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Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

Although the environmental and economic impacts of drought have been widely studied, few large‐scale studies have examined the broader social impacts of drought. To fill this knowledge gap, the Australian Institute of Family Studies undertook the Regional and Rural Families Survey in 2007, when a significant part of Australia was experiencing a severe drought. This paper analyses that survey to measure the extent to which drought affects a range of economic, health and social outcomes. Drought is found to have a substantial negative economic and health impact on farmers and others employed in the agricultural sector. There is some evidence that groups that are not employed in agriculture are adversely affected, with a widespread loss of services in drought‐affected areas and some marginal labour market groups (e.g. carers) experiencing poor employment outcomes in a drought‐affected local economy. Policymakers need to take these impacts into account in designing effective responses to future droughts. [ABSTRACT FROM AUTHOR]

The symbiotic synergy between proteome shifts in plants and microbial colonization orchestrates adaptive responses. This thorough review delves into the less explored domain of proteomic and metabolomic changes triggered by drought stress, shedding light on how they are influenced by interactions with microbiota. Notably, microbial mediation at the crossroads of hormone signaling, proteomic and metabolomic dynamics in drought adaptation emerges as a crucial focal point. Understanding the regulatory mechanisms that orchestrate these complex interactions offers a holistic view of the molecular foundation underlying a plant's ability to endure water scarcity. The insights gained from this exploration hold the potential to reshape agricultural practices and enhance drought‐tolerance through microbiota‐mediated mechanisms, supported by proteomic and metabolomic insights. As this review seamlessly integrates the latest developments in understanding drought stress responses, microbiota dynamics, proteomics and metabolomic, it reveals the interconnected molecular basis that underlies these aspects. Specifically, the review emphasizes the crucial role of microbial mediation at the crossroads of hormone signaling, proteomic and metabolomic dynamics during drought adaptation. This enhanced understanding of the intricate interactions among these components presents new opportunities for envisioning sustainable agricultural approaches in the face of the escalating challenges presented by intensifying drought scenarios. [ABSTRACT FROM AUTHOR]

Various studies have been performed on drought hazard assessment at the national or regional scales, but few studies to date at the global scale, especially on global agriculture. In this paper, we utilized an agricultural drought hazard index (DHI), based on both drought severity and drought occurrence rate, derived from 3-month scale Standardized Precipitation Index (SPI) and the phenology data of main crops (rice, maize, wheat, barley, sorghum and soybean) to assess the agricultural drought hazard grades of the world during 1980-2008. The results indicated that area percentages of high and very high agricultural drought hazard zones were approximately 23.57 and 27.19% of the total agricultural area in the world. Moreover, those zones mostly were distributed in central United States, southeastern South America, most of Europe, southwestern Russia, both southern Congo and Nigeria, east-central and southwest China, Southeast Asia and eastern Australia, and most of those areas were also located in semi-humid or humid climate zones. In addition, some regions above were also found to be the very high agricultural drought hazard zones for the main crops: East-central and southwest China for wheat, maize, rice and soybean; Europe for wheat, maize and barley; Southeast Asia for rice; both central United States and southeastern South America for wheat, maize, soybean and sorghum. [ABSTRACT FROM AUTHOR]

This commentary discusses new advances in the predictability of east African rains and highlights the potential for improved early warning systems (EWS), humanitarian relief efforts, and agricultural decision‐making. Following an unprecedented sequence of five droughts, 23 million east Africans faced starvation in 2022, requiring >$2 billion in aid. Here, we update climate attribution studies showing that these droughts resulted from an interaction of climate change and La Niña. Then we describe, for the first time, how attribution‐based insights can be combined with the latest dynamical models to predict droughts at 8‐month lead‐times. We then discuss behavioral and social barriers to forecast use, and review literature examining how EWS might (or might not) enhance agro‐pastoral advisories and humanitarian interventions. Finally, in reference to the new World Meteorological Organization "Early Warning for All" Executive Action Plan, we conclude with a set of recommendations supporting actionable and authoritative climate services. Trust, urgency, and accuracy can help overcome barriers created by limitedfunding, uncertain tradeoffs, and inertia. Understanding how climate change is producing predictable climate extremes now, investing in African‐led EWS, and building better links between EWS and agricultural development efforts can support long‐term adaptation, reducing chronic needs for billions of dollars in reactive assistance. In Africa and beyond, climate change brings increasingly extreme sea surface temperature (SST) gradients. Using climate models, we can often see these extremes coming. Prediction, therefore, offers opportunities for proactive risk management and improved advisory services, if we can create effective societal linkages via cross‐silo collaborations. Plain Language Summary: Eastern East Africa is extremely food insecure. Millions of farmers and pastoralists rely on two meager rainy seasons that arrive twice a year. In the 13 seasons since late 2016, the region experienced eight droughts and three exceptionally wet seasons. Seven droughts were linked to very strong Pacific sea surface temperature (SST) gradients, which arose through an interaction between climate change and La Niña. Climate change will bring more extreme Pacific and Indian Ocean SST gradients. Here, for the first time, we show that these gradients can be very well predicted by the current generation of climate models. We then discuss how such information might be used to inform risk management, agriculture, and livestock management practices. The IGAD Climate Predictions and Applications Center, Ethiopian and Kenyan meteorological agencies, and other groups are providing increasingly accurate climate information. This creates opportunities for more proactive and effective agricultural and pastoral advisory services. Trust, urgency and accuracy can lower uncertainty, reduce risk aversion, and empower poor households and cash‐strapped institutions to act and innovate. Investing now in collaborative African climate systems, participatory advisory services and proactive risk management will help counter these threatening climate extremes. Key Points: Climate change and La Niña are producing extreme Pacific sea surface temperature (SST) gradients, which can be predicted very far in advanceThese Pacific SST forecasts provide robust opportunities for predicting well wet and dry outcomes in East AfricaTrust, urgency and accuracy can overcome barriers due to limited funding, uncertain tradeoffs, and inertia by improving advisory services [ABSTRACT FROM AUTHOR]

Drought and aridity are good measures to study climate change that are measured using several indices. In this study, the performance of Standardized Copula‐based Drought Index (SCDI) is compared with Standardized Precipitation Temperature Index (SPTI) and Reconnaissance Drought Index (RDI) for measuring drought in Balochistan province of Pakistan. These standardized drought indices combine the outcomes of De‐Martone Aridity Index (DAI) and UNEP Aridity Index (UAI). SCDI is calculated using probability distributions and copula models that combine the outcomes of UAI and DAI utilizing data of precipitation, potential evapotranspiration (PE), and temperature. Climate data from nine including arid and humid metrological stations are used to study drought conditions in Balochistan province. SCDI outcomes are graphically and numerically compared with SPTI and RDI. Selected drought indices are compared based on frequency of drought and wet events occurred in moderate, severe, and extreme drought categories, which indicate that SCDI has maximum number of events in these categories. It gives better results due to the utilization of more climate data as compared to RDI and SPTI. Severity–duration frequency curves are used to find future projections which shows that drought severity and drought duration have increasing trend with the passage of time. The indices have more differences in results of arid stations. The results indicate that there are no significant chances of drought at lower time scales, but the chances increase with the increase in time scale. The SCDI may also be more useful for agricultural and hydrological droughts due to temperature and PE variables. This study's results will be helpful for climate planning in Balochistan province. [ABSTRACT FROM AUTHOR]

Wind erosion from agricultural land is an underrated and understudied environmental challenge in Europe. Its societal and policy relevance will likely increase in the near future due to climate change and associated increases in the frequency, severity and patterns of atmospheric events such as droughts.We review the research on this issue and find it to be fragmented, siloed and dominated by natural sciences, leaving important research gaps. The most important gaps that circumscribe a research agenda for the future include specific effects of future climate change on wind erosion, the relevance of wind erosion for public health and ecosystem functioning, farmers' behaviour affecting erosion risk and feedback between land management and environmental change, and appropriate policy approaches to address wind erosion risks. Social science contributions are thus required to make wind erosion research relevant for addressing the related societally most pressing questions.We provide a social–environmental systems perspective to highlight the potential of inter‐ and transdisciplinary research into wind erosion in times of climate change and the increasingly recognized need to transform agriculture towards more sustainability and climate resilience. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

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