberellic acid (GA3) and chlorophyll measurements; thus, the data were analyzed statistically using SPSS software.

All applied endophytes significantly promoted pollen viability and tomato yield under stressed and nonstressed conditions. Interestingly, these endophytes significantly enhanced the number of trichomes under drought stress and promoted tomato fruit quality. The colonized tomato plants accumulated a high proline level under drought stress but lower than un-inoculated stressed plants. Also, a significant rise in growth characteristics was observed by A. fumigatus and A. terreus under normal conditions. Moreover, both raised GA3 levels under drought-stressed and nonstressed conditions. Also these two endophytes enhanced chlorophyll and carotenoid contents under drought stress. Fruit characteristics were enhanced by nonstressed T. variabilis and stressed A. fumigatus.

The present endophytic fungi provide impressive benefits to their host in normal and drought-stressed conditions. Consequently, they represent valuable sources as sustainable and environmentally friendly alternatives to mitigate drought stress.

In Argentina, soy and maize represent 28% of the total country exports, affecting the balance of payments, international reserves accumulation and sovereign credit risk. In the past 10 years, three extreme and moderate droughts have affected the agricultural areas, causing significant losses in soybean and maize production. This study aims to estimate the economic impact generated by different drought levels for soy and maize production areas through a financial perspective that allows the estimation of the cash flow and income losses.

By analyzing the extreme deviations in yields during dry periods, the losses generated by droughts were valuated among 183 departments nationwide.

The aggregated results indicated a total loss of US$24.170m, representing 57.45% of the international reserves of the Argentinean Central Bank in 2021. This estimate shows the magnitude of the climate impact on the Argentinean economy, indicating that severe droughts have macroeconomic impacts, with the external sector as the main transmission channel in an economy with historic restrictions on the balance of payments, international reserve accumulation and sovereign credit risk.

This study analyses the macroeconomic impact of drought on Argentinean soybean and maize production.

The purpose of this paper is to establish a two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem with three-parameter interval grey number to evaluation of agricultural drought resistance grade of 18 cities in Henan Province.

The clustering process is divided into two stages. In the first stage: Combining variance and time degree, the time weight optimization model is established. Applying the prospect theory, the index weight optimization model is established. Then, with the help of grey possibility function, the first stage of grey cloud clustering evaluation is carried out. In the second stage: the weight vector group of kernel clustering is constructed, and the grey class of the object is determined. A two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem is proposed.

This paper indicates that 18 cities in Henan Province are divided into four categories. The drought capacity in Henan province is high in the east and low in the west, high in the south and low in the north and the central region is relatively stable. The drought is greatly affected by natural factors. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical method for drought resistance assessment, and provides theoretical support for farmers to grasp the drought information timely and improve the drought resistance ability.

The model in this paper solves the situation of ambiguity and randomness to some extent with the help of grey cloud possibility function. Moreover, the time weight of time degree and variance are used to reduce the volatility and the degree of subjective empowerment. Considering the risk attitude of the decision makers, the prospect theory is applied to make the index weight more objective. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

This study aims to explore the smallholder farmers’ perceptions of climate change and its adaptation options (changing crop variety; improved crop and livestock; soil and water conservation [SWC]; and irrigation practices) and drought indices in the Dire Dawa Administration Zone, Eastern Ethiopia.

A cross-sectional household survey was used. A structured interview schedule for respondent households for key informants and focus group discussions were used. This study used both descriptive statistics and an econometric model. The model was used to compute the determinants of climate adaptation options in the study area. Drought characterization was carried out by DrinC software.

The results revealed households adapted to selected adaptation options. The model results confirmed that education level, farm size, tropical livestock units (TLUs) and access to agricultural extension services have positive and significant impacts on changing crop variety by 0.0014%, 0.045%, 0.032% and 0.035%, respectively. The likelihood of farmers’ decisions to use adaptation strategies (family size, TLU, agricultural extension service and distance from the market) has positive and significant impacts on SWC. The reconnaissance drought index (RDI6) of ONDJFM and AMJJAS showed extreme and severe drought index values of −2.88 and −1.96, respectively.

This study used a locally adopted climate change adaptation intervention for smallholder farmers, revealing the importance of drought characterization indices both seasonally and annually.

The first aim of this study is to show the impact of global warming on temperature and precipitation changes in Algeria. The second objective is to exhibit the strategy planned by the country to mitigate these effects on water resources in the future.

This research assesses the expected changes in temperature, precipitation and SPEI index, over Algeria (16 weather stations), between two horizons (2030, 2050), by using an ensemble of 16 general circulation models under RCP2.6 and RCP8.5 scenarios.

More warming and drought will be experienced under RCP8.5 than RCP2.6 scenario. The highest warming is observed at the Southern stations. However, the lowest precipitation is projected in the western stations. The results of SPEI calculation indicate that the severity of drought spread progressively across time and space. The highest values were observed over 2050 with values varied between 0.15 and −2.08 under RCP2.6 scenario, and range from −0.73 to −2.63 under RCP8.5. These results indicate that Algeria is highly vulnerable to the impact of climate change on water resources, which stressed the need to develop a strategy against this situation.

This study is one of the first to simulate the future climate changes over 16 Algerian weather stations by using an average of 16 general circulation models data, under two RCP scenarios. This study shows the 2030 water development strategy to mitigate the effect of drought and water scarcity on different sectors.

The purpose of this study results and recommendations will have a paramount significance for policymakers, policy advocates, development planners and practitioners who may be in need of such information for reconsideration, evaluation and inclusion into their respective development and humanitarian programming and operational strategies. Above all, the study result has further provided the local community with viable adaptation strategies to climate-induced changes in the study area.

This study was conducted to measure the livelihood vulnerability of Borana pastoralists to climate change and variability in southern Ethiopia. Pastoralists’ households were sampled using multistage sampling techniques. A total of 27 socio-economic and biophysical indicators were used to reflect vulnerability components: adaptive capacity, exposure and sensitivity. Principal component analysis was used to develop weights for indicators and to produce livelihood vulnerability index to classify households according to their level of vulnerability. Ordinal logistic regression was used to identify the determinants of vulnerability to climate-induced stresses.

The results showed that 24.4% of households were highly vulnerable, 60.3% were moderately vulnerable and 15.3% of households were less vulnerable to climate-induced stresses. Factor estimates of the logistic model further revealed that early warning information, bush encroachment, coping strategy, temperature, drought frequency, provision of humanitarian services and food shortage during the normal season of the year have a significant influence on vulnerability in the study area.

The study’s results and recommendations will be of great significance to policymakers, development planners, and practitioners who require such information for reconsideration, evaluation, and inclusion in their respective development and humanitarian program and operational strategies. Most importantly, the study’s findings have provided the local community with practical adaptation strategies to climate-induced changes in the study area.

The study explored pastoralist perception of climate change and variability and measured the livelihood vulnerability of pastoralists’ households to climate change and variability and finally investigated viable adaptation and coping strategies in the study area.

Tropical wetland ecosystems are threatened by climate change but also play a key role in its mitigation and adaptation through management of land use and other drivers. Local-level assessments are needed to support evidence-based wetland management in the face of climate change. This study aims to examine the local communities’ knowledge and perception of climate change in Yala wetland, Kenya, and compare them with observed data on climate trends. Such comparisons are useful to inform context-specific climate change adaptation actions.

The study used a mixed methods approach that combined analysis of climate data with perceptions from the local community. Gridded data on temperature and rainfall for the period from 1981 to 2018 were compared with data on climate change perceptions from semi-structured questionnaires with 286 key informants and community members.

Majority of the respondents had observed changes in climate parameters – severe drought (88.5%), increased frequency of floods (86.0%) and irregular onset and termination of rains (90.9%) in the past 20 years. The perceptions corresponded with climate trends that showed a significant increasing trend in the short rains and the average maximum temperature, high incidence of very wet years and variability in onset and termination of rainfall between 1981 and 2018. Gender, age and education had little influence on knowledge and awareness of climate change, except for frequency of floods and self-reported understanding of climate change. The community perceived the wetland to be important for climate change adaptation, particularly the provision of resources such as grazing grounds during drought.

The study faced challenges of low sample size, use of gridded climate data and reproducibility in other contexts. The results of this study apply to local communities in a tropical wetland in Western Kenya, which has a bi-modal pattern of rainfall. The sample of the study was regional and may therefore not be representative of the whole of Kenya, which has diverse socioeconomic and ecological contexts. Potential problems have been identified with the use of gridded data (for example, regional biases in models), although their usefulness in data scarce contexts is well established. Moreover, the sample size has been found to be a less important factor in research of highly complex socio-ecological systems where there is an attempt to bridge natural and social sciences.

This study addresses the paucity of studies on climate change trends in papyrus wetlands of sub-Saharan Africa and the role of local knowledge and perceptions in influencing the management of such wetlands. Perceptions largely influence local stakeholders’ decisions, and a study that compares perceptions vs “reality” provides evidence for engagement with the stakeholders in managing these highly vulnerable ecosystems. The study showed that the local community’s perceptions corresponded with the climate record and that adaptation measures are already ongoing in the area.

This study presents a case for the understanding of community perceptions and knowledge of climate change in a tropical wetland under threat from climate change and land use change, to inform management under a changing climate.